Objective:To construct an assessment model on the basis of dynamic programming algorithm for medical device,so as to improve the management level for medical devices.Methods:A assessment model for medical device was constructed on the basis of the presupposition,basic ideas,solution steps and algorithm elements of dynamic programming algorithm,and the management of medical devices was transferred and carried out according to the state of the model at the multi-stage when decided problem.A total of 200 used medical devices in clinical application in Zhongshan City People's Hospital from January 2022 to December 2023 were selected.The conventional management method was adopted to manage these medical devices from January to December 2022,and the assessment model(dynamic programming algorithm)on the basis of dynamic programming algorithm for these medical devices was adopted to manage them from January to December 2023.The management level for medical devices,the score for management indicators,the incidences of low risk,medium risk and high risk of adverse event were compared before and after the dynamic programming algorithm was applied,and the difference of the scores of assessing comprehensive business ability of management team was also compared.Results:The standard placement rate,standard recording rate and availability rate of equipment were respectively 85.5%,84.0%and 84.5%after the dynamic programming algorithm was applied,which were higher than those before it was applied,and the failure rate of equipment was 2.5%,which was lower than that before it was applied,and the differences were statistically significant(x2=13.888,12.516,14.240,14.414,P＜0.05).The scores of resource allocation,information basis,technical support and guarantee for operation environment of devices were respectively(92.54±4.69),(93.65±3.65),(94.58±3.65)and(92.47±3.65)after the dynamic programming algorithm was applied,which were higher than these before it was applied,and the differences were statistically significant(t=14.574,18.419,11.438,12.981,P＜0.05).The ratios of the adverse events with low risk,medium risk and high risk were respectively 6%,5%and 2%,which were lower than these before it was applied,and the differences were statistically significant(x2=12.754,12.876,11.348,P＜0.05).The scores of comprehensive business ability of the technical support team,research team,promotion team and auxiliary management team for medical device were respectively(94.56±4.69),(92.65±3.14),(94.69±4.98)and(95.68±4.14)after the dynamic planning algorithm was applied,which were higher than these before it was applied,and the difference was statistically significant(t=12.170,18.682,12.449,18.269,P＜0.05).Conclusion:The application of the assessment model on the basis of dynamic programming algorithm for medical devices in management for medical device can improve the management level for device,and reduce the incidence of adverse events,and enhance the comprehensive business ability of management team for device.

Objective To analyze the influencing factors of postoperative hypoxemia after whole lung lavage (WLL) in patients with pneumoconiosis and to evaluate the predictive value of lung ultrasound scores. Methods A total of 757 patients with pneumoconiosis who underwent unilateral large-volume WLL were selected as the research subjects by continuous sampling method. The patients with hypoxemia after large-volume WLL were assigned to the observation group (82 cases), and those without hypoxemia were assigned to the control group (675 cases). Patients′ basic information and clinical data of the two groups were collected using a retrospective investigation method. The binary logistic regression analysis was used to analyze the influencing factors of hypoxemia after large-volume WLL in patients with pneumoconiosis, and receiver operating characteristic (ROC) curve analysis was conducted to assess the predictive value of ultrasound indicators. Results The combined rate of postoperative hypoxemia in the patients was 10.8% (82/757). The multivariate logistic regression analysis showed that the risk of hypoxemia in patients aged ≥65 years was higher than that in patients aged <65 years (P<0.05). The risk of hypoxemia was higher in patients with increased pre-extubation lung ultrasound score than those with lower pre-extubation lung ultrasound score (P<0.01). Patients with a higher partial pressure of carbon dioxide in arterial blood (PaCO₂) had a higher risk of concurrent hypoxemia than those with a lower pressure (P<0.01), while patients with lower arterial partial pressure of oxygen (PaO₂) had a higher risk of concurrent hypoxemia than those with higher PaO₂ (P<0.01). Pearson correlation analysis showed that lung ultrasound scores were negatively correlated with PaO₂ and positively correlated with PaCO₂ (both P<0.01). The ROC curve analysis showed that the area under the curve was 0.855, the 95% confidence interval was 0.828 to 0.879, the diagnostic sensitivity was 84.2%, and the specificity was 75.1%. Conclusion Age, pre-extubation lung ultrasound score, and PaCO₂ are risk factors for hypoxemia after WLL in patients with pneumoconiosis, while PaO₂ is a protective factor. Pre-extubation lung ultrasound scoring demonstrates good accuracy in predicting postoperative hypoxemia among pneumoconiosis patients after WLL.

Objective To investigate the effects of periodontitis induced by Prevotella nigrescens(Pn)combined with ligation on cognitive functions in mice.Methods Twenty-four C57BL/6J mice were randomly divided into control group,ligation group,and ligation+Pn treatment(P+Pn)group.Experimental periodontitis was induced by silk ligation of the first molars followed by topical application of Pn for 6 weeks.After modeling,alveolar bone resorption was assessed using micro-CT and histological analysis.Learning and memory abilities of the mice were evaluated using open field test(OFT),novel object recognition test(NORT),and Morris water maze test(MWM).Seven weeks after the start of modeling,the mice were sacrificed for examining histopathological changes in the hippocampus using HE and Nissl staining.Results After 6 weeks of molar ligation,micro-CT revealed horizontal alveolar bone resorption and furcation exposure in the mice,and histological analysis showed apical migration of the junctional epithelium,epithelial ridge hyperplasia,and lymphocyte infiltration,and these changes were obviously worsened in P+Pn group.Alveolar bone height decreased significantly in both ligation groups compared to the control group.Cognitive tests showed that the mice in both of the ligation groups traveled shorter distances in OFT,showed reduced novel object preference in NORT,and exhibited longer escape latencies in MWM,and the mice in P+Pn group had significantly poorer performances in the tests.Histologically,obvious neuronal cytoplasmic degeneration,necrosis,nuclear pyknosis,vacuolation,and reduced Nissl bodies and viable neurons were observed in the hippocampal regions of the mice in the two ligation groups.Conclusion Pn infection aggravates alveolar bone destruction,accelerates necrosis and causes morphological abnormalities of neuronal cells in the hippocampus to reduce cognitive functions of mice with periodontitis.

Objective:To construct an assessment model on the basis of dynamic programming algorithm for medical device,so as to improve the management level for medical devices.Methods:A assessment model for medical device was constructed on the basis of the presupposition,basic ideas,solution steps and algorithm elements of dynamic programming algorithm,and the management of medical devices was transferred and carried out according to the state of the model at the multi-stage when decided problem.A total of 200 used medical devices in clinical application in Zhongshan City People's Hospital from January 2022 to December 2023 were selected.The conventional management method was adopted to manage these medical devices from January to December 2022,and the assessment model(dynamic programming algorithm)on the basis of dynamic programming algorithm for these medical devices was adopted to manage them from January to December 2023.The management level for medical devices,the score for management indicators,the incidences of low risk,medium risk and high risk of adverse event were compared before and after the dynamic programming algorithm was applied,and the difference of the scores of assessing comprehensive business ability of management team was also compared.Results:The standard placement rate,standard recording rate and availability rate of equipment were respectively 85.5%,84.0%and 84.5%after the dynamic programming algorithm was applied,which were higher than those before it was applied,and the failure rate of equipment was 2.5%,which was lower than that before it was applied,and the differences were statistically significant(x2=13.888,12.516,14.240,14.414,P＜0.05).The scores of resource allocation,information basis,technical support and guarantee for operation environment of devices were respectively(92.54±4.69),(93.65±3.65),(94.58±3.65)and(92.47±3.65)after the dynamic programming algorithm was applied,which were higher than these before it was applied,and the differences were statistically significant(t=14.574,18.419,11.438,12.981,P＜0.05).The ratios of the adverse events with low risk,medium risk and high risk were respectively 6%,5%and 2%,which were lower than these before it was applied,and the differences were statistically significant(x2=12.754,12.876,11.348,P＜0.05).The scores of comprehensive business ability of the technical support team,research team,promotion team and auxiliary management team for medical device were respectively(94.56±4.69),(92.65±3.14),(94.69±4.98)and(95.68±4.14)after the dynamic planning algorithm was applied,which were higher than these before it was applied,and the difference was statistically significant(t=12.170,18.682,12.449,18.269,P＜0.05).Conclusion:The application of the assessment model on the basis of dynamic programming algorithm for medical devices in management for medical device can improve the management level for device,and reduce the incidence of adverse events,and enhance the comprehensive business ability of management team for device.

Objective:This study used data-independent acquisition (DIA) proteomics to analyze plasma protein expression in sepsis-induced coagulopathy (SIC), identify key biomarkers, and develop a diagnostic model.Methods:This prospective study included 46 adult sepsis patients from the intensive care unit. Patients were categorized into a general sepsis group ( n=26) and an SIC group ( n=20) based on established SIC criteria. Plasma samples underwent proteomic and bioinformatics analyses to identify differentially expressed protein (DEP) using LASSO regression and Random Forest. A diagnostic model was constructed and assessed via receiver operating characteristic (ROC) curve analysis. Results:The baseline data revealed that SIC patients exhibited longer prothrombin times, lower platelet counts, and higher D-dimer, fibrin degradation products, blood lactate, SOFA scores, and APACHE Ⅱ scores compared with general sepsis patients ( P<0.05). DIA proteomics identified 2 637 proteins, with 240 DEP meeting the criteria (fold change >1.5, P<0.05), including 81 upregulated and 159 downregulated DEP. Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear. Gene ontology (GO) annotation showed that DEP were mainly involved in cellular physiology, biological regulation, and stress response processes in biological processes. Domain annotation revealed a predominance of immunoglobulin V regions in DEP, which are crucial for antigen recognition and binding. KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity, glycosylphosphatidylinositol anchor biosynthesis, tumor necrosis factor signaling, and NF-κB signaling. LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP. The SIC diagnostic nomogram showed an area under the curve of 0.896, with 0.731 specificity and 0.900 sensitivity. Conclusion:The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis.

Lung cancer poses a serious threat to global public health security.Chemotherapy,as the main strategy for cancer treatment,faces challenges such as high toxicity and drug resistance.Anticancer peptides have the potential of being developed into new anticancer drugs due to their advantages of broad-spectrum anticancer activity,rapid action,and difficulty in generating drug resistance,but they also face shortcomings such as weak activity and strong toxic side effects.The weakly acidic microenvironment of tumors(pH 6.5-6.8)provides a good idea for the design of anticancer peptides of high-efficiency and low-toxicity.Previously,we designed the acid-sensitive antibacterial peptide pHly-1 using the wolf spider(Lycosa singoriensis)toxin Lycosin-Ⅰ as a template.In this study,we found that pHly-1 also had acid-sensitive anticancer activity.Further alanine scanning analysis of pHly-1 was carried out,and we ob-tained a mutant pHTP-2 with better acid sensitivity,whose IC50(half maximal inhibitory concentration)against A549 cells was 15.68 μmol/L at pH 6.6 and was greater than 100 μmol/L at pH 7.4.At pH 6.6,pHTP-2 could act on various lung cancer cell lines and induce the death of A549 cells by rapid ly-sis;at pH 7.4,500 μmol/L pHTP-2 had weak toxicity to red blood cells(the hemolysis rate was ap-proximately 38％)and primary myocardial cells(the inhibition rate was 49.7％,with P＜0.05).Analy-sis of its charge,particle size,morphology,and secondary structure showed that at pH 6.6,the histidine in the sequence of pHTP-2 was protonated,increasing the positive charge(P＜0.01),decreasing the hy-drated particle size(P＜0.05)and forming an α-helical structure to induce membrane lysis of A549 cells.At pH 7.4,it was deprotonated,the positive charge decreases,a β-sheet structure was formed and self-aggregation occurred,limiting its effect on the A549 cell membrane and showing weak activity.In summary,pHTP-2 could respond to the weakly acidic microenvironment of tumors to exert selective cyto-toxic activity,effectively overcoming the shortcomings of anticancer peptides such as low efficiency and high toxicity.Our findings suggest that it is a high-quality lead molecule for anticancer drugs.

Lung cancer poses a serious threat to global public health security.Chemotherapy,as the main strategy for cancer treatment,faces challenges such as high toxicity and drug resistance.Anticancer peptides have the potential of being developed into new anticancer drugs due to their advantages of broad-spectrum anticancer activity,rapid action,and difficulty in generating drug resistance,but they also face shortcomings such as weak activity and strong toxic side effects.The weakly acidic microenvironment of tumors(pH 6.5-6.8)provides a good idea for the design of anticancer peptides of high-efficiency and low-toxicity.Previously,we designed the acid-sensitive antibacterial peptide pHly-1 using the wolf spider(Lycosa singoriensis)toxin Lycosin-Ⅰ as a template.In this study,we found that pHly-1 also had acid-sensitive anticancer activity.Further alanine scanning analysis of pHly-1 was carried out,and we ob-tained a mutant pHTP-2 with better acid sensitivity,whose IC50(half maximal inhibitory concentration)against A549 cells was 15.68 μmol/L at pH 6.6 and was greater than 100 μmol/L at pH 7.4.At pH 6.6,pHTP-2 could act on various lung cancer cell lines and induce the death of A549 cells by rapid ly-sis;at pH 7.4,500 μmol/L pHTP-2 had weak toxicity to red blood cells(the hemolysis rate was ap-proximately 38％)and primary myocardial cells(the inhibition rate was 49.7％,with P＜0.05).Analy-sis of its charge,particle size,morphology,and secondary structure showed that at pH 6.6,the histidine in the sequence of pHTP-2 was protonated,increasing the positive charge(P＜0.01),decreasing the hy-drated particle size(P＜0.05)and forming an α-helical structure to induce membrane lysis of A549 cells.At pH 7.4,it was deprotonated,the positive charge decreases,a β-sheet structure was formed and self-aggregation occurred,limiting its effect on the A549 cell membrane and showing weak activity.In summary,pHTP-2 could respond to the weakly acidic microenvironment of tumors to exert selective cyto-toxic activity,effectively overcoming the shortcomings of anticancer peptides such as low efficiency and high toxicity.Our findings suggest that it is a high-quality lead molecule for anticancer drugs.

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.

Objective:This study used data-independent acquisition (DIA) proteomics to analyze plasma protein expression in sepsis-induced coagulopathy (SIC), identify key biomarkers, and develop a diagnostic model.Methods:This prospective study included 46 adult sepsis patients from the intensive care unit. Patients were categorized into a general sepsis group ( n=26) and an SIC group ( n=20) based on established SIC criteria. Plasma samples underwent proteomic and bioinformatics analyses to identify differentially expressed protein (DEP) using LASSO regression and Random Forest. A diagnostic model was constructed and assessed via receiver operating characteristic (ROC) curve analysis. Results:The baseline data revealed that SIC patients exhibited longer prothrombin times, lower platelet counts, and higher D-dimer, fibrin degradation products, blood lactate, SOFA scores, and APACHE Ⅱ scores compared with general sepsis patients ( P<0.05). DIA proteomics identified 2 637 proteins, with 240 DEP meeting the criteria (fold change >1.5, P<0.05), including 81 upregulated and 159 downregulated DEP. Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear. Gene ontology (GO) annotation showed that DEP were mainly involved in cellular physiology, biological regulation, and stress response processes in biological processes. Domain annotation revealed a predominance of immunoglobulin V regions in DEP, which are crucial for antigen recognition and binding. KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity, glycosylphosphatidylinositol anchor biosynthesis, tumor necrosis factor signaling, and NF-κB signaling. LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP. The SIC diagnostic nomogram showed an area under the curve of 0.896, with 0.731 specificity and 0.900 sensitivity. Conclusion:The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis.

Objective:To systematically synthesize the illness stigma experiences of stroke patients.Methods:A systematic search was conducted in PubMed, Cochrane Library, Embase, Web of Science, China Biology Medicine disc, China National Knowledge Infrastructure, Wanfang Data, and VIP for qualitative studies exploring illness stigma in stroke patients. The search period extended from database inception to September 30, 2024. A Meta-synthesis approach was employed to integrate the findings.Results:A total of fourteen articles were included and ten new categories were extracted and synthesized into four integraion results: sources of illness stigma, key influencing factors of illness stigma, manifestations and impacts of illness stigma, and coping strategies illness stigma.Conclusions:Illness stigma is a significant barrier to stroke rehabilitation. Nurses should be aware of the characteristics of illness stigma, conduct early identification, and develop individualized strategies for prevention and intervention. It is essential to help patients build multi-dimensional support systems involving society and family, and to guide them in gradually accepting and adapting to their new self.