Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

Foodborne illnesses caused by Salmonella pose significant threats to worldwide public health safety.In this study,a rapid method for screening viable Salmonella in oyster sauce and milk was developed by utilizing an electronic microbial growth analyzer(EMGA).Target food samples were diluted 10-fold with RVS broth and loaded into test tubes.Test tubes were positioned in the EMGA to determine the bacterial growth curves and the time required to reach the maximum growth rate(Tmgr).Using Salmonella typhimurium(S.typhimurium)asan model species,there was linear relationship between the logarithmic value of viable bacterial concentration(lgC)and Tmgr over the range of 5×101-5×106 CFU/mL,with a detection limit of 10 CFU/mL.For oyster sauce,the regression equation was Tmgr(min)=-80.775lg[C/(CFU/mL)]+754.96(R2=0.9907),and the recovery rates of S.typhimurium ranged from 95.2%to 119.8%,with relative standard deviations(RSD)ranging from 3.5%to 16.3%.For milk,the regression equation was Tmgr(min)=-71.922 lg[C/(CFU/mL)]+618.65(R2=0.9985),with recovery rates ranging from 98.4%to 110.6%and RSD ranging from 6.4%to 12.8%.The EMGA method required only one portable instrument,and involving only three manual steps,i.e.,dilution,transfer,and insertion.When S.typhimurium contamination reached 106 CFU/mL,the total time consumption,from the unwrapping of samples to the readout of bacterial concentration,was no more than 7 h.When applied to detection of actual oyster sauce and milk samples,the new method demonstrated strong consistency with plate counting results in positive detection rates.This method was superior to the plate counting method,which was generally considered as a gold standard,in terms of accuracy,precision,simplicity and efficiency,representing a promising alternative for the on-site screening and quantification of viable Salmonella in oyster sauce and milk products.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Radiation mainly comes from medical radiation,industrial radiation,nuclear waste and atmospheric ultraviolet radiation,etc.,radiation is divided into ionizing radiation and non-ionizing radiation.Studying the effects of ionizing and non-ionizing radiation on drug metabolism,understanding the absorption and distribution of drugs in the body after radiation and the speed of elimination under radiation conditions can provide reasonable guidance for clinical medication.This article reviews the effects of radiation on the pharmacokinetics of different drugs,elaborates the changes of different pharmacokinetics under radiation state,and discusses the reasons for the changes.

Objective To investigate the role of inhibition of Runt-associated transcription factor 1(Runx1)expression in arterial interventional chemotherapy for lung cancer in rats.Methods A549 cells were randomly divided into control group(normal cultured cells),si-NC group(transfected with si-NC plasmid),si-Runx1 group(transfected with si-Runx1 plasmid).Cell proliferation was detected by cell counting kit-8(CCK-8)assay,and the relative expression level of protein was detected by Western blotting.Rats were randomly divided into model group(constructed lung cancer transplanted tumor rats),sh-Runx1 group(knockdown Runx1 expression),OXA arterial group(single arterial interventional chemotherapy),sh-Runx1+OXA group(knockdown Runx1+intravenous chemotherapy),sh-Runx1+OXA arterial group(knockdown Runx1+arterial interventional chemotherapy).After continuous treatment for 3 weeks,tumor volume and weight were measured,TdT mediated dUDP nick end labeling(Tunel)assay was used to detect tumor apoptosis,and Western blot assay was used to detect the expression of migration and invasion-related proteins.Results The survival rates of A549 cells in the control group,si-NC group and si-Runx1 group were(100.00±5.13)％,(99.56±3.44)％and(60.96±7.00)％,respectively;the expression levels of Runx1 protein were 0.84±0.06,0.85±0.06 and 0.20±0.03,respectively.Compared with the control group and si-NC group,the cell survival rate and Runx1 protein expression level in the si-Runx1 group were significantly decreased(all P＜0.05).The tumor volume of the model group,sh-Runx1 group,OXA arterial group,sh-Runx1+OXA group and sh-Runx1+OXA arterial group after the last treatment were(1 069.58±121.79),(819.30±6.98),(639.34±66.64),(486.91±29.88),(416.57±21.58)mm3,respectively;the apoptosis rates were(4.32±0.36)％,(13.95±1.22)％,(15.46±1.14)％,(23.71±2.01)％,(31.16±3.04)％,respectively;the expression levels of E-cadherin protein were 0.31±0.05,0.61±0.07,0.67±0.09,0.92±0.07,1.23±0.13,respectively.The above indexes of sh-Runx1 group,OXA arterial group,sh-Runx1+OXA group and sh-Runx1+OXA arterial group were compared with those of the model group,and the difference was statistically significant(all P＜0.05).The above indexes of sh-Runx1+OXA arterial group were compared with those of sh-Runx1,OXA arterial group and sh-Runx1+OXA group,and the difference was statistically significant(all P＜0.05).Conclusion inhibition of Runx1 can enhance the apoptosis induction and cell metastasis inhibition of arterial interventional chemotherapy in lung cancer rats.

AIM To study the chemical constituents from the large polar fraction of the roots of Lindera reflexa Hemsl.and their antitumor activities.METHODS The large polar fraction from the roots of L.reflexa was isolated and purified by silica gel column,Sephadex LH-20 gel column,semi-preparative HPLC and ODS medium pressure column,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT method.RESULTS Thirteen compounds were isolated and identified as 2,6-dimethoxy-4-hydroxyphenyl-1-O-β-D-glucopyranoside(1),3-hydroxy-4,5-dimethoxyphenol-β-D-glucopyranoside(2),syringin(3),1-O-3,4-dimethoxy-5-hydroxyphenyl-(6-O-3,5-dimethoxygalloyl)-β-D-glucopyranoside(4),p-cymen-7-yl β-D-glucopyranoside(5),pisumionoside(6),staphylionoside D(7),dendranthemoside B(8),lynoiside(9),nudiposide(10),icariside B1(11),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(12),(+)-N-(methoxycarbonyl)-N-norboldine(13).Compounds 3 and 13 showed obvious cytotoxicity against human lung cancer cells(A549)and human gastric cancer cells(MGC80-3).CONCLUSION Compounds 1-13 are isolated from the roots of L.reflexa for the first time.Compounds 3 and 13 have good anti-tumor activities.

Objective: To systematically study the anti-fibrotic effect of N-acetyl-seryl-as partyl-lysyl-proline (Ac-SDKP) on pulmonary fibrosis. Methods: In May 2021, a computer search was performed on CNKI, Wanfang Knowledge Service Platform, VIP.com, China Biomedical Literature Database, Pubmed, OVID and other databases. The retrieval time was from January 2008 to May 2021. Randomized controlled experiments on the inhibition of pulmonary fibrosis by Ac-SDKP were screened. The control group was the pulmonary fibrosis model group and the experimental group was the Ac-SDKP treatment group. The quality of the literature was assessed using the syrcle risk of bias assessment tool, and data were extracted. Data analysis was Performed using revman 5.4 software. Results: 18 papers were included, with a total of 428 animal models. The results of meta analysis showed that the contents of α-smooth muscle actin (α-SMA), type I collagen, type Ⅲ collagen, transforming growth factor-β (TGF-β) and Nodule area in the exPerimental group were lower than those in the control grouP. [SMD=-2.44, 95%CI (-3.71--1.17), P=0.000][SMD=-5.36, 95%CI (-7.13--3.59), P=0.000] [SMD=-3.07, 95%CI (-4.13--2.02), P<0.000][SMD=-2.88, 95%CI (-3.63--2.14), P=0.000] [SMD=-1.80, 95%CI (-2.42--1.18), P=0.000], the content of hydroxy proline in the experimental group was higher than that in the control group [SMD=7.62, 95%CI (4.90-10.33), P=0.000], all indexes included in the literature were statistically significant. Conclusion: Ac-SDKP has obvious inhibitory effect on the process of pulmonary fibrosis, and may become a new clinical drug for the treatment of pulmonary fibrosis.
Rats ; Animals ; Pulmonary Fibrosis ; Rats, Wistar ; Fibrosis ; Disease Models, Animal ; Proline

OBJECTIVES: To explore the difference in CT values between pulmonary thromboembolism and postmortem clot in postmortem CT pulmonary angiography (CTPA) to further improve the application value of virtual autopsy. METHODS: Postmortem CTPA data with the definite cause of death from 2016 to 2019 were collected and divided into pulmonary thromboembolism group (n=4), postmortem clot group (n=5), and control group (n=5). CT values of pulmonary trunk and left and right pulmonary artery contents in each group were measured and analyzed statistically. RESULTS: The average CT value in the pulmonary thromboembolism group and postmortem clot group were (168.4±53.8) Hu and (282.7±78.0) Hu, respectively, which were lower than those of the control group (1 193.0±82.9) Hu (P<0.05). The average CT value of the postmortem clot group was higher than that of the pulmonary thromboembolism group (P<0.05). CONCLUSIONS CT value is reliable and feasible as a relatively objective quantitative index to distinguish pulmonary thromboembolism and postmortem clot in postmortem CTPA. At the same time, it can provide a scientific basis to a certain extent for ruling out pulmonary thromboembolism deaths.
Humans ; Autopsy ; Thrombosis ; Pulmonary Embolism/diagnostic imaging* ; Tomography, X-Ray Computed ; Angiography ; Cadaver

Objective: To analyze the association between exposure patterns of adverse childhood experiences (ACEs) and anxiety symptom trajectories in medical college students. Methods: A survey was conducted on first-year students from Anhui Medical College and Anqing Medical College, using the Childhood Abuse Questionnaire, Family Disability Questionnaire, Childhood Adverse Social Experience Item, and Anxiety Self Rating Scale. The baseline survey was conducted from November to December 2019, and two follow-up visits were conducted once every six months until November to December 2020. The latent class analysis (LCA) was used to analyze the exposure patterns of ACEs. The latent class growth analysis (LCGA) was used to analyze the development trajectory of anxiety symptoms. The multiple logistic regression model was used to analyze the correlation between different exposure patterns of ACEs and the trajectory of anxiety symptom trajectories. Results: A total of 3 662 college students aged (19.2±1.0) were surveyed. The LCA showed that the exposure patterns of ACEs could be divided into the "high ACEs" group (13.4%), "high neglect/emotional abuse" group (25.7%), "high family dysfunction" group (6.9%), "high neglect" group (27.1%), and "low ACEs" group (26.3%). The LCGA divided anxiety trajectories into four groups: "high anxiety decline" (7.1%),"anxiety increase "(4.1%), "moderate anxiety"(52.9%), and "low anxiety"(35.9%). Using the low ACEs group as a reference group, compared with the low anxiety trajectory, the high ACEs group, high neglect/emotional abuse group, high family dysfunction group, high neglect group, and medium to high-level anxiety trajectory were all associated with an increased risk (P<0.05). Conclusion: There is heterogeneity in ACEs exposure patterns among medical college students, and ACEs exposure patterns are important influencing factors for anxiety symptom trajectories.
Humans ; Adverse Childhood Experiences ; Anxiety/epidemiology* ; Child Abuse/psychology* ; Students/psychology* ; Surveys and Questionnaires ; Adolescent ; Young Adult