ObjectiveTo clarify the anti-inflammatory and lung-protective effects of Yantiao prescription on lipopolysaccharide （LPS）-induced acute lung injury （ALI）， and to explore the impact of Yantiao prescription on the metabolic pathways of arachidonic acid （AA） in vivo. MethodsThirty male C57BL/6J mice were randomly divided into the following groups based on body weight： normal group， model group， dexamethasone group （2 mg·kg^-1）， low-dose Yantiao prescription group （18 g·kg^-1）， and high-dose Yantiao prescription group （36 g·kg^-1）， with 6 mice in each group. The ALI mouse model was established by intraperitoneal injection of LPS. The treatment groups received oral gavage once a day for 7 consecutive days， and serum and lung tissue were collected at the end of the experiment. The content of pro-inflammatory cytokines tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in serum was detected by enzyme-linked immunosorbent assay （ELISA）. Hematoxylin-eosin （HE） staining was used to assess lung tissue pathology. The wet/dry weight ratio （W/D） and myeloperoxidase （MPO） activity in lung tissue were measured. The content of AA metabolites in serum and lung tissue was measured by liquid chromatography triple quadrupole-mass spectrometry （LC-MS/MS）. ResultsCompared with the conditions in the normal group， the content of serum pro-inflammatory cytokines TNF-α， IL-1β， and IL-6 in the model group was significantly increased （P<0.01）. The alveolar structure in mice was severely damaged， with markedly thickened alveolar walls and extensive inflammatory cell infiltration. The W/D ratio and MPO activity in lung tissue were significantly increased （P<0.01）. The content of AA metabolites， including prostaglandin D₂ （PGD₂）， prostaglandin E₂ （PGE₂）， 11（S）-hydroxy-eicosatetraenoic acid ［11（S）-HETE］， and 5-hydroxy-eicosatetraenoic acid （5-HETE） in serum and lung tissue was significantly increased （P<0.05）， while the content of 11，12-epoxyeicosatrienoic acid （11，12-EET） and 14，15-epoxyeicosatrienoic acid （14，15-EET） in serum was significantly decreased （P<0.01）. Compared with the results in the model group， the content of serum pro-inflammatory cytokines TNF-α， IL-1β， and IL-6 in the dexamethasone group， low-dose Yantiao prescription group， and high-dose Yantiao prescription group was significantly reduced （P<0.05）. Mild thickening of alveolar walls， scattered inflammatory cell infiltration， and relatively intact tissue structure with improved alveolar architecture were observed. The W/D ratio and MPO activity in lung tissue were significantly reduced （P<0.01）. The content of AA metabolites PGD₂， PGE₂， 11（S）-HETE， and 5-HETE in serum from the dexamethasone group was significantly decreased （P<0.05）， while the content of 14，15-EET in serum significantly increased （P<0.01）， and the content of 5-HETE in lung tissue significantly decreased （P<0.01）. In the low-dose and high-dose Yantiao prescription groups， the content of AA metabolites PGD₂， PGE₂， 11（S）-HETE， and 5-HETE in serum and lung tissue was significantly decreased （P<0.05）， while the content of 11，12-EET in both serum and lung tissue was significantly increased （P<0.05）. ConclusionYantiao prescription has significant protective effects against LPS-induced ALI， which are related to its regulation of AA metabolic pathways in vivo.

Blue light inactivation technology, particularly at the 405 nm wavelength, has demonstrated distinct and multifaceted mechanisms of action against both Gram-positive and Gram-negative bacteria, offering a promising alternative to conventional antibiotic therapies. For Gram-positive pathogens such as Bacillus cereus, Listeria monocytogenes, and methicillin-resistant Staphylococcus aureus (MRSA), the bactericidal effects are primarily mediated by endogenous porphyrins (e.g., protoporphyrin III, coproporphyrin III, and uroporphyrin III), which exhibit strong absorption peaks between 400-430 nm. Upon irradiation, these porphyrins are photoexcited to generate cytotoxic reactive oxygen species (ROS), including singlet oxygen, hydroxyl radicals, and superoxide anions, which collectively induce oxidative damage to cellular components. Early studies by Endarko et al. revealed that (405±5) nm blue light at 185 J/cm² effectively inactivated L. monocytogenes without exogenous photosensitizers, supporting the hypothesis of intrinsic photosensitizer involvement. Subsequent work by Masson-Meyers et al. demonstrated that 405 nm light at 121 J/cm² suppressed MRSA growth by activating endogenous porphyrins, leading to ROS accumulation. Kim et al. further elucidated that ROS generated under 405 nm irradiation directly interact with unsaturated fatty acids in bacterial membranes, initiating lipid peroxidation. This process disrupts membrane fluidity, compromises structural integrity, and impairs membrane-bound proteins, ultimately causing cell death. In contrast, Gram-negative bacteria such as Salmonella, Escherichia coli, Helicobacter pylori, Pseudomonas aeruginosa, and Acinetobacter baumannii exhibit more complex inactivation pathways. While endogenous porphyrins remain central to ROS generation, studies reveal additional photodynamic contributors, including flavins (e.g., riboflavin) and bacterial pigments. For instance, H. pylori naturally accumulates protoporphyrin and coproporphyrin mixtures, enabling efficient 405 nm light-mediated inactivation without antibiotic resistance concerns. Kim et al. demonstrated that 405 nm light at 288 J/cm² inactivates Salmonella by inducing genomic DNA oxidation (e.g., 8-hydroxy-deoxyguanosine formation) and disrupting membrane functions, particularly efflux pumps and glucose uptake systems. Huang et al. highlighted the enhanced efficacy of pulsed 405 nm light over continuous irradiation for E. coli, attributing this to increased membrane damage and optimized ROS generation through frequency-dependent photodynamic effects. Environmental factors such as temperature, pH, and osmotic stress further modulate susceptibility, sublethal stress conditions (e.g., high salinity or acidic environments) weaken bacterial membranes, rendering cells more vulnerable to subsequent ROS-mediated damage. The 405 nm blue light inactivates drug-resistant Pseudomonas aeruginosa through endogenous porphyrins, pyocyanin, and pyoverdine, with the inactivation efficacy influenced by bacterial growth phase and culture medium composition. Intriguingly, repeated 405 nm exposure (20 cycles) failed to induce resistance in A. baumannii, with transient tolerance linked to transient overexpression of antioxidant enzymes (e.g., superoxide dismutase) or stress-response genes (e.g., oxyR). For Gram-positive bacteria, porphyrin abundance dictates sensitivity, whereas in Gram-negative species, membrane architecture and accessory pigments modulate outcomes. Critically, ROS-mediated damage is nonspecific, targeting DNA, proteins, and lipids simultaneously, thereby minimizing resistance evolution. The 405 nm blue light technology, as a non-chemical sterilization method, shows promise in medical and food industries. It enhances infection control through photodynamic therapy and disinfection, synergizing with red light for anti-inflammatory treatments (e.g., acne). In food processing, it effectively inactivates pathogens (e.g., E. coli, S. aureus) without altering food quality. Despite efficacy against multidrug-resistant A. baumannii, challenges include device standardization, limited penetration in complex materials, and optimization of photosensitizers/light parameters. Interdisciplinary research is needed to address these limitations and scale applications in healthcare, food safety, and environmental decontamination.

Objective To evaluate the effect of donor gender on short-term survival rate of lung transplant recipients. Methods A retrospective analysis was conducted on the data of 1 066 lung transplant recipients. The log-rank test was used to evaluate the differences in short-term fatality among different donor gender groups and donor-recipient gender combination groups. Multivariate Cox regression, propensity score (PS) regression, and propensity score matching (PSM) were employed to control for confounding factors and further assess the differences in fatality. Subgroup analyses were also performed based on donor gender. Results Multivariate Cox regression analysis showed no statistically significant differences in fatality at 30 days, 1 year, 2 years and 3 years postoperatively between male and female donor groups (all P>0.05). After PS regression and PSM, univariate Cox regression analysis indicated that recipients from female donors had a higher fatality at 2 years postoperatively compared to those from male donors, with hazard ratios (95% confidence intervals) of 1.29 (1.01-1.65) and 1.36 (1.03-1.80) respectively. Multivariate Cox regression analysis also revealed no statistically significant differences in fatality at various follow-up time points among different donor-recipient gender combination groups (all P>0.05). Subgroup analyses based on donor sex showed no statistically significant differences in fatality among recipients of different gender within either male or female donor groups (all P>0.05). Conclusions Female donors may reduce the short-term postoperative survival rate of lung transplant recipients, but this negative impact is not sustainable in the long term. At present, there is no evidence to support the inclusion of sex as a factor in lung allocation rules.

OBJECTIVE: To investigate platelet count trajectories after induction therapy with venetoclax combined with azacitidine (VA regimen) in newly diagnosed AML patients and further analyze its clinical significance. METHODS: Clinical date of 50 newly diagnosed AML patients who received VA treatment from March 2020 to July 2023 in Department of Hematology of the First Hospital of Lanzhou University were retrospectively collected. The platelet trajectories after induction chemotherapy were constructed by using group-based trajectory modeling. To study the association between diverse trajectories of platelet counts and compound complete remission (cCR) rate, overall response rate (ORR), minimal residual disease (MRD) negative rate and overall survival (OS) rate. The Cox proportional hazard model was used to evaluate the relationship between platelet trajectory and OS. The logistic regression was used to analyze the influence of individual characteristics on platelet trajectory. RESULTS: Two platelet trajectories were identified based on the model, including platelet slowly increased group (n=31, 62.0%) and platelet rapidly increased group (n=19, 38.0%). There were statistically significant differences in cCR rate, ORR and OS rate between platelet slowly increased group and platelet rapidly increased group (all P < 0.05). The Cox regression analysis showed that platelet rapidly increased group was associated with a decreased risk of mortality compared with platelet slowly increased group (HR=0.153, 95%CI : 0.045-0.527, P =0.003). Logistic regression analysis showed that IDH1/2 mutation (OR =3.908, 95%CI : 1.023-14.923, P =0.046) and platelet transfusion (OR =0.771, 95%CI : 0.620-0.959, P =0.020) were independent influencing factors of platelet trajectory. CONCLUSION The dynamic trajectory of platelet counts in newly diagnosed AML patients who received VA treatment can serve as a significant indicator to observe the efficacy and prognosis. The platelet rapidly increased is an independent protective factor for good prognosis. TheIDH1 /2 mutation and platelet transfusion are independent influencing factors of platelet trajectory.
Humans ; Leukemia, Myeloid, Acute/blood* ; Sulfonamides/administration & dosage* ; Azacitidine/therapeutic use* ; Platelet Count ; Retrospective Studies ; Bridged Bicyclo Compounds, Heterocyclic/administration & dosage* ; Male ; Female ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Induction Chemotherapy ; Survival Rate

This paper explains the mechanism of the mutual switching between physiological sleep and wakefulness from the aspects of the sleep circadian system and the sleep homeostasis system. In the circadian rhythm system, with the suprachiasmatic nucleus as the core, the anatomical connections between the suprachiasmatic nucleusand various systems that affect sleep are summarized, starting from the suprachiasmatic nucleus, passing through the four pathways of the melatonin system, namely, subventricular area of the hypothalamus, the ventrolateral nucleus of the preoptic area, orexin neurons, and melatonin, then the related mechanisms of their regulation of sleep and wakefulness are expounded. In the sleep homeostasis system, with adenosine and prostaglandin D2 as targets, the role of hypnogen in sleep arousal mechanisms in regulation is also expounded.

Objective To observe the effects of acupoint catgut embedding therapy on body mass,lipid metabolism,serum leptin and mRNA and protein expressions of hypothalamic leptin receptor(LepR)-mediated Janus kinase 2(JAK2)/signal transducer and activator of transcription 3(STAT3)pathway in rats with diet-induced obesity(DIO).Methods Forty male SD rats were randomly divided into 10 in normal group and 30 in modeling group.A high-fat diet was used to establish the DIO rat model.After successful modeling,the modeled rats were randomly divided into the model group,the acupoint catgut embedding group and the acupoint catgut embedding + AG490(JAK2/STAT3 pathway blocker)group,with 10 rats in each group.The acupoint catgut embedding group and the acupoint catgut embedding + AG490 group were embedded on day(s)1,8,15 and 22 after successful modeling,the acupoints were selected from the Zhongwan(RN12),Shuidao(ST28),Tianshu(ST25),Pishu(BL20),Weishu(BL21),Sanjiaoshu(BL22)with a total of 4 treatments,and the acupoint catgut embedding + AG490 group was injected intraperitoneally with 1 mg/kg of AG490 every day during the treatment period;the normal group and the model group were only grasped and fixed.Body mass was measured before and after treatment.Lipid metabolism indexes of triglyceride(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),and serum leptin levels were measured after treatment,and the mRNA expressions of hypothalamus LepR,JAK2 and STAT3 were detected by real-time quantitative polymerase chain reaction(RT-PCR),and the protein expressions of hypothalamus LepR,JAK2 and STAT3 were detected by Western Blot.Results Before treatment,compared with the normal group,the body mass of the model group,the acupoint catgut embedding group,and the acupoint catgut embedding+AG490 group were all elevated(P＜0.01),and compared with the model group,there was no significant difference in the body mass between the acupoint catgut embedding group and the acupoint catgut embedding+AG490 group(P＞0.05).After treatment,compared with the normal group,body mass,leptin and TG,TC,LDL-C levels were increased,and mRNA and protein expression levels of LepR,JAK2,STAT3 were decreased in the model group(all P＜0.01);compared with the model group,body mass,leptin and TG,TC,LDL-C levels were decreased in the acupoint catgut embedding group,and mRNA and protein levels of LepR,JAK2,STAT3 were increased in the acupoint catgut embedding + AG490 group(all P＜0.01);compared with the acupoint catgut embedding + AG490 group,the body mass,leptin and TG,TC,LDL-C levels were decreased,and mRNA and protein levels of LepR,JAK2,STAT3 were increased in the acupoint catgut embedding group(P＜0.05 or P＜0.01).Conclusion Acupoint catgut embedding has a good effect on weight loss and lipid reduction in DIO rats,and its central mechanism may be related to the down-regulation of serum leptin level and activation of hypothalamic LepR-mediated JAK2/STAT3 pathway.

Objective To investigate the relationship between perioperative nutritional risk and venous thromboembolism(VTE)in patients with hip fracture.Methods A total of 379 patients with unilateral hip fracture due to fall or sprain who underwent elective surgery were selected and divided into the non-VTE group(246 cases)and the VTE group(133 cases)according to whether or not VTE occurred during perioperative period.Basic information,surgical and anesthesia records,nutritional risk related indicators,inflammatory indicators and outcome indicators of patients were collected.Multiple Logistic regression was used to analyze the independent influencing factors of perioperative VTE.Receiver operating characteristics(ROC)curves were used to assess the ability to discriminate independent factors,and DeLong test was used to compare area under the curve(AUC).Results Compared with the non-VTE group,the proportion of patients in the VTE group was older,complicated with hypertension,the time to visit hospital more than 2 days,received(hollow/intramedullary nail)internal fixation,perioperative blood transfusion,ASA gradeⅢtoⅣ,and higher nutritional risk screening Table(NRS)-2002 scores on admission and higher postoperative neutrophil/lymphocyte ratio(NLR).Nutritional prognosis index(PNI),hemoglobin(Hb)and prealbumin(PA)at admission and after operation were lower in the VTE group than those in the non-VTE group(P＜0.01).Multivariate Logistic regression analysis showed that PNI was decreased,NRS-2002 scores and PA were increased,and the time of visit hospital was>2 days after internal fixation.American College of Anesthesiologists(ASA)gradesⅢ-Ⅳwere independent risk factors for perioperative VTE of hip fracture(P＜0.05).ROC curve analysis showed that the AUC(95%CI)of NRS-2002 at admission was 0.739(0.692-0.783),and that of PNI at admission was 0.720(0.672-0.765),both of which were better than other influencing factors(P＜0.01).Conclusion NRS-2002 and PNI are good predictors of perioperative VTE in patients with hip fracture.

Objective To construct and validate a risk prediction model for poor inhalation in chronic obstructive pulmonary disease(COPD)patients receiving inhaler therapy,providing a decision support tool for personalized prevention of poor inhalation.Methods A cross-sectional study was conducted to collect data related to COPD patients receiving inhaler therapy,forming a dataset.The dataset was randomly divided into a training set and a test set in a ratio of 4∶1.Four different methods for missing value imputation,3 methods for variable feature selection,and 18 machine learning algorithms were employed to successfully construct 216 models on the training set.The monte carlo simulation method was used for resampling in the test set to validate the models,with the area under curve(AUC),accuracy,precision,recall,and F1 score used to evaluate model performance.The optimal model was selected to build the poor inhalation prediction platform.Results A study involving 308 patients with COPD found that 135(43.8%)were at risk of adverse inhalation.Using 33 predictor variables,216 risk prediction models were developed.Of these models,the ensemble learning algorithm yielded the highest average AUC of 0.844,with a standard deviation of 0.058[95%CI=(0.843,0.845)].The differences in predictive performance among the 216 models were statistically significant(P＜0.01).Under the ensemble learning algorithm,adherence to inhaler use(38.087 4%),inhaler satisfaction(25.680 1%),literacy(24.031 3%),number of inhalers(5.482 3%),age(4.204 5%)and number of acute exacerbations in the past year(2.184 7%)contributed most to the predictive model.The model exhibited superior performance,with an AUC of 0.869 3,an accuracy of 83.87%,a precision of 86.96%,a recall of 74.07%,and an F1 score of 0.8.Conclusion This study has developed a predictive model for poor inhalation risk in COPD inhaler therapy patients using machine learning algorithms,which exhibits strong predictive capabilities and holds potential clinical application value.

Objective To screen biomarkers for forensic identification of acute myocardial infarction (AMI) by non-targeted metabolomic studies on changes of urine metabolites in rats with AMI.Methods The rat models of the sham surgery group,AMI group and hyperlipidemia+acute myocardial infarction (HAMI) group were established.Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the changes of urine metabolic spectrometry in AMI rats.Principal compo-nent analysis,partial least squares-discriminant analysis,and orthogonal partial least squares-discriminant analysis were used to screen differential metabolites.The MetaboAnalyst database was used to analyze the metabolic pathway enrichment and access the predictive ability of differential metabolites.Results A total of 40 and 61 differential metabolites associated with AMI and HAMI were screened,respec-tively.Among them,22 metabolites were common in both rat models.These small metabolites were mainly concentrated in the niacin and nicotinamide metabolic pathways.Within the 95% confidence in-terval,the area under the curve (AUC) values of receiver operator characteristic curve for N8-acetyl-spermidine,3-methylhistamine,and thymine were greater than 0.95.Conclusion N8-acetylspermidine,3-methylhistamine,and thymine can be used as potential biomarkers for AMI diagnosis,and abnormal metabolism in niacin and nicotinamide may be the main causes of AMI.This study can provide reference for the mechanism and causes of AMI identification.

Objective:To automatically classify hypertensive heart disease (HHD) and hypertrophic cardiomyopathy (HCM) based on mul-titask learning algorithm using native T1 mapping images.Methods:A total of 203 patients admitted to Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University from January 2017 to December 2021 were enrolled, including 53 patients with HHD, 121 patients with HCM, and 29 patients with normal control (NC). Native T1 mapping images of all enrolled patients were acquired using MRI and processed by a multi-task learning algorithm. The classification performance of each model was validated using ten-fold crossover, confusion matrix, and receiver operator characteristic (ROC) curves. The Resnet 50 model based on the original images was established as a control.Results:The ten-fold crossover validation results showed that the MTL-1 024, MTL-64, and MTL-all models showed better performance in terms of area under the curve (AUC), accuracy, sensitivity, and specificity compared to the Resnet 50 model. In the classification task, the MTL-64 model showed the best performance in terms of AUC (0.942 1), while the MTL-all model reached the highest value in terms of accuracy (0.852 2). In the segmentation task, the MTL-64 model achieved the best results with the Dice coefficient (0.879 7). The confusion matrix plot showed that the MTL model outperforms the Resnet 50 model based on the original image in terms of overall performance. The ROC graphs of all MTL models were significantly higher than the original image input Resnet 50 model.Conclusions:Multi-task learning-based native T1 mapping images are effective for automatic classification of HHD and HCM.