Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

OBJECTIVE: To explore the differences in clinical efficacy between enhanced workflows and express workflows in robotic-assisted total hip arthroplasty(THA). METHODS: A retrospective analysis was conducted on 46 patients who underwent robotic-assisted THA between November 2020 and May 2021. They were divided into the enhanced workflows group and the express workflows group based on the surgical methods. There were 20 patients in the enhanced workflows group, including 11 males and 9 females;aged from 51 to 78 years old with an average of (67.30±7.52) years old. The BMI ranged from 18.24 to 24.03 kg·m^-2 with an average of(23.80±3.01) kg·m^-2. There were 26 patients in the express workflows group, including 12 males and 14 females;aged from 57 to 84 years old with a mean age of (67.58±7.29) years old, and their BMI ranged from 19.72 to 30.08 kg·m^-2 with an average of (24.41 ±2.92) kg·m^-2. The operation time, hospital stay, and perioperative complications of the patients were recorded. The postoperative acetabular prosthesis anteversion angle, abduction angle, limb length, and offset distance data were measured. The Harris hip score at the latest follow-up was recorded. RESULTS: All patients completed the surgery as planned and were followed up, with the follow-up period ranging from 47 to 54 months with a mean of (49.78±1.85) months and the length of hospital stay ranging from 2 to 11 days with an average of (6.57±1.82 ) days. The operation time of enhanced workflows group was (93.41±16.41) minutes, which was longer than that of the express workflow groups (75.19±18.36) minutes, and the difference was statistically significant (P<0.05). In enhanced workflows group, the postoperative acetabular anteversion angle was (19.20±4.46)°, the limb length discrepancy was (-1.55±9.13) mm, and changes of the offset was (-5.15±6.77) mm. The corresponding values in express workflows group were (20.46±3.29)°, (2.19±4.39) mm, and (-2.39±4.34) mm, respectively. There was no statistically significant difference in these indicators between the two groups(P>0.05). One patient in the enhanced workflows group developed deep venous thrombosis after surgery. No cases of dislocation or periprosthetic infection. At the latest follow-up, all patients had well-positioned prostheses without loosening. Harris hip score was (90.50±1.67) points in enhanced workflows group and (90.73±2.36) points in the express workflows group, with no statistically significant difference between the two groups (P>0.05). CONCLUSION The clinical efficacy of robot assisted total hip arthroplasty technology is satisfactory. The enhanced workflows will increase the surgical time. For patients with normal anatomical hip joint disease, this study did not find significant advantages in joint stability and functional scoring for the enhanced workflows.
Humans ; Arthroplasty, Replacement, Hip/methods* ; Male ; Female ; Aged ; Middle Aged ; Robotic Surgical Procedures/methods* ; Retrospective Studies ; Aged, 80 and over ; Workflow ; Treatment Outcome

Bronchial asthma (asthma) is a complex inflammatory airway disease affecting approximately 100 million children worldwide, imposing a heavy burden on society and families. Studies have shown that the gut microbiota plays a significant role in the occurrence and development of childhood asthma. This paper reviews the research progress on the relationship between gut microbiota and childhood asthma. By elucidating the composition, function, and relationship with the host of gut microbiota, the impact of changes in its composition and function on the development of asthma is revealed. Furthermore, the potential value and application prospects of modulating gut microbiota as a new strategy for asthma treatment are discussed, providing a theoretical reference for in-depth research on the relationship between gut microbiota and the onset of childhood asthma and the development of new therapeutic approaches.
Humans ; Asthma/etiology* ; Gastrointestinal Microbiome/physiology* ; Child

Hereditary hemochromatosis is a rare autosomal genetic disorder that can cause multi-organ dysfunction in the liver,pancreas,spleen,heart and pituitary gland,with diverse clinical manifestations,make the diagnosis difficult.In recent years,with the deepening of clinical understanding and the development of genetic diagnosis tools,the diagnostic rate of this disease has increased significantly.In this paper,we report a case of hereditary hemochromatosis type 3 involving multiple organs and complicated by severe heart failure,aiming to improve the clinicians'understanding of this disease and reduce the leakage and misdiagnosis.

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 construct machine learning models that can be used to predict AUC fold change(FC)using a database of existing pharmacokinetic(PK)and drug-drug interaction(DDI)information,which can be used to explore the possibility of predicting existing drug interactions and to provide certain rational recommendations for clinical drug use.Methods PK data of DDIs and AUC fold change data were extracted from FDA-approved drug labels.Peptide and pharmacodynamic(PD)information related to drug interactions were retrieved through DrugBank,and PPDT identification of relevant peptide IDs was performed using Protein Resource(UniProt),and a matrix normalization code was used to generate multidimensional vector data that were easy to analysis.The effect of PPDT on the AUC,and the resulting multiplicity change was used as the dependent variable for machine learning model construction.The model with the smallest root mean square error(RMES)value was used for model construction to train a bagged decision tree(Bagged)prediction model.The models were tested using the trained models for some of the drug tests.The models were evaluated by reviewing the available literature findings on detection of drug interaction pairs and analyzing and comparing the predicted values.Results A total of 16 pairs of model drug pairs were tested for the effects of 16 drugs on tacrolimus,and it was found that the accuracy of the prediction of the presence or absence of drug interactions was 81.25％;the prediction results were classified according to the FDA standard classification of the strong and weak for the strength of drug interactions,and the results showed that the prediction of the strength of drug interactions,with a large deviation from the larger prediction was less.Conclusion The evaluation of the model to predict the presence or absence of drug interactions was general;however,after classifying the strengths and weaknesses of drug interactions,the prediction of drug interactions was better,and the prediction results indicated that the model prediction performance has a certain reference value for potential DDI assessment before clinical trials.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Liposome was used as carrier to carry triptolide and ginsenoside Rg3 in the treatment of pancreatic cancer tumor mice. The effects of liposome on the levels of CD4⁺ and CD8⁺ microenvironmental immune factors of pancreatic cancer tumor were investigated, and the tumor inhibitory effect and safety were evaluated. In this study, Pan02 cells were used to construct a tumor-bearing C57BL/6 mouse model. After 14 days of treatment, the changes in tumor volume and body weight of tumor-bearing mice were observed. The results showed that the high and low doses of liposome had significant therapeutic effect on tumor volume in the model group (P < 0.01), and the tumor inhibition rate of high doses of liposome was significantly increased compared with triptolide group (P < 0.05). Immunohistochemistry showed that compared with the model group, the tumor inhibition rate of liposome was significantly increased. The high-dose liposome group can up-regulate the ratio of immune factor CD4⁺/CD8⁺, inhibit the expression of tumor proliferation factor and promote the expression of tumor apoptosis factor, and has a high safety after pathological hematoxylin and eosin staining of liver, spleen, lung and kidney and serum factor detection. Animal welfare and experimental procedures are in accordance with the regulations of the Experimental Animal Ethics Committee of Henan University of Chinese Medicine (approval No.: DWLL202103173). This study provides a new idea for the exploration of immunotherapy for pancreatic cancer.

Extracting extracts of secondary metabolites from the karst cave fungus Metarhizium anisopliae NHC-M3-2 from the Yilingyan Scenic Area in Guangxi. Ten compounds were isolated and purified from fungal secondary metabolites using thin-layer chromatography and high-performance liquid chromatography. 7-Hydroxy-3-hydroxypropyl-5,6-dimethylisochrome-1-one (1) and 7-hydroxy-3,5,6-trimethyl-isochromen-1-one (2) were new isocoumarin compounds, N-acetyl phenylalanine (3), chaetosumin J (4), 2-one-13-hydroxy-3,5,8,7(11)-eudesmatetraen-12,8-olide (5), 1H-indole-3-carboxaldehyde (6), irpexolaceus B (7), irlactin L (8), cytochalasin K (9), and helvolic acid (10), a total of 8 known compounds. The structure of the compound was determined using methods such as NMR and mass spectrometry. The tumor cytotoxicity of the compound was evaluated using the CCK-8 method. The results showed that the IC₅₀ of compound 2 on HepG2 cells was 29.83 µmol·L^-1, and compound 9 on HCT116 cells was 27.44 µmol·L^-1.

Constipation is a prevalent ailment which might significantly impact the quality of people's life and rise some associated deseases risks. In this study, a chronic constipation mouse model was established using loperamide hydrochloride. Mice were gavaged an Angelica sinensis Cistanche Fiber Compound, comprised of Dang Gui [Angelica sinensis (Oliv.) Diels], Rou Cong Rong (Cistanche deserticola Y.C.Ma), wheat fiber, and low-molecular-weight xylan at high dosage (3.6 g·kg^-1, 30 times the recommended human dose) and low dosage (0.6 g·kg^-1, 5 times the recommended human dose) for 14 days. The study assessed the therapeutic efficacy of the compound by observing fecal morphology, measuring water content, and conducting small intestine motility experiments. Furthermore, enzyme-linked immunosorbent assays (ELISA) were conducted to evaluate the serum levels of gastrointestinal hormones including motilin (MTL), gastrin (GAS), the inflammatory factors interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α). Histopathological examination with H&E staining was employed to evaluate colonic tissue damage. Additionally, Western blot and immunohistochemistry experiments were conducted to examine the expression levels of aquaporin-3 (AQP3) and c-Kit in the colon. The results indicated that the Angelica sinensis Cistanche Fiber Compound could improve fecal morphology, increase fecal water content, enhance small intestinal transit rates in mice. Additionally, there was a significant elevation in the serum levels of gastrointestinal hormones and a notable reduction in the levels of inflammatory factors. The improvement in colonic histopathological damage was accompanied by a marked decrease in the expression of the colonic water channel protein AQP3 and a significant increase in c-Kit expression. These results collectively suggested the presence of a dose-response relationship. These findings indicate that the Angelica sinensis Cistanche Fiber Compound effectively alleviates constipation in mice. Its action is associated with the regulation of colonic water channel protein AQP3 and c-Kit expression, along with the modulation of serum inflammatory factors and gastrointestinal hormones. This experiment was approved by the Animal Experiment Ethics Committee of Jinan University.