OBJECTIVE: To explore the feasibility of establishing a temporary trauma team led by trauma experts in primary hospitals for disaster medical rescue. METHODS: In the coal mine flooding accident in Xiaoyi City, Shanxi Province on December 15, 2021, according to the local emergency plan and the characteristics of the accident, the trauma experts trained the medical staff from the local primary hospital on advanced trauma life support (ATLS) and damage control surgery (DCS) in the short time interval between the occurrence of the mine disaster and the admission of medical staff to the disaster scene. A temporary trauma team composed of trauma experts, ATLS team, and DCS team was formed to provide early diagnosis and treatment for survivors before and in the hospital. RESULTS: The miners were found on the 36th hour of the disaster. All 22 miners were male, and 2 died underground. Another 20 people were rescued 39－43 hours after the disaster, with a median age of 48 years (34-57 years). All the survivors suffered from hypothermia, dehydration, maceration of feet and other injuries. There were 18 cases of acute inhalation tracheobronchitis, 14 cases of electrolyte acid-base disturbance, 6 cases of trunk contusion, 1 case of psoas major hematoma, and 1 case of lower extremity hematoma. Deep vein thrombosis was in 4 cases. The ATLS team focused on injury assessment, rewarming and rehydration within 50－60 minutes before admission, and completed auxiliary examinations within 2 hours after admission to clarify the diagnosis. The DCS team evaluated 6 patients with mechanical blunt trunk injury and excluded the indication of emergency surgery. The trauma experts conducted the whole process of supervision and quality control of disaster rescue. The positive rate of capillary refill test in the all survivors at the third hour of admission was significantly lower than that immediately after being rescued (75.0% vs. 15.0%, P=0.000 3), and they were discharged 4－7 days after admission. CONCLUSION Under the leadership of trauma experts and relying on the medical staff of primary hospitals, it is feasible to establish and train a temporary trauma team with ATLS and DCS functions to participate in the medical rescue of disasters, which is in line with the current national conditions of China.
Humans ; Adult ; Middle Aged ; Male ; Rescue Work/organization & administration* ; China ; Disasters ; Patient Care Team/organization & administration* ; Wounds and Injuries/therapy* ; Advanced Trauma Life Support Care/organization & administration* ; Disaster Planning/organization & administration* ; Emergency Medical Services/organization & administration*

Cancer stem cells (CSCs) are widely acknowledged as primary mediators to the initiation and progression of tumors. The association between microbial infection and cancer stemness has garnered considerable scholarly interest in recent years. Porphyromonas gingivalis (P. gingivalis) is increasingly considered to be closely related to the development of oral squamous cell carcinoma (OSCC). Nevertheless, the role of P. gingivalis in the stemness of OSCC cells remains uncertain. Herein, we showed that P. gingivalis was positively correlated with CSC markers expression in human OSCC specimens, promoted the stemness and tumorigenicity of OSCC cells, and enhanced tumor formation in nude mice. Mechanistically, P. gingivalis increased lipid synthesis in OSCC cells by upregulating the expression of stearoyl-CoA desaturase 1 (SCD1) expression, a key enzyme involved in lipid metabolism, which ultimately resulted in enhanced acquisition of stemness. Moreover, SCD1 suppression attenuated P. gingivalis-induced stemness of OSCC cells, including CSCs markers expression, sphere formation ability, chemoresistance, and tumor growth, in OSCC cells both in vitro and in vivo. Additionally, upregulation of SCD1 in P. gingivalis-infected OSCC cells was associated with the expression of KLF5, and that was modulated by P. gingivalis-activated NOD1 signaling. Taken together, these findings highlight the importance of SCD1-dependent lipid synthesis in P. gingivalis-induced stemness acquisition in OSCC cells, suggest that the NOD1/KLF5 axis may play a key role in regulating SCD1 expression and provide a molecular basis for targeting SCD1 as a new option for attenuating OSCC cells stemness.
Porphyromonas gingivalis/pathogenicity* ; Stearoyl-CoA Desaturase/metabolism* ; Humans ; Carcinoma, Squamous Cell/pathology* ; Mouth Neoplasms/metabolism* ; Animals ; Neoplastic Stem Cells/microbiology* ; Mice, Nude ; Mice ; Nod1 Signaling Adaptor Protein/metabolism* ; Kruppel-Like Transcription Factors/metabolism* ; Cell Line, Tumor

BACKGROUND:The extracellular matrix is a complex network structure,which not only builds physical support for tissue cells,but also plays an important regulatory role in cell survival,proliferation,and death.Abnormal changes in the biochemical and biomechanical properties of the extracellular matrix can significantly affect the proliferation,migration,immune evasion,and treatment resistance of tumor cells.Stiffness is an important mechanical property of the extracellular matrix,and abnormalities in matrix stiffness are closely related to tumor progression.OBJECTIVE:By reviewing the mechanism of extracellular matrix sclerosis,the impact of high stiffness matrix on tumor progression,and the latest research progress in the treatment of cancer based on reducing matrix stiffness,to deeply understand the mechanical properties of the extracellular matrix,improve the understanding of the complex mechanism of tumor progression,and provide new ideas and directions for tumor treatment.METHODS:"Extracellular matrix function,extracellular matrix stiffness,collagen deposition cross-linking,extracellular matrix stiffness therapy,immunotherapy"were used as the search terms in Chinese and English.Relevant literature published from January 2016 to June 2024 was searched in CNKI,PubMed,and WanFang databases,and 80 articles were finally included for review.RESULTS AND CONCLUSION:(1)Deposition and excessive cross-linking of collagen and elastin in the extracellular matrix leads to matrix remodeling,which in turn increases matrix stiffness.This sclerosis activates pro-cancer signaling pathways such as cyclin-D1,Rho/ROCK,p-PXN-Rac1-YAP,and STAT3/p-STAT3,promotes malignant behaviors such as cancer cell proliferation,metastasis,tumor microangiogenesis and immune escape,and accelerates tumor progression.(2)Reducing the deposition and cross-linking of matrix proteins can reduce matrix stiffness,which cannot only inhibit the activation of multiple cancer-promoting signaling pathways,but also enhance the penetration and delivery of drugs at tumor sites,which is a new strategy for cancer treatment.(3)At present,drugs based on matrix degradation to reduce tumor stiffness are under development,and a few drugs have entered the clinical trial stage,which are expected to provide a new powerful weapon for tumor treatment.

Neuroimaging techniques are tools used to investigate and monitor the activity of the nervous system.This study reviews studies that have attempted to quantify athletes'brain using neuroimaging techniques,and summarizes the specific changes in athletes'brain as evidenced by structural magnetic resonance imaging,functional magnetic resonance imaging,functional near-infrared spectroscopy,transcranial magnetic stimulation and electroencephalography.Open-skill sports have been found to increase the brain volume and resting-state functional connectivity related to athletes'executive control,somatosensory processing,vision,and balance coordination,whereas closed-skill sports may decrease the brain volume and resting-state functional connectivity related to athletes'episodic memory,emotional processing and executive functions.Brain regions associated with executive functions,body awareness,motor learning,and episodic memory exhibit stronger activation during tasks.Athletes demonstrate higher neural excitability and neural efficiency.The association between sports training and the brain should be explored through multimodal neuroimaging techniques,which will play a significant role in athlete selection,real-time status monitoring and long-term training supervision.

Objective:To investigate the risk of hospital death in patients with traumatic hemorrhagic shock combined with multiple organ dysfunction syndrome(MODS)predicted by discriminant analysis.Methods:This study was a single-center retrospective study. From January 2013 to May 2023, patients with traumatic hemorrhagic shock complicated with MODS admitted to Peking University People's Hospital were selected as the research objects. According to the in-hospital survival, the patients were divided into survival group (205 cases) and death group (29 cases). The general condition, injury assessment, laboratory indexes, complications and clinical scores of the two groups were compared. Wilks's Lambda stepwise discriminant analysis was used to establish a discriminant model for in-hospital death in patients with traumatic hemorrhagic shock combined with MODS. the Receiver operating characteristic curve (ROC) was drawn and the Area under the curve (AUC) was calculated. The cross-validation method was used to evaluate the accuracy of the prediction results of the established model.Results:There was a statistical difference between the survival group and the death group in terms of the main bleeding site (limbs), the time from injury to hospital admission, temperature, platelet count, prothrombin time, activated partial thrombin time, fibrinogen, albumin, serum creatinine, estimated glomerular filtration rate, uric acid, cardiac troponin I, procalcitonin, base excess, lactate to albumin ratio, glucose to albumin ratio, acute respiratory distress syndrome, acute kidney injury, acute myocardial injury, traumatic induced coagulopathy, ISS, APACHEⅡ score and SOFA scores. There are four indicators entering the final discrimination model: Prothrombin time, ISS score, estimated glomerular filtration rate, lactate to albumin ratio. The AUC for predicting the risk of death in patients with traumatic hemorrhagic shock combined with MODS was 0.791, and the 95% CI was 0.671 to 0.911. Conclusions:The established discriminant model is highly accurate in predicting the risk of hospital death in patients with traumatic hemorrhagic shock complicated with MODS. Prothrombin time, ISS score, estimated glomerular filtration rate and lactate to albumin ratio were associated with an increased risk of death from traumatic hemorrhagic shock with MODS.

Objective To investigate mortality risk factors and characterize pathogen distribution and antimicrobial resistance patterns in intensive care unit(ICU)patients with suspected infection following surgery.Methods A total of 65 hospitals in 16 provinces in China from July 1,2021,to December 31,2022.Clinical data were collected for surgical patients transferred to the ICU with suspected infection.Data included demographics[sex,age,underlying conditions(hypertension,diabetes,cardiovascular/cerebrovascular disease,hematologic disease)],surgical site,infection site,microbiological results with susceptibility testing,drug resistance and acute physiology and chronic health evaluationⅡ(APACHEⅡ)scores and the length of hospital stays.Patients were stratified by prognosis into death group and survial group,by drug resistance status into resistant and non-resistant groups.Univariate and multivariate Logistic regression identified risk factors for mortality and antimicrobial resistance.Draw the receiver operator characteristic curve(ROC curve)to evaluate the predictive value of each risk factor for patient prognosis and drug resistance occurrence.Results A total of 677 patients with suspected postoperative infection in the ICU were enrolled.There were 96 deaths and 591 survivors.① Analysis of risk factors affecting prognosis:univariate analysis showed that compared with the survival group,the patients in the had a higher APACHEⅡscore,the proportion of patients with previous cerebrovascular disease,surgery sites in the abdomen,chest,brain,pelvis,limbs,other areas,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,Gram-positive bacterial infection(Candida),fungal infection,multi-drug resistant bacterial infection was higher,and the length of hospital stay was shorter(all P<0.05).Multivariate Logistic regression analysis identified higher APACHEⅡscore[odds ratio(OR)=1.15,95%confidence interval(95%CI)was 1.11-1.20],pulmonary infection(OR=4.07,95%CI was 2.05-8.11),bloodstream infection(OR=2.61,95%CI was 1.52-4.51),and urinary tract infection(OR=2.20,95%CI was 1.01-4.42)were independent risk factors for prognosis(all P<0.05).The ROC curve analysis showed that the death risk prediction model established based on the above independent risk factors had certain predictive value for the prognosis of ICU postoperative patients with suspected infection,area under the curve(AUC)=0.820,95%CI was 0.770-0.860,P<0.05.②Regarding antimicrobial resistance:250 patients developed resistance and 427 did not.Univariate analysis showed compared with the non-resistant group,the APACHEⅡscore,the proportion of patients with cerebrovascular diseases,hematological diseases,surgeries at chest,brain,limbs,other sites,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,intracranial infection,Gram-negative bacillus infection,and Gram-positive cocci infection(Staphylococcus epidermidis,Staphylococcus aureus,Enterococcus faecalis),and the mortality rate in the resistant group were significantly higher,the proportion of patients with surgeries at abdominal cavity,pelvic cavity and abdominal cavity infection were significantly lower,and the length of hospital stay was significantly longer(all P<0.05).Multivariate Logistic regression analysis bloodstream infection(OR=4.00,95%CI was 2.22-7.19),urinary tract infection(OR=3.25,95%CI was 1.47-7.17),Klebsiella pneumoniae infection(OR=2.23,95%CI was 11.22-44.02),Acinetobacter baumannii infection(OR=48.12,95%CI was 20.10-115.17),Pseudomonas aeruginosa infection(OR=34.06,95%CI was 13.00-89.25),Escherichia coli infection(OR=24.97,95%CI was 10.55-59.13),Stenotrophomonas maltophilia infection(OR=19.04,95%CI was 3.30-109.96),and Staphylococcus aureus infection(OR=13.48,95%CI was 4.57-39.78)were independent risk factors for resistance(all P<0.01).The ROC curve analysis showed that the predictive model for drug resistance established based on the above independent risk factors had certain predictive value for drug resistance in adult patients with suspected infections after surgery in the ICU.The AUC=0.920,95%CI was 0.890-0.940,P<0.05.Conclusion Higher APACHEⅡscores and the presence of pulmonary,bloodstream,or urinary tract infections were associated with increased mortality in ICU patients with suspected postoperative infection.Patients with bloodstream or urinary tract infections,or infections caused by Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,Escherichia coli,Stenotrophomonas maltophilia,or Staphylococcus aureus,had significantly higher odds of developing antimicrobial resistance.

BACKGROUND:The extracellular matrix is a complex network structure,which not only builds physical support for tissue cells,but also plays an important regulatory role in cell survival,proliferation,and death.Abnormal changes in the biochemical and biomechanical properties of the extracellular matrix can significantly affect the proliferation,migration,immune evasion,and treatment resistance of tumor cells.Stiffness is an important mechanical property of the extracellular matrix,and abnormalities in matrix stiffness are closely related to tumor progression.OBJECTIVE:By reviewing the mechanism of extracellular matrix sclerosis,the impact of high stiffness matrix on tumor progression,and the latest research progress in the treatment of cancer based on reducing matrix stiffness,to deeply understand the mechanical properties of the extracellular matrix,improve the understanding of the complex mechanism of tumor progression,and provide new ideas and directions for tumor treatment.METHODS:"Extracellular matrix function,extracellular matrix stiffness,collagen deposition cross-linking,extracellular matrix stiffness therapy,immunotherapy"were used as the search terms in Chinese and English.Relevant literature published from January 2016 to June 2024 was searched in CNKI,PubMed,and WanFang databases,and 80 articles were finally included for review.RESULTS AND CONCLUSION:(1)Deposition and excessive cross-linking of collagen and elastin in the extracellular matrix leads to matrix remodeling,which in turn increases matrix stiffness.This sclerosis activates pro-cancer signaling pathways such as cyclin-D1,Rho/ROCK,p-PXN-Rac1-YAP,and STAT3/p-STAT3,promotes malignant behaviors such as cancer cell proliferation,metastasis,tumor microangiogenesis and immune escape,and accelerates tumor progression.(2)Reducing the deposition and cross-linking of matrix proteins can reduce matrix stiffness,which cannot only inhibit the activation of multiple cancer-promoting signaling pathways,but also enhance the penetration and delivery of drugs at tumor sites,which is a new strategy for cancer treatment.(3)At present,drugs based on matrix degradation to reduce tumor stiffness are under development,and a few drugs have entered the clinical trial stage,which are expected to provide a new powerful weapon for tumor treatment.

Objective To investigate mortality risk factors and characterize pathogen distribution and antimicrobial resistance patterns in intensive care unit(ICU)patients with suspected infection following surgery.Methods A total of 65 hospitals in 16 provinces in China from July 1,2021,to December 31,2022.Clinical data were collected for surgical patients transferred to the ICU with suspected infection.Data included demographics[sex,age,underlying conditions(hypertension,diabetes,cardiovascular/cerebrovascular disease,hematologic disease)],surgical site,infection site,microbiological results with susceptibility testing,drug resistance and acute physiology and chronic health evaluationⅡ(APACHEⅡ)scores and the length of hospital stays.Patients were stratified by prognosis into death group and survial group,by drug resistance status into resistant and non-resistant groups.Univariate and multivariate Logistic regression identified risk factors for mortality and antimicrobial resistance.Draw the receiver operator characteristic curve(ROC curve)to evaluate the predictive value of each risk factor for patient prognosis and drug resistance occurrence.Results A total of 677 patients with suspected postoperative infection in the ICU were enrolled.There were 96 deaths and 591 survivors.① Analysis of risk factors affecting prognosis:univariate analysis showed that compared with the survival group,the patients in the had a higher APACHEⅡscore,the proportion of patients with previous cerebrovascular disease,surgery sites in the abdomen,chest,brain,pelvis,limbs,other areas,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,Gram-positive bacterial infection(Candida),fungal infection,multi-drug resistant bacterial infection was higher,and the length of hospital stay was shorter(all P<0.05).Multivariate Logistic regression analysis identified higher APACHEⅡscore[odds ratio(OR)=1.15,95%confidence interval(95%CI)was 1.11-1.20],pulmonary infection(OR=4.07,95%CI was 2.05-8.11),bloodstream infection(OR=2.61,95%CI was 1.52-4.51),and urinary tract infection(OR=2.20,95%CI was 1.01-4.42)were independent risk factors for prognosis(all P<0.05).The ROC curve analysis showed that the death risk prediction model established based on the above independent risk factors had certain predictive value for the prognosis of ICU postoperative patients with suspected infection,area under the curve(AUC)=0.820,95%CI was 0.770-0.860,P<0.05.②Regarding antimicrobial resistance:250 patients developed resistance and 427 did not.Univariate analysis showed compared with the non-resistant group,the APACHEⅡscore,the proportion of patients with cerebrovascular diseases,hematological diseases,surgeries at chest,brain,limbs,other sites,as well as those with pulmonary infection,bloodstream infection,urinary tract infection,intracranial infection,Gram-negative bacillus infection,and Gram-positive cocci infection(Staphylococcus epidermidis,Staphylococcus aureus,Enterococcus faecalis),and the mortality rate in the resistant group were significantly higher,the proportion of patients with surgeries at abdominal cavity,pelvic cavity and abdominal cavity infection were significantly lower,and the length of hospital stay was significantly longer(all P<0.05).Multivariate Logistic regression analysis bloodstream infection(OR=4.00,95%CI was 2.22-7.19),urinary tract infection(OR=3.25,95%CI was 1.47-7.17),Klebsiella pneumoniae infection(OR=2.23,95%CI was 11.22-44.02),Acinetobacter baumannii infection(OR=48.12,95%CI was 20.10-115.17),Pseudomonas aeruginosa infection(OR=34.06,95%CI was 13.00-89.25),Escherichia coli infection(OR=24.97,95%CI was 10.55-59.13),Stenotrophomonas maltophilia infection(OR=19.04,95%CI was 3.30-109.96),and Staphylococcus aureus infection(OR=13.48,95%CI was 4.57-39.78)were independent risk factors for resistance(all P<0.01).The ROC curve analysis showed that the predictive model for drug resistance established based on the above independent risk factors had certain predictive value for drug resistance in adult patients with suspected infections after surgery in the ICU.The AUC=0.920,95%CI was 0.890-0.940,P<0.05.Conclusion Higher APACHEⅡscores and the presence of pulmonary,bloodstream,or urinary tract infections were associated with increased mortality in ICU patients with suspected postoperative infection.Patients with bloodstream or urinary tract infections,or infections caused by Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,Escherichia coli,Stenotrophomonas maltophilia,or Staphylococcus aureus,had significantly higher odds of developing antimicrobial resistance.

Objective:To investigate the risk factors of acute respiratory distress syndrome(ARDS)after traumatic hemorrhagic shock.Methods:This was a retrospective cohort study of 314 patients with traumatic hemorrhagic shock at Trauma Medicine Center,Peking University People's Hospital from De-cember 2012 to August 2021,including 152 male patients and 162 female patients,with a median age of 63.00(49.75-82.00)years.The demographic data,past medical history,injury assessment,vital signs,laboratory examination and other indicators of these patients during hospitalization were recorded.These patients were divided into two groups,ARDS group(n=89)and non-ARDS group(n=225)ac-cording to whether there was ARDS within 7 d of admission.Risk factors for ARDS were identified using Logistic regression.The C-statistic expressed as a percentage[area under curve(AUC)of the receiver operating characteristic(ROC)curve]was used to assess the discrimination of the model.Results:The incidence of ARDS after traumatic hemorrhagic shock was 28.34％.Finally,Logistic regression model showed that the independent risk factors of ARDS after traumatic hemorrhagic shock included male,histo-ry of coronary heart disease,high acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score,road traffic accident and elevated troponin Ⅰ.The OR and 95％confidence intervals(CI)were 4.01(95％CI:1.75-9.20),5.22(95％CI:1.29-21.08),1.07(95％CI:1.02-1.57),2.53(95％CI:1.21-5.28),and 1.26(95％CI:1.02-1.57),respectively;the P values were 0.001,0.020,0.009,0.014,and 0.034,respectively.The ROC curve was used to analyze the value of each risk factor in predicting ARDS.It was found that the AUC for predicting ARDS after traumatic hemor-rhagic shock was 0.59(95％CI:0.51-0.68)formale,0.55(95％CI:0.46-0.64)for history of coronary heart disease,0.65(95％CI:0.57-0.73)for APACHE Ⅱ score,0.58(95％CI:0.50-0.67)for road traffic accident,and 0.73(95％CI:0.66-0.80)for elevated troponin Ⅰ,with an overall predictive value of 0.81(95％CI:0.74-0.88).Conclusion:The incidence of ARDS in pa-tients with traumatic hemorrhagic shock is high,and male,history of coronary heart disease,high APACHE Ⅱ score,road traffic accident and elevated troponin Ⅰ are independent risk factors for ARDS after traumatic hemorrhagic shock.Timely monitoring these indicators is conducive to early detection and treatment of ARDS after traumatic hemorrhagic shock.

Objective To explore the current status of posttraumatic growth (PTG) among nurses at psychiatric department and analyze its latent profiles and population characteristics. Methods A total of 357 nurses from psychiatric departments of five tertiary Grade A hospitals were selected as the research subjects using the convenience sampling method. The PTG and professional quality of life were studied using the Posttraumatic Growth Inventory and the Chinese version of the Compassion Fatigue Scale. Results The PTG score of the nurses was (56.6±23.2). The scores of compassion satisfaction, burnout, and secondary traumatic stress among nurses were (32.6±7.2), (26.9±5.9), and (26.0±5.4), respectively. The result of potential profile analysis showed that the nurses could be divided into three latent profiles based on PTG levels: low PTG group (34.4%), moderate PTG group (44.0%), and high PTG group (21.6%). The results of multinomial logistic regression analysis showed that the nurses who slept 7-8 hours per day were at higher risk of being in the high PTG group compared with those who slept more than eight hours per day (P<0.05). Psychiatric nurses who took regular exercise were at higher risk of being in the high PTG group compared with those who took irregular exercise (P<0.05). The nurses who had high job satisfaction scores were at higher risk of being in the high PTG group compared with those who had low job satisfaction scores (P<0.01). The nurses with higher compassion satisfaction scores increased the risk of being in the high PTG group compared with those with lower compassion satisfaction scores (P<0.01). The nurses with higher burnout scores increased the risk of being in the low PTG group compared with those with lower burnout scores (P<0.01). Conclusion The PTG characteristics of the nurses exhibit heterogeneity and can be categorized into three distinct profiles. Sleep duration, regular exercise, job satisfaction, compassion satisfaction, and burnout are influencing factors for the PTG latent profiles of nurses working at psychiatric department.