To investigate the prevalence and associated factors of fall risk among Chinese older adults, and to examine the roles of urban-rural differences, regional disparities, physical health status, and psychosocial factors in falls among this population, thereby providing evidence for tailored fall prevention strategies.

Based on the data from the 5^th National Physical Fitness Surveillance in China, this study aimed to explore the relationship between abnormal body weight and physical fitness levels in older adults.

Background and Aims:Early-onset extensive emphysematous pancreatitis(EP)is a rare but highly lethal subtype of infected pancreatic necrosis(IPN),characterized by abrupt onset and rapid deterioration.This study aimed to investigate its clinical characteristics,microbiological spectrum,treatment approaches,and outcomes to provide evidence for early identification and timely intervention.Methods:A retrospective analysis was performed on 305 IPN patients treated at Xiangya Hospital,Central South University,from January 2010 to October 2023.Eight patients who developed gas accumulation involving≥50%of pancreatic or peripancreatic necrosis within two weeks of onset were defined as early-onset extensive EP.Their clinical data were compared with those of ordinary IPN patients.Results:Early-onset extensive EP accounted for 2.6%of all IPN cases.The early-onset extensive EP group had significantly higher mortality and multiple organ failure rates compared with the ordinary IPN group(75.0%vs.24.6%and 75.0%vs.34.7%,respectively;both P<0.05).A total of 15 microbial isolates were identified from early-onset extensive EP patients,predominantly Klebsiella pneumoniae(62.5%)and Escherichia coli(37.5%).The infection rate of carbapenem-resistant Enterobacteriaceae(CRE)was markedly higher in the EP group than in the ordinary IPN group(75.0%vs.31.1%,P=0.015).Most patients were treated using a step-up approach based on percutaneous catheter drainage,with no significant difference in treatment strategy between the two groups(P=0.625).Conclusion:Early-onset extensive EP represents a rare and fulminant subtype of IPN with extremely poor outcomes.Klebsiella pneumoniae and CRE are the predominant pathogens.Early radiological evaluation and timely intervention are crucial for improving prognosis in these patients.

Airway management is a critical component of critical patient care.Although traditional methods of airway management are effective to some extent,they still face many challenges,such as difficult airways,delayed endotracheal intubation,endotracheal tube migration,unpredictable airway complications and failure to mechanical ventilation weaning.Artificial intelligence(AI),a technological tool with advanced algorithms,offers important innovations to improve the safety and efficiency of airway management with its multimodal data integration and real-time decision support capabilities.For example,AI can be used in areas such as real-time monitoring of patients′ vital signs,dynamic adjustment of ventilator parameters,monitoring and assessment of airway complications,and assisted robotic tracheal intubation.In addition,AI is able to build predictive models based on big data to help reduce the risk of injury in mechanically ventilated patients and assist clinicians in making timely decisions.This paper reviews the research progress of AI in airway management and discusses issues of privacy and security,ethics,model performance and interpretability that may be faced during the use of AI,and looks forward to a more active role for AI in airway management in future.

Background and Aims:Early-onset extensive emphysematous pancreatitis(EP)is a rare but highly lethal subtype of infected pancreatic necrosis(IPN),characterized by abrupt onset and rapid deterioration.This study aimed to investigate its clinical characteristics,microbiological spectrum,treatment approaches,and outcomes to provide evidence for early identification and timely intervention.Methods:A retrospective analysis was performed on 305 IPN patients treated at Xiangya Hospital,Central South University,from January 2010 to October 2023.Eight patients who developed gas accumulation involving≥50%of pancreatic or peripancreatic necrosis within two weeks of onset were defined as early-onset extensive EP.Their clinical data were compared with those of ordinary IPN patients.Results:Early-onset extensive EP accounted for 2.6%of all IPN cases.The early-onset extensive EP group had significantly higher mortality and multiple organ failure rates compared with the ordinary IPN group(75.0%vs.24.6%and 75.0%vs.34.7%,respectively;both P<0.05).A total of 15 microbial isolates were identified from early-onset extensive EP patients,predominantly Klebsiella pneumoniae(62.5%)and Escherichia coli(37.5%).The infection rate of carbapenem-resistant Enterobacteriaceae(CRE)was markedly higher in the EP group than in the ordinary IPN group(75.0%vs.31.1%,P=0.015).Most patients were treated using a step-up approach based on percutaneous catheter drainage,with no significant difference in treatment strategy between the two groups(P=0.625).Conclusion:Early-onset extensive EP represents a rare and fulminant subtype of IPN with extremely poor outcomes.Klebsiella pneumoniae and CRE are the predominant pathogens.Early radiological evaluation and timely intervention are crucial for improving prognosis in these patients.

Airway management is a critical component of critical patient care.Although traditional methods of airway management are effective to some extent,they still face many challenges,such as difficult airways,delayed endotracheal intubation,endotracheal tube migration,unpredictable airway complications and failure to mechanical ventilation weaning.Artificial intelligence(AI),a technological tool with advanced algorithms,offers important innovations to improve the safety and efficiency of airway management with its multimodal data integration and real-time decision support capabilities.For example,AI can be used in areas such as real-time monitoring of patients′ vital signs,dynamic adjustment of ventilator parameters,monitoring and assessment of airway complications,and assisted robotic tracheal intubation.In addition,AI is able to build predictive models based on big data to help reduce the risk of injury in mechanically ventilated patients and assist clinicians in making timely decisions.This paper reviews the research progress of AI in airway management and discusses issues of privacy and security,ethics,model performance and interpretability that may be faced during the use of AI,and looks forward to a more active role for AI in airway management in future.

Objective:To investigate the application value of metagenomic next-genera-tion sequencing (mNGS) in pathogenic diagnosis of suspected infected severe acute pancreatitis (SAP).Methods:The prospective study was conducted. The clinical data of 25 patients with suspected infected SAP who were admitted to the Xiangya Hospital of Central South University from May to September 2023 were collected. Upper limb venous blood samples of all the patients were collected for both of mNGS and routine pathogen microbial culture. Observation indicators: (1) grouping situations of the enrolled patients; (2) comparison of the diagnostic efficiency of mNGS and routine pathogen microbial culture; (3) results of peripheral blood pathogen microbial testing and peri-pancreatic effusion microbial culture; (4) testing time and cost. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M( Q1, Q3). Count data were expressed as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. Results:(1) Grouping situations of the enrolled patients. A total of 25 patients were selected for eligibility. There were 18 males and 7 females, aged 48(40,59)years. The duration of hospital stay of 25 patients was 30(20,50)days. The etiologies of 25 patients included 14 cases of hyperlipidemic pancreatitis, 8 cases of biliary pancreatitis, 1 case of alcohol-induced acute pancreatitis, and 2 cases of pancreatitis caused by other causes. Of the 25 patients, there were 17 cases with infected pancreatic necrosis (IPN) including 7 cases of death, and 8 cases with sterile pancreatic necrosis including no death. (2) Comparison of the diagnostic efficiency of mNGS and routine pathogen microbial culture. The positive rates of mNGS and routine pathogen microbial culture in diagnosis of suspected infected SAP were 72.0%(18/25) and 32.0%(8/25), respectively, showing a significant difference between them ( χ2=8.01, P<0.05). The sensitivity and negative predic-tive value of mNGS and routine pathogen microbial culture in diagnosis of IPN were 94.1%(16/17), 35.3%(6/17) and 85.7%(6/7), 35.3%(6/17), showing significant differences between them ( χ2=12.88, 5.04, P<0.05). The specificity and positive predictive value of mNGS and routine pathogen microbial culture in diagnosis of IPN were 75.0%(6/8), 75.0%(6/8) and 88.9%(16/18), 75.0%(6/8), showing no significant difference between them ( χ2=0, 0.82, P>0.05). (3) Results of peripheral blood pathogen microbial testing and peripancreatic effusion microbial culture. Of the 17 patients with IPN, 36 strains of pathogenic bacteria were detected by mNGS, and 6 strains were detected by routine pathogen microbial culture. There were 16 of 17 patients with IPN showing positive mNGS pathogenic testing, of which 13 cases were consistent with the pathogenic testing results of peri-pancreatic effusion microbial culture, showing a consistency rate of 76.5%(13/17). There were 6 pati-ents with IPN showing positive routine pathogen microbial culture, with a consistency rate of 35.3%(6/17) to peripancreatic effusion microbial culture. (4) Testing time and cost. Testing time of mNGS and routine pathogen microbial culture were (43±17)hours and (111±36)hours, showing a signifi-cant difference between them ( t=9.31, P<0.05). Testing cost of mNGS was (2 267±0)yuan/case, accoun-ting for 1.7% of the hospitalization expenses of (133 759±120 744)yuan/case. Testing cost of routine pathogen microbial culture was (240±0)yuan/case, accounting of 0.2% of the hospitalization expenses. Conclusion:mNGS has important value for early pathogenic diagnosis of suspected infected SAP, and has a high timeliness.

Background and Aims:Accurate early pathogen diagnosis is a breakthrough for improving the prognosis of infectious pancreatic necrosis(IPN)patients.However,there is currently a lack of efficient methods for early identification of IPN in clinical settings.This study was performed to assess the application value of next-generation sequencing technology based on metagenomic capture(MetaCAP)in the pathogen diagnosis of IPN. Methods:A prospective study was conducted on 29 patients suspected of having acute necrotizing pancreatitis at Xiangya Hospital of Central South University between January and July 2024.Blood samples were tested using MetaCAP and conventional pathogen culture.The results of peritoneal fluid pathogen culture were used as the gold standard to compare the diagnostic efficacy of the two methods. Results:Due to three cases lacking peritoneal fluid culture results,a total of 26 cases were included in the final analysis.The overall mortality rate was 23.1％(6/26).During hospitalization,9 cases(34.6％)were diagnosed with IPN.The sensitivity and negative predictive value of MetaCAP for diagnosing IPN were significantly higher than those of conventional pathogen culture(77.8％vs.11.1％,P=0.031;86.7％vs.65.2％,P=0.032),while the differences in specificity(76.5％vs.88.2％,P=0.689)and positive predictive value(63.6％vs.33.3％,P=0.347)between the two methods were not statistically significant.The average detection time for MetaCAP was 33(20-49)h,while microbial culture took 125(45-142)h,with a significant difference(P＜0.001).The average cost for blood MetaCAP testing was 2 500 yuan per case,but it accounted for only 1.19％of the average hospitalization cost. Conclusion:MetaCAP has significant value in the early pathogen diagnosis of IPN,with a shorter detection time,good testing efficacy,and health-economic value,demonstrating a promising clinical application prospect.

Objective To explore the antidepressant effects of acupuncture at Baihui and Zusanli acupoints on mice with chronic unpredictable mild stress(CUMS)-induced depressive-like behavior and its association with changes in gut microbiota.Methods Sixty mice were randomly divided into four groups:control group(Ctrl),control+acupuncture group(Ctrl+AP),CUMS group,and CUMS+acupuncture group(CUMS+AP).The CUMS and CUMS+AP groups underwent 6-week CUMS treatment.During the last three weeks of CUMS,mice in the Ctrl+AP and CUMS+AP groups received 20 minutes of acupuncture at Baihui and Zusanli acupoints daily.Sucrose preference test and tail suspension test were used to assess the depressive-like behavior in mice.After the behavioral tests,fecal samples were collected from the mice,and the gut microbiota composition was analyzed using 16S rRNA gene sequencing.Results Acupuncture alone had no effect on sucrose preference or tail suspension test results in mice(P＞0.05).CUMS induced depressive-like behavior in mice,as evidenced by decreased sucrose preference(P＜0.001)and increased immobility time in the tail suspension test(P=0.003).The CUMS+AP group showed increased sucrose preference(P=0.035)and decreased immobility time in the tail suspension test(P=0.045)compared to the CUMS group.Acupuncture and CUMS did not alter the richness of gut microbiota in mice(P＞0.05),but they caused significant changes in gut microbiota composition(P=0.002).CUMS increased the abundance of six bacterial genera,including Patulibacter,and decreased the abundance of 26 bacterial genera,including Faecalibacterium(P＜0.05).The CUMS+AP group showed increased abundance of 10 bacterial genera,including Faecalibacterium,and decreased abundance of four bacterial genera,including Patulibacter,compared to the CUMS group(P＜0.05).Each group of mice had specific gut microbiota.The CUMS group showed significant enrichment of gene functions related to retinol metabolism,ubiquitin system,N-glycan biosynthesis,steroid hormone biosynthesis,apoptosis,and thermogenesis compared to the control group(P＜0.05),while acupuncture reduced the enrichment of these gene functions in the CUMS+AP mice(P＜0.05).Conclusion Acupuncture at Baihui and Zusanli acupoints has antidepressant effects and can partially restore the depression-induced dysbiosis of gut microbiota.Acupuncture at Baihui and Zusanli acupoints may exert antidepressant effects by influencing gut microbiota composition and metabolism functions of retinol,ubiquitin,N-glycan,and steroids.

ObjectiveTo screen the differential markers by analyzing volatile components in Dalbergia odorifera and its counterfeits， in order to provide reference for authentication of D. odorifera. MethodThe volatile components in D. odorifera and its counterfeits were detected by headspace gas chromatography-mass spectrometry（HS-GC-MS）， and the GC conditions were heated by procedure（the initial temperature of the column was 50 ℃， the retention time was 1 min， and then the temperature was raised to 300 ℃ at 10 ℃ for 10 min）， the carrier gas was helium， and the flow rate was 1.0 mL·min^-1， the split ratio was 10∶1， and the injection volume was 1 mL. The MS conditions used electron bombardment ionization（EI） with the scanning range of m/z 35-550. The compound species were identified by database matching， the relative content of each component was calculated by the peak area normalization method， and principal component analysis（PCA）， orthogonal partial least squares-discrimination analysis（OPLS-DA） and cluster analysis were performed on the detection results by SIMCA 14.1 software， and the differential components of D. odorifera and its counterfeits were screened out according to the variable importance in the projection（VIP） value>2 and P<0.05. ResultA total of 26， 17， 8， 22， 24 and 7 volatile components were identified from D. odorifera， D. bariensis， D. latifolia， D. benthamii， D. pinnata and D. cochinchinensis， respectively. Among them， there were 11 unique volatile components of D. odorifera， 6 unique volatile components of D. bariensis， 3 unique volatile components of D. latifolia， 6 unique volatile components of D. benthamii， 8 unique volatile components of D. pinnata， 4 unique volatile components of D. cochinchinensis. The PCA results showed that， except for D. latifolia and D. cochinchinensis， which could not be clearly distinguished， D. odorifera and other counterfeits could be distributed in a certain area， respectively. The OPLS-DA results showed that D. odorifera and its five counterfeits were clustered into one group each， indicating significant differences in volatile components between D. odorifera and its counterfeits. Finally， a total of 31 differential markers of volatile components between D. odoriferae and its counterfeits were screened. ConclusionHS-GC-MS combined with SIMCA 14.1 software can systematically elucidate the volatile differential components between D. odorifera and its counterfeits， which is suitable for rapid identification of them.