ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To evaluate the precision of robot-assisted axis pedicle screw placement and to evaluate the factors influencing the accuracy of the placement.Methods:The medical records of 27 consecutive patients who underwent posterior internal fixation of the upper cervical spine for atlantoaxial instability with intraoperative robot-assisted axis pedicle screw placement from January 2017 to December 2020 at Beijing Jishuitan Hospital were retrospectively analyzed. T The cohort comprised 10 males and 17 females, aged 41.3±16.6 years (range 12-75 years), with a body mass index (BMI) of 23.0±2.9 kg/m 2 (range 18.9-30.0 kg/m 2). There were 16 cases of traumatic atlantoaxial instability and 11 cases of atlantoaxial instability caused by deformity. The accuracy of robot-assisted axis pedicle screw placement was evaluated by postoperative CT using Gertzbein-Robbins scale. Factors potentially affecting placement accuracy were initially identified via univariate analysis, with significant factors ( P<0.200) subsequently analyzed through multivariate modeling using generalized estimating equations. Results:A total of 49 axis pedicle screws were placed in 27 patients, with 35 (71.4%) in Gertzbein-Robbins scale grade A, 12 (24.5%) in grade B, 2 (4.1%) in e grade C, and 0 in grades D and E. The clinically acceptable rate (Gertzbein-Robbins grades A and B) was 95.9%. No patient experienced vascular or neurologic injury due to screw displacement. The results of univariate analysis showed no statistical significance for patient factors (age, gender, BMI, preoperative cervical curvature, and causes of atlantoaxial instability); no statistical significance for the surgical factors of tracker position, screw position, screw type, and screw placement approach ( P>0.05), and a statistically significant difference for the difference between the effective width of the axis pedicle and the screw diameter ( t=3.484, P<0.001). The results of multifactorial analysis showed that tracker fixation to the Mayfield frame in robot-assisted axis pedicle screw placement over the axis spinous process resulted in more accurate screw placement [ OR=83.231, 95% CI(3.898, 1776.952), P=0.005]; and the greater the difference between the effective width of the axis pedicle and the diameter of the screw, the greater the accuracy of screw placement [ OR=5.330, 95% CI(1.648, 17.243), P=0.005]. Conclusion:Robot-assisted axis pedicle screw placement is both precise and safe. Securing the tracker to the Mayfield clamp rather than the axis spinous process enhances the accuracy of screw placement. A greater discrepancy between the axis pedicle's effective width and the screw diameter decreases the likelihood of cortical violation. Preoperative planning, including the selection of appropriate screw types and adjusting the trajectory in three dimensions to maximize the difference between the pedicle's effective width and the screw diameter, can mitigate the risk of cortical breach and subsequent vascular and neurological injury.

Objective To analyze the characteristics of time in range(TIR)and its relationship with oxidative stress(OS)and insulin resistance status(HOMA-IR)in patients with type 2 diabetes mellitus(T2DM)and sleep apnea-hypopnea syndrome(OSAHS).Methods According to apnea-hypopnea index(AHI),165 T2DM in patients were divided into simple T2DM group(AHI<5 times/h,n=43),T2DM combine OSAHS mild group(OSAHS-G,5≤AHI<15 times/h,n=51),T2DM combined OSAHS moderate group(OSAHS-M,15≤AHI≤30 times/h,n=40)and T2DM combine OSAHS severe group(OSAHS-S,AHI>30 times/h,n=31).TIR was calculated by dynamic blood glucose monitoring.Superoxide dismutase(SOD),glutathione peroxidase(GSH-Px)and other indexes were detected and analyzed.Results Compared with simple T2DM group,the levels of HOMA-IR,8-iso-PGF2a and Ox-LDL were higher in T2DM combined OSAHS-G,OSAHS-M or OSAHS-S group,while the levels of TIR,SOD and GSH-Px were lower(P<0.05).Pearson correlation analysis showed that TIR was positively correlated with the levels of SOD and GSH-Px(P<0.05 or P<0.01),and negatively correlated with the levels of 8-iso-PGF2a,Ox-LDL,HbA1c,HOMA-IR and the severity of OSAHS(P<0.01).Logistic regression analysis showed that TIR,SOD and GSH-Px were protective factors for severe OSAHS in T2DM patients,while 8-iso-PGE2a and Ox-LDL were the risk factors for severe OSAHS.Conclusions The glucose level fluctuates greatly in patients with T2DM and OSAHS.Insulin resistance and oxidative stress are factors that affect the normalization of TIR.

With the widespread use of carbapenem antibiotics,the clinical detection rate of carbapenem-resistant Gram-negative bacilli has shown a significant increase.Carbapenem-resistant Gram-negative bacilli isolates are often extensively or fully resistant,resulting in limited antimicrobial treatment options and high morbidity and mortality rates,posing a serious public health threat.The clinical treatment of carbapenem-resistant Gram-negative bacilli includes the use of single or combination antimicrobials such as polymyxin,tigecycline,and fosfomycin.A number of new antimicrobials and therapeutic approaches are under development.The clinical management of carbapenem-resistant Gram-negative infections is severely challenged by the limited choice of antimicrobial agents.Therefore,this article reviews the current status and progress of antimicrobial treatment for carbapenem-resistant Gram-negative bacilli to providing clinical reference.