ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

OBJECTIVE To study the protective effect and potential mechanism of chikusetsu saponin Ⅳ a （chsⅣ） on renal function in diabetic nephropathy （DN） model rats. METHODS DN rat model was established by high-fat diet combined with streptozotocin injection. Thirty-six model rats were randomly divided into model group （i.g. administration of normal saline， high-fat diet）， chsⅣ low-dose and high-dose groups （i.g. administration of 90， 180 mg/kg chsⅣ， high-fat diet）， with 12 rats in each group. Additionally， 10 normal rats were set as the control group （i.g. administration of normal saline， regular diet）. From the 5th to the 12th week after streptozotocin injection， they were given intragastric administration of relevant drug or normal saline， once a day. After the last medication， the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine and urine protein as well as the levels of reduced glutathione （GSH）， superoxide dismutase （SOD） and malondialdehyde （MDA） in renal tissues were measured. Additionally， the insulin resistance index was calculated. Hematoxylin-eosin， periodic acid-Schiff， and Masson staining techniques were employed to examine the histopathological alterations in the renal tissue. The expressions of Notch signaling pathway-related proteins in renal tissue were detected by immunohistochemical staining and Western blot methods. RESULTS Compared with model group， the histomorphological of renal tissues in the chsⅣ low- and high-dose groups were significantly improved， with significant decreases in renal histological scores， mesangial expansion index， and glomerulosclerosis scores （ P ＜0.05）； the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine， urine protein and homeostasis model assessment for insulin resistance， as well as MDA content， the expression levels of Notch1， Notch intracellular domain， hairy and enhancer of Split 1 and Delta-like protein 1 in renal tissue were all significantly decreased （ P ＜0.05）. The levels of GSH and SOD in renal tissue were significantly elevated （ P ＜0.05）. Moreover， the improvement in these indicators was significantly more pronounced in the chsⅣ high-dose group compared to the chsⅣ low-dose group （ P ＜0.05）. CONCLUSIONS ChsⅣ can ameliorate renal pathological damage and functional impairment in DN rats. Its underlying mechanisms include restoration of glucose homeostasis and insulin sensitivity， attenuation of renal oxidative stress， and suppression of aberrant Notch signaling pathway activation.

Endoscopic transforaminal lumbar interbody fusion (TLIF) offers substantial advantages in the management of degenerative spinal diseases, including accelerated postoperative recovery. However, its technical complexity and steep learning curve pose risks for nerve root injury. Optimizing nerve root protection in full-endoscopic facet-sparing TLIF (FE fs-TLIF) and full-endoscopic facet-resecting TLIF (FE fr-TLIF) is essential for enhancing surgical safety. This study aimed to improve the nerve root protection in FE fs-TLIF and FE fr-TLIF by optimizing cage glider selection and insertion techniques based on the specific cage shape—banana-shaped or bullet-shaped. The goal was to ensure safe cage positioning and mitigate nerve root injury during discectomy, endplate preparation, and cage insertion. These strategies were validated through cadaveric simulations and clinical implementation. In FE fr-TLIF utilizing bullet-shaped (straight) cages, one-tip and two-tip cage gliders effectively protected the traversing nerve root by facilitating medial cage entry, thereby minimizing irritation of the exiting nerve root. Conversely, in FE fr-TLIF with banana-shaped cages, the lateral tilt of the cage holder during implantation required the use of a two-tip cage glider to protect the traversing and exiting nerve roots, thereby mitigating the potential risk of nerve irritation. In FE fs-TLIF, a one-tip cage glider is preferred for safeguarding the exiting nerve root, while the traversing root is inherently protected by the medial wall of the facet joint. The use of a two-tip cage glider in FE fs-TLIF can cause injury to the nerve root during glider insertion. In addition to the selection of cage gliders, improper cage insertion steps can also contribute to postoperative neurapraxia. The appropriate selection of cage gliders with corresponding insertion techniques is critical for nerve root protection in endoscopic TLIF. Tailoring these choices to the specific approach (FE fs-TLIF or FE fr-TLIF) and cage type (banana or bullet) enhances surgical safety and clinical outcomes.

Objectives:To explore whether short-course radiotherapy (SCRT)-based total neoadjuvant therapy (TNT) combined with PD-1 inhibitors could further promote tumor regression and improve the prognosis.Methods:This is a prospective, multicenter, two-arm randomized controlled, seamless phase Ⅱ/Ⅲ trial for proficient mismatch repair or microsatellite stable (pMMR/MSS) locally advanced rectal cancer (LARC). Eligible patients were randomly assigned to the iTNT (TNT+PD-1) group or the TNT group. Patients in the TNT group received SCRT (5 Gy×5) followed by 4 cycles of CAPOX or 6 cycles of mFOLFOX chemotherapy, with the iTNT group receiving SCRT followed by the same regime in combination with 4 cycles of Sintilimab. Total mesorectal excision (TME) surgery or watch and wait (W&W) was performed after neoadjuvant therapy and then 2 cycles of same regimen as before were recommended. The primary endpoints are the complete response (CR) rate for phase Ⅱ trial and 3-year disease-free survival (DFS) for phase Ⅲ trial. A total of 588 patients will be enrolled for the phase Ⅱ/Ⅲ trial. Short-term efficacy and safety data from the initial 100 treated patients were analyzed as planned.Results:From 2022-8-31 to 2023-5-24 the initial 100 patients were enrolled from 10 hospitals in China, 76.0%(76/100) patients were male, and the median age was 61 years (21-74 years). More patients had tumors located in the lower rectum (78.0%, 78/100), staged T3-4 (97.0%, 97/100) and N1-2 (93.0%, 93/100), and about half of the tumors invaded the mesorectal fascia (52.0%, 52/100) and with extramural vascular invasion (51.0%, 51/100). Analyses were performed according to the per-protocal (PP) set. All patients in the iTNT group ( n=52) and the TNT group ( n=48) completed SCRT; The 4-cycle chemotherapy±Sintilimab completion rates were 86.5% and 100.0% in the iTNT and TNT groups, respectively. In the iTNT group, 82.7% (43/52), 11.5% (6/52), and 5.8% (3/52) of the patients received 4, 3, and 2 cycles of PD-1 inhibitor. After TNT, 68 patients underwent radical surgery and 15 patients achieved cCR and adopted W&W. The pathological complete response (pCR) rates were 48.5% (16/33) and 17.1% (6/35) in the iTNT and TNT groups, with CR rates of 50.0% (25/50) and 26.1% (12/46), respectively. The incidence of treatment-related grade 3-4 adverse events was 26.9% (14/52, iTNT group) and 18.8% (9/48, TNT group), with thrombocytopenia and leukopenia being the most common. Among patients receiving immunotherapy, grade 3 immunotherapy-related adverse events occurred in 2 (3.8%, 2/52) patients: one case was pancreatitis, another case was hepatitis combined with myositis and myocarditis. Conclusion:The preliminary results show that SCRT-based TNT combined with PD-1 inhibitors could further improve the CR rate for LARC without unexpected serious adverse events.

Objective To propose a dynamic early warning model based on machine learning methods and validate its predi-ctive efficacy so as to achieve precise assessment and early warning of mortality risk in patients with traumatic hypothermia.Methods Firstly,a total of 480 patients who met inclusion criteria were retrospectively selected from the eICU database and randomly divided into training and test sets at an 8∶2 ratio.Secondly,physiological parameters were extracted from these patients,and five machine learning algorithms including XGBoost,AdaBoost,LightGBM,logistic regression(LR)and random forest(RF)were employed respectively to develop dynamic mortality risk warning models for traumatic hypothermia patients,utilizing a 1-hour observation window.Thirdly,receiver operating characteristic curves(ROC)were plotted using the test set data and the effects of different warning windows on the model performance were analyzed by calculating the AUC.Finally,the interpretability of the models was analyzed using the SHapley Additive exPlanations(SHAP)algorithm to elucidate the contribution of each feature to predictive performance.Results The optimal warning window for the dynamic warning model constructed using the eICU database was 12 hours,and in case of 12-hour warning window the logistic regression model achieved the highest AUC of 0.935 and showed optimal predictive performance.The results of the interpretability analysis by the SHAP algorithm showed that body temperature was the feature that had the greatest impact on the model results,and its reduction was positively correlated with the increased risk of death.Conclusion The machine learning-based dynamic warning model for mortality risk in traumatic hypothermia patients enables real-time dynamic risk assessment,providing robust support for clinicians to identify the patient's condition changes at an early stage and references for the adjustment of clinical treatment programs.[Chinese Medical Equipment Journal,2025,46(3):9-14]

Objective:To construct a sizeable naive human Fab phage display antibody library to screen high-affinity specific antibodies in vitro. Methods:Total RNA was extracted from peripheral blood mononuclear cells (PBMCs) of 126 healthy individuals, subsequently reverse-transcribed into cDNA, and used as a template. PCR amplification was performed to obtain the V H from IgG, IgM and light chain κ, λ, separately, with the initial PCR products serving as templates for a second round of PCR. Overlap extension PCR was employed to generate fragments of the κ and λ light chains. These fragments were ligated with the phage vector pNC3, which harbors the variable region 1 of the heavy chain, to construct a recombinant phage plasmid. This plasmid was then electroporated into competent Escherichia Coli TG1 cells to establish a naive human Fab phage display antibody library. One hundred clones were randomly selected for identification and sequencing, and antibody gene polymorphisms were analyzed using the IMGT database and MAFFT software. Recombinant α-hemolysin from Staphylococcus aureus was utilized to screen Fab antibody fragments through biopanning of the antibody library, followed by random selection of phage ELISA-identified clones. The positive clones (antigen A450∶blank control A450≥2.1) were sequenced. Results:Two large naive Fab phage display antibody libraries were successfully constructed, in which the capacity of κ and λ chain antibody libraries were 1.25×10 11 and 1.54×10 11, respectively. The titers for two antibody libraries were 6.04×10 13 CFU/ml and 3.50×10 13 CFU/ml. The positive transformation insertion rates for κ and λ chain antibody libraries were 96% (96/100) and 100% (100/100), respectively. Sequence analysis revealed that all antibody sequences were unique. The amino acid sequences in the skeletal region were relatively conserved. In contrast, significant variations in the length of the complementarity determining region (CDR) were found, and the diversity of amino acid sequence of the complementary determining region was high, especially the CDR3. Analysis using the IMGT database indicated that the sequences exhibited a broad distribution across variable-diversity-joining gene families. After six rounds of panning, specific phage antibodies enrichment targeting α-hemolysin were achieved. A total of 142 monoclonal antibodies were sequenced, yielding 8 distinct Fab antibody sequences. Conclusion:This study successfully constructed two naive human Fab phage display antibody libraries with large capacity and good diversity, which can be used for screening human antibodies for serum epidemiology.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Objective To investigate the dosimetric differences in preoperative short-course volumetric modulated arc therapy(VMAT)for rectal cancer using different fluence smoothing(FS)levels in the Monaco Treatment Planning System(Monaco TPS).Methods Twenty rectal cancer patients who received preoperative neoadjuvant short-course VMAT at some hospital from September 2021 to December 2022 were retrospectively selected.Four groups of radiotherapy plans were formulated using the Monaco TPS for each case,which were classified into an off group,a low group,a medium group and a high group based on the FS levels.Then the four groups were compared in terms of the dosimetric parameters,monitor unit and number of the segments in the planning target volume(PTV)and organ at risk(OAR).Statistical analysis was performed using SPSS 27.0 software.Results All the four groups had the doses to the target volume meeting clinical requirements,which had no significant differences in the doses to 5％(D5％)and 95％(D95％)to the target volume and the maximum dose(Dmax),minimum dose(Dmin),mean dose(Dmean)and conformity index(all P＞0.05).Statistical differences were found between the homogeneity indexes of the four groups(P＜0.05),with the medium group behaving the best.The number of the segments rose while the mornitor units decreased siginificantly with the increase of FS levels,with the differences being statistically significant(P＜0.05).There were no significant differences between the V25,V20,V15 and V10 of the small intestine,the V25 and V20 of the bladder and the V15 and V10 of the left and right femur(all P＞0.05).Conclusion In preoperative short-course VMAT for rectal cancer,clinical requirements can be met with different FS levels in the Monaco TPS,and medium-level FS results in optimal overall dose distribution in terms of treatment planning.[Chinese Medical Equipment Journal,2025,46(5):48-53]

Objectives:This study aims to evaluate the relationship between the triglyceride-glucose body mass index(TyG-BMI),the right pericoronary fat attenuation index(RCA-FAI),and prognosis in patients with coronary artery disease(CAD).Methods:This study included 513 CAD patients who underwent coronary computed tomography angiography(CCTA)and coronary angiography between April 2018 and June 2023.Data collection and parameter calculations were performed for all research variables.The patients were stratified into three groups based on TyG-BMI tertiles:T1 group(TyG-BMI≤207.02,n=171),T2 group(207.02