Liquiritigenin(LG)is a flavone of pharmacological importance,however,its application potential is severely limited due to its poor water solubility.LG could be disassociated slightly in water to form phenolate anion,therefore,better solubilization effect is expected by inclusion with cationic cyclodextrins(CCDs).In this work,four kinds of CCDs modified with amino groups at the primary face were synthesized,and their solid inclusion complexes with LG were successfully prepared by preparing their saturated solutions.The formation of the solid inclusion complexes was confirmed by scanning electron microscopy(SEM)and powder X-ray diffraction(PXRD),and their supramolecular binding behavior in solution was studied using multiple techniques.A 1∶1 inclusion stoichiometry of inclusion complexation was defined using Job plot by ultraviolet-visible(UV-vis)spectroscopy,and their binding stability constants(Ks)were determined as 2862.77,3494.70,6521.85 and 9599.48 L/mol using UV-vis spectroscopic titration,far more superior to that of nativeβ-CD(Ks=236.79 L/mol).This indicated that the amino side chains on CCDs could actively participate in the inclusion complexation through anion-cation interactions,significantly strengthening the host-guest binding between CCDs and LG.The inclusion modes were further elucidated based on proton and two-dimensional rotating-frame overhauser enhancement spectroscopy(2D-ROESY)nuclear magnetic resonance(NMR)experiments and molecular docking.Water solubility of LG was dramatically promoted up to 4.9 mg/mL,which was 70-fold higher than that of native LG.This study could draw inspiration for the binding and solubilization of phenols such as flavones by design of cationic macrocyclic molecules.

Objective To analyze the feasibility and advantage of indocyanine green(ICG)fluorescence imaging technique in the thoracoscopic anatomical segmentectomy.Methods Patients with small pulmonary nodules who underwent thoracoscopic anatomical segmentectomy in our department from January 2023 to June 2024 were selected and divided into the ICG fluorescence group(35 cases determining intersegmental plane through ICG fluorescence imaging method)and the modified inflation-deflation group(42 cases determining intersegmental plane through modified inflation-deflation method)according to different methods of determining intersegmental plane.The surgery-related indicators including time of intersegmental plane occurrence,operation time,number of lymph node dissection,postoperative duration of chest tube and postoperative hospital stay as well as the occurrence of complications in the two groups were counted.Patients over 60 years old in two groups were selected and the differences in surgery-related indicators were analyzed.Results The time of intersegmental plane occurrence and operation time in the ICG fluorescence group were shorter than those in the modified inflation-deflation group,with statistically significant differences(P<0.05).There was no significant difference in the number of lymph node dissection,postoperative duration of chest tube or postoperative hospital stay between the two groups(P>0.05).There was no significant difference in the incidence of postoperative complications between the two groups(P>0.05).The time of intersegmental plane occurrence,operation time and postoperative hospital stay of patients over 60 years old in the ICG fluorescence group were shorter than those in the modified inflation-deflation group,with statistically significant differences(P<0.05).Conclusion ICG fluorescence imaging method can display the intersegmental plane clearly and quickly,which can shorten the time of intersegmental plane occurrence and hospital stay in elderly patients with pulmonary nodules.

The scaphoid bone is one of the important bone of hand,which is frequently injured and difficult to treat in clinical practice.Therefore,it is very important to deeply study the microstructure and biomechanical characteristics of the scaphoid bone for understanding its injury mechanism and optimizing treatment scheme.Microcomputed tomography(micro-CT)provides high-resolution imaging of bone tissue,while finite element analysis can help to simulate the stress distribution and behavioral patterns of the scaphoid bone under various physiological and pathological states.The high-resolution three-dimensional image of the scaphoid bone obtained by micro-CT technology can be used to construct finite element models of real anatomical structure of the scaphoid bone,thus achieving accurate simulation of the mechanical properties of the scaphoid bone.The fusion of these two advanced technologies provides a new perspective for revealing the structural and functional relationships and injury mechanism of the scaphoid bone.Therefore,this paper reviews the anatomical characteristics of the scaphoid bone and its biomechanical behavior in different states,emphasizing the specific applications and advantages of micro-CT and finite element analysis techniques in the study of the scaphoid bone.By summarizing the research findings in recent years,this paper provides novel scientific basis and methods for the diagnosis,treatment,and prevention of scaphoid bone-related disorders.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective To analyze the feasibility and advantage of indocyanine green(ICG)fluorescence imaging technique in the thoracoscopic anatomical segmentectomy.Methods Patients with small pulmonary nodules who underwent thoracoscopic anatomical segmentectomy in our department from January 2023 to June 2024 were selected and divided into the ICG fluorescence group(35 cases determining intersegmental plane through ICG fluorescence imaging method)and the modified inflation-deflation group(42 cases determining intersegmental plane through modified inflation-deflation method)according to different methods of determining intersegmental plane.The surgery-related indicators including time of intersegmental plane occurrence,operation time,number of lymph node dissection,postoperative duration of chest tube and postoperative hospital stay as well as the occurrence of complications in the two groups were counted.Patients over 60 years old in two groups were selected and the differences in surgery-related indicators were analyzed.Results The time of intersegmental plane occurrence and operation time in the ICG fluorescence group were shorter than those in the modified inflation-deflation group,with statistically significant differences(P<0.05).There was no significant difference in the number of lymph node dissection,postoperative duration of chest tube or postoperative hospital stay between the two groups(P>0.05).There was no significant difference in the incidence of postoperative complications between the two groups(P>0.05).The time of intersegmental plane occurrence,operation time and postoperative hospital stay of patients over 60 years old in the ICG fluorescence group were shorter than those in the modified inflation-deflation group,with statistically significant differences(P<0.05).Conclusion ICG fluorescence imaging method can display the intersegmental plane clearly and quickly,which can shorten the time of intersegmental plane occurrence and hospital stay in elderly patients with pulmonary nodules.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

The scaphoid bone is one of the important bone of hand,which is frequently injured and difficult to treat in clinical practice.Therefore,it is very important to deeply study the microstructure and biomechanical characteristics of the scaphoid bone for understanding its injury mechanism and optimizing treatment scheme.Microcomputed tomography(micro-CT)provides high-resolution imaging of bone tissue,while finite element analysis can help to simulate the stress distribution and behavioral patterns of the scaphoid bone under various physiological and pathological states.The high-resolution three-dimensional image of the scaphoid bone obtained by micro-CT technology can be used to construct finite element models of real anatomical structure of the scaphoid bone,thus achieving accurate simulation of the mechanical properties of the scaphoid bone.The fusion of these two advanced technologies provides a new perspective for revealing the structural and functional relationships and injury mechanism of the scaphoid bone.Therefore,this paper reviews the anatomical characteristics of the scaphoid bone and its biomechanical behavior in different states,emphasizing the specific applications and advantages of micro-CT and finite element analysis techniques in the study of the scaphoid bone.By summarizing the research findings in recent years,this paper provides novel scientific basis and methods for the diagnosis,treatment,and prevention of scaphoid bone-related disorders.

Objective:To investigate the application of (4R)-4-(3-[ 18F]fluoranyl-5-fluorophenyl)-1-((3-methylpyridin-4-yl)methyl)pyrrolidin-2-one( 18F-SynVesT-1), a synaptic vesicle glycoprotein 2A (SV2A) radioactive tracer, in patients with Alzheimer′s disease (AD). Methods:A total of 20 AD patients (2 males, 18 females, age (66.4±8.1) years) with positive β-amyloid (Aβ) deposition and 20 normal controls (NC; 9 males, 11 females, age (62.6±8.6) years ) without Aβ deposition were retrospectively recruited from Huashan Hospital, Fudan University between December 2021 and December 2022. All of them underwent 18F-SynVesT-1 PET/MR and 18F-Florbetapir (AV45) PET/CT scans. Preprocessing of brain 18F-SynVesT-1 PET images was carried out using statistical parametric mapping (SPM). The differences of the uptke of 18F-SynVesT-1 (synaptic density) between two groups based on ROI were compared by using either the independent-sample t test or Mann-Whitney U test. Spearman rank correlation analysis was performed to assess the relationship between synaptic density and cognitive performance. For voxelwise analysis, a general linear model was constructed to analyze differences in synaptic density between the two groups using the independent-sample t test. Furthermore, a multiple linear regression model was developed to explore the relationship between synaptic density and cognitive performance. Results:Compared to the NC group, the AD group exhibited significant widespread reduction in synaptic density across the cortical regions ( P<0.05, false discovery rate (FDR)-corrected), particularly in the medial temporal lobe (0.84±0.09 vs 1.04±0.09; t=-6.95, P<0.001), lateral temporal lobe (1.15±0.13 vs 1.31±0.08; t=-4.56, P<0.001), and lateral parietal lobe (1.24(1.04, 1.26) vs 1.32(1.23, 1.39); z=-3.25, P=0.001). Moreover, synaptic density in extensive cortical regions showed a positive correlation with mini-mental state examination (MMSE) and Montreal cognitive assessment-basic (MoCA-B) scores ( P<0.05, FDR-corrected). Notably, significant associations were observed between MMSE and MoCA-B scores and synaptic density in the lateral temporal lobe ( rs values: 0.71, 0.74, both P<0.001) and medial temporal lobe ( rs values: 0.71, 0.74, both P<0.001). Conclusions:18F-SynVesT-1 PET imaging is a valuable tool for evaluating synaptic density, specifically in the context of AD. The observed widespread reduction in synaptic density across cortical regions of patients with AD are closely related to cognitive decline.

Objective:To introduce a surgical method involving the indwelling of double-J tubes(DJT)in the seminal vesicles after transurethral seminal vesiculoscopy(TSV)in order to reduce the recurrence of refractory ejaculatory duct obstruction(EDO).Methods:This randomized controlled trial included 67 EDO patients undergoing TSV in our hospitals,27 with(the trial group)and 29 without postoperative indwelling of DJTs in the seminal vesicles(the control group).We collected the general information on the pa-tients and TSV-related parameters,including age,body mass index(BMI),preoperative use of antibiotics,history of urinary tract dis-ease,operation time,hospital stay and intra-and postoperative complications,and performed comparative analyses particularly on the surgical effect,complications,recurrence rate and time to recurrence in the two groups of patients.Results:The patients in the trial and control groups were followed up for(40.5±10.6)and(32.5±14.8)months,respectively.There were no statistically signifi-cant differences in the baseline data,intra-and postoperative complications,and postoperative hospital days between the two groups(P＞0.05).Compared with the controls,the patients in the trial group showed a significantly shorter operation time([62.8±6.1]vs[49.5±7.7]min,P＜0.05)and a lower recurrence rate than the controls(18.5％vs 44.8％,P＜0.05),but with no statisti-cally significant difference in the median time to recurrence(21.0 mo vs 22.0 mo,P＞0.05).Conclusion:The novel technique of indwelling double-J tubes in the seminal vesicles after TSV can significantly reduce the recurrence rate of refractory EDO.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.