Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Dynamic tracking analysis of monoclonal antibodies(mAbs)biotransformation in vivo is crucial,as certain modifications could inactivate the protein and reduce drug efficacy.However,a particular chal-lenge(i.e.immune recognition deficiencies)in biotransformation studies may arise when modifications occur at the paratope recognized by the antigen.To address this limitation,a multi-epitope affinity technology utilizing the metal organic framework(MOF)@Au@peptide@aptamer composite material was proposed and developed by simultaneously immobilizing complementarity determining region(CDR)mimotope peptide(HH24)and non-CDR mimotope aptamer(CH1S-6T)onto the surface of MOF@Au nanocomposite.Comparative studies demonstrated that MOF@Au@peptide@aptamer exhibited signifi-cantly enhanced enrichment capabilities for trastuzumab variants in comparison to mono-epitope af-finity technology.Moreover,the higher deamidation ratio for LC-Asn-30 and isomerization ratio for HC-Asn-55 can only be monitored by the novel bioanalytical platform based on MOF@Au@peptide@aptamer and liquid chromatography-quadrupole time of flight-mass spectrometry(LC-QTOF-MS).Therefore,multi-epitope affinity technology could effectively overcome the biases of traditional affinity materials for key sites modification analysis of mAb.Particularly,the novel bioanalytical platform can be suc-cessfully used for the tracking analysis of trastuzumab modifications in different biological fluids.Compared to the spiked phosphate buffer(PB)model,faster modification trends were monitored in the spiked serum and patients'sera due to the catalytic effect of plasma proteins and relevant proteases.Differences in peptide modification levels of trastuzumab in patients'sera were also monitored.In summary,the novel bioanalytical platform based on the multi-epitope affinity technology holds great potentials for in vivo biotransformation analysis of mAb,contributing to improved understanding and paving the way for future research and clinical applications.

Dynamic tracking analysis of monoclonal antibodies (mAbs) biotransformation in vivo is crucial, as certain modifications could inactivate the protein and reduce drug efficacy. However, a particular challenge (i.e. immune recognition deficiencies) in biotransformation studies may arise when modifications occur at the paratope recognized by the antigen. To address this limitation, a multi-epitope affinity technology utilizing the metal organic framework (MOF)@Au@peptide@aptamer composite material was proposed and developed by simultaneously immobilizing complementarity determining region (CDR) mimotope peptide (HH24) and non-CDR mimotope aptamer (CH1S-6T) onto the surface of MOF@Au nanocomposite. Comparative studies demonstrated that MOF@Au@peptide@aptamer exhibited significantly enhanced enrichment capabilities for trastuzumab variants in comparison to mono-epitope affinity technology. Moreover, the higher deamidation ratio for LC-Asn-30 and isomerization ratio for HC-Asn-55 can only be monitored by the novel bioanalytical platform based on MOF@Au@peptide@aptamer and liquid chromatography-quadrupole time of flight-mass spectrometry (LC-QTOF-MS). Therefore, multi-epitope affinity technology could effectively overcome the biases of traditional affinity materials for key sites modification analysis of mAb. Particularly, the novel bioanalytical platform can be successfully used for the tracking analysis of trastuzumab modifications in different biological fluids. Compared to the spiked phosphate buffer (PB) model, faster modification trends were monitored in the spiked serum and patients' sera due to the catalytic effect of plasma proteins and relevant proteases. Differences in peptide modification levels of trastuzumab in patients' sera were also monitored. In summary, the novel bioanalytical platform based on the multi-epitope affinity technology holds great potentials for in vivo biotransformation analysis of mAb, contributing to improved understanding and paving the way for future research and clinical applications.

Objective To study the clinical characteristics and bacterial antimicrobial susceptibility testing results of patients with clinically isolated Ralstonia pickettii(R.pickettii),and provide basis for the rational use of antimi-crobial agents.Methods Inpatients with R.pickettii infection who were treated at the Tianjin First Central Hospi-tal from January 2014 to December 2023 were analyzed retrospectively.Clinical characteristics and antimicrobial sus-ceptibility testing results were analyzed.Results A total of 80 strains of Ralstonia spp.were isolated over 10-year period,including 42(52.5％)non-repetitive strains of R.pickettii.Among 42 R.pickettii strains,64.3％were isolated from male patients.The strains isolated from sputum,catheter,blood,throat swabs,and drainage fluid specimens accounted for 38.1％,28.6％,19.0％,4.8％,and 2.4％,respectively.The clinical distribution of R.pickettii was highest in the intensive care unit(ICU),with a proportion of 52.4％.The number of infected patients first increased and then decreased with the years,followed by a slight fluctuation.There was no statistically signifi-cant difference in the number of infected patients in each department over the years(P＞0.05).R.pickettii had higher susceptibility rates to doxycycline,levofloxacin,ciprofloxacin,and minocycline,susceptibility rates were 78.3％-90.9％,but was completely resistant to compound sulfamethoxazole and cefazolin(100％),it also had higher resistance rates to aztreonam,colistin,cefotetan,tobramycin,amikacin,ceftazidime,and gentamicin(80.0％-97.4％).There was no statistically significant difference in the resistance rates to 21 antimicrobial agents among different years(all P＞0.05).Conclusion R.pickettii is mainly from ICU,and the majority of the infected population are adult males.Most strains are isolated from sputum and catheter.R.pickettii presents multidrug re-sistance.Attention should be paid to the changes in the resistance rates of antimicrobial agents,strengthen the dy-namic monitoring of bacterial resistance and guide the rational selection of antimicrobial agents in clinic,implement early and effective treatment to improve the prognosis of the patients.

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 study the expression of the Homeobox C6(HOXC6)gene in the homeobox family in PCa,its effect on the biological behavior of PCa cells and its action mechanism.Methods:Based on the studies of HOXC6 retrieved from the data-base of Gene Expression Profiling Interactive Analysis(GEPIA),we analyzed the expression of HOXC6 in PCa and the relationship of its expression level with the survival prognosis of the patients.We detected the expression of the HOXC6 protein in PCa tissues and cells by Western blot,stably interfered with the expression of the HOXC6 gene in human PCa DU145 and PC-3 cells and normal prosta-tic epithelial RWPE-1 cells using the siRNA plasmid,and determined the effects of HOXC6 on the proliferation,migration and inva-siveness of PCa cells by CCK8,plate cloning and scratch healing and Transwell invasion assays.Using the GEPIA database,we ana-lyzed the correlation of the Wnt tumor inhibitory factor-secreted frizzled-related protein 1(SFRP1)gene with HOXC6,and detected the expressions of HOXC6,SFRP1,Wnt and β-catenin in PC-3 cells after siRNA-HOXC6 transfection by Western blot.Results:The expression of HOXC6 was dramatically higher in the PCa than in the normal prostate tissue(P<0.01),and in the PCa cells than in the normal prostatic epithelial cells(P<0.01).Bioinformatics analysis indicated a lower survival rate of the PCa patients with a high than those with a low HOXC6 expression(P=0.011).The relative expression of the HOXC6 protein,absorbance value,number of clones formed and number of invaded cells were significantly lower in the siRNA group than in the negative controls(P<0.05).Ac-cording to the GEPIA database,highly expressed SFRP1 was associated with a good prognosis of PCa,and the protein expressions of Wnt and β-catenin were markedly increased while that of SFRP1 decreased in the PCa PC-3 cell line(P<0.05).The expressions of the Wnt and β-catenin proteins were decreased and that of SFRP1 increased significantly in the siRNA-HOXC6 transfection group com-pared with those in the siRNA negative control and PCa PC-3 groups(P<0.05).Conclusion:HOXC6 is highly expressed in PCa tissues and related to the proliferation,migration and invasiveness of PCa cells.HOXC6 promotes the growth of DU145 and PC-3 cells in PCa by inhibiting the SFRP1/Wnt/β-catenin signaling pathway,and may be a potential target for clinical treatment of PCa.

The therapeutic application of artemisinin (ART) is restricted in application due to its poor water solubility and stability. In this study, the long-circulating liposomes (L-Lip) were constructed to improve the solubility and stability of ART. The preparation method, physicochemical properties, serum stability, in vitro release profile and cytotoxicity of the ART loaded long-circulating liposomes were investigated. Using the particle size and entrapment efficiency (EE) as the evaluation index, the preparation procedure was optimized by the Box-Behnken response surface design based on the single factor screening method. The ART loaded long-circulating liposomes were prepared by filming rehydration method, and evaluated with particle size and entrapment efficiency. The optimal formulation was as follows:lipid-cholesterol=5.22:1 (mass ratio), drug-lipid=1:23.15 (mass ratio), lipid concentration=14.35 mg·mL^-1, and molar percentage of mPEG=2%. The morphology of L-Lip was uniformly spherical shape according to optimal formulation. The mean size and polydispersity index (PDI) were about (113.3 ±4.7) nm and 0.227 ±0.022 respectively, the zeta potential was (-12.9 ±2.6) mV, and the entrapment efficiency (EE) of ART was (95.88 ±4.8)%. The L-Lip had good stability at 4℃ for 15 days and the particle sizes did not exhibit significant variations in 50% rat plasma over 24 h at 37℃. The in vitro release study of formulation showed a sustained release. Moreover, the cytotoxicity exhibited that blank liposomes were of great safety. Compared with the free ART, the liposome formulation achieved lower cytotoxicity at the high concentration. The L-Lip successfully prepared by a simple filming-rehydration method exhibited ideal physicochemical properties and were enhanced safety, which may sever as a promising nanoplatform for clinical application.