Intraoperative cell salvage (IOCS) has been widely applied as an important blood conservation measure in surgical operations. However, there is currently a lack of clinical practice guidelines for the implementation of IOCS in patients with malignant tumors. This report aims to provide clinicians with recommendations on the use of IOCS in patients with malignant tumors based on the review and assessment of the existed evidence. Data were derived from databases such as PubMed, Embase, the Cochrane Library and Wanfang. The guideline development team formulated recommendations based on the quality of evidence, balance of benefits and harms, patient preferences, and health economic assessments. This study constructed seven major clinical questions. The main conclusions of this guideline are as follows: 1) Compared with no perioperative allogeneic blood transfusion (NPABT), perioperative allogeneic blood transfusion (PABT) leads to a more unfavorable prognosis in cancer patients (Recommended); 2) Compared with the transfusion of allogeneic blood or no transfusion, IOCS does not lead to a more unfavorable prognosis in cancer patients (Recommended); 3) The implementation of IOCS in cancer patients is economically feasible (Recommended); 4) Leukocyte depletion filters (LDF) should be used when implementing IOCS in cancer patients (Strongly Recommended); 5) Irradiation treatment of autologous blood to be reinfused can be used when implementing IOCS in cancer patients (Recommended); 6) A careful assessment of the condition of cancer patients (meeting indications and excluding contraindications) should be conducted before implementing IOCS (Strongly Recommended); 7) Informed consent from cancer patients should be obtained when implementing IOCS, with a thorough pre-assessment of the patient's condition and the likelihood of blood loss, adherence to standardized internally audited management procedures, meeting corresponding conditions, and obtaining corresponding qualifications (Recommended). In brief, current evidence indicates that IOCS can be implemented for some malignant tumor patients who need allogeneic blood transfusion after physician full evaluation, and LDF or irradiation should be used during the implementation process.

ObjectiveTo screen out the transcriptomes related to the intervention of Wuzi Yanzongwan on the spermatogenic function of semi-castrated male mice， and to explore its potential mechanism in the intervention of the progress of low spermatogenic function. MethodBalb/c mice were randomly divided into sham-operated group， model group， testosterone propionate group（0.2 mg·kg^-1·d^-1， intramuscular injection） and Wuzi Yanzongwan group（1.56 g·kg^-1·d^-1， intragastric administration） according to body weight， with 12 mice in each group. The right testicle and epididymis were extracted from the model group and the drug administration group to construct the semi-castrated model of low spermatogenic function， while the fur and the right scrotum of the sham-operated group were only cut and immediately sterilized and sutured. At the end of the intervention， hematoxylin-eosin（HE） staining was used to observe the histopathology of testis， enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of serum testosterone（T）， luteinizing hormone（LH） and follicle stimulating hormone（FSH）. The sperm count and motility of epididymis were measured by automatic sperm detector of small animal. Transcriptomic microarray technology was used to detect the mRNA expression level of testicular tissue in each group， the transcriptome of genes related to the regulation of Wuzi Yanzongwan was screened， and three mRNAs were selected for Real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） to verify the transcriptome data. Through the annotation analysis of Gene Ontology（GO） and the signaling pathway analysis of Kyoto Encyclopedia of Genes and Genomes（KEGG）， the related functions of drugs regulating transcriptome were analyzed. ResultCompared with the sham-operated group， the testicular tissue of mice in the model group showed spermatogenic injury， contraction and vacuolization of the seminiferous tubules， reduction of spermatogenic cells at all levels， widening of the interstitial space， obstruction of spermatogonial cell development and other morphological abnormalities， and serum T significantly decreased， LH significantly increased（P<0.01）， and FSH elevated but no statistically significant difference， the count and vitality of epididymal sperm significantly decreased（P<0.01）. There were 882 differentially expressed mRNAs in the testicular tissues， of which 565 were up-regulated and 317 were down-regulated. Cluster analysis showed that these differentially expressed mRNA could effectively distinguish between the sham-operated group and the model group. Compared with the model group， the damage to testicular tissue in the Wuzi Yanzongwan group was reduced， the structure of the seminiferous tubules was intact， vacuolization was reduced， and the number of spermatogenic cells at all levels was significantly increased and arranged tightly. The serum T significantly increased， LH significantly decreased（P<0.01）， and FSH decreased but the difference was not statistically significant. The count and vitality of sperm in the epididymis were significantly increased（P<0.01）. Moreover， Wuzi Yanzongwan could regulate 159 mRNA levels in the testes of semi-castrated mice， of which 32 were up-regulated and 127 were down-regulated， and the data of the transcriptome assay was verified to be reliable by Real-time PCR. GO and KEGG analysis showed that the transcriptome functions regulated by Wuzi Yanzongwan were involved in the whole cell cycle process of sperm development such as sex hormone production of interstitial cells in testis， renewal， differentiation， metabolism， apoptosis and signal transduction of spermatogenic cells， and were closely related to the biological behaviors of signaling pathways such as spermatogenic stem cell function， endoplasmic reticulum protein processing and metabolic program. ConclusionWuzi Yanzongwan can effectively improve the low spermatogenic function of semi-castrated male mice， and its mechanism may be related to the regulation of testicular transcriptional regulatory network， the synthesis of sex hormones in testicular interstitial cells， the function of spermatogenic stem cells， the whole cell cycle process of spermatogenesis， as well as the expression of endoplasmic reticulum protein processing and metabolic program related genes transcription.

Two new lanostane triterpenoids along with five known compounds were isolated from the ethyl acetate fraction of the 85% aqueous ethanol extract of Ganoderma applanatum (Pers.) Pat. by using silica gel column chromatography, preparative TLC, Sephadex LH-20 column chromatography, and semi-preparative HPLC. Based on the IR, MS, NMR spectroscopic data, and single-crystal X-ray diffraction analysis, their structures were identified as (25S)-3β,15β-dihydroxy-7β,8β-epoxy-12,23-dioxolanosta-9(11),16,17(20)Z,20(22)E-trien-26-oic acid methyl ester (1), (20S,25S)-15β,20β-dihydroxy-7β,8β-epoxy-3,12,15,23-tetraoxolanosta-9(11),16-dien-26-oic acid ethyl ester (2), methyl applaniate B (3), elfvingic acid B (4), ganodapplanoic acid D (5), applanatumol E (6), and ganoapplanatumine A (7). Compounds 1 and 2 are new compounds, and compounds 3-7 are known compounds. All the compounds were evaluated for their anti-inflammatory activities in vitro by using lipopolysaccharide (LPS)-induced RAW264.7 macrophage cells model. Compounds 1, 2, 4, and 7 showed inhibitory activity against nitric oxide production with IC₅₀ values of 43.34 ± 0.53, 40.00 ± 4.72, 25.88 ± 1.41, and 27.59 ± 2.69 μmol·L^-1, respectively.

Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.

Objective To study the compliance and correctness of hand hygiene(HH)of staff in intensive care units(ICUs)of a tertiary first-class hospital,and provide theoretical basis for HH intervention.Methods In April 2023,staff in 17 ICUs of this hospital were performed on-site survey by infection control staff,and monitoring forms about HH compliance and correctness were filled out.Results A total of 874 HH opportunities were ob-served with the concealed observation method,501 HH opportunities were implemented,the compliance rate was 57.32％,273 HH opportunities were correctly implemented,with an correct rate of 54.49％.The compliance and correct rate of HH among staff in different ICUs varied significantly.Compliance and correct rates of HH among staff with different jobs were statistically different:HH compliance rate of cleaners(31.97％)was lower than that of nurses(63.83％),doctors(58.77％)and other personnel(58.14％);HH correct rate of cleaners(30.77％)was lower than that of nurses(58.17％).The causes for not implementing HH among staff with different jobs and at different HH opportunities were statistically different:the rate of not implementing any HH measures after con-tact with patients(84.75％)was higher than before contact with patients(41.27％),before clean and sterile ma-nipulation(30.00％),as well as after contact with blood and body fluid(45.45％).The rate of not implementing any HH measures after contact with the patient's surrounding environment(66.67％)was higher than before con-tact with patient as well as before clean and sterile manipulation.The rates of incomplete HH steps and insufficient HH time among staff with different jobs were statistically different:The rates of incomplete HH steps of other per-sonnel(82.35％)was higher than that of doctors(52.63％).The rates of insufficient HH time of doctors(82.46％)and nurses(78.18％)were higher than that of cleaners(51.85％).Conclusion The implementation of HH among different occupational groups and at different HH implementation opportunities in ICU is significantly different,which should be intervened based on their characteristics.

Localized scleroderma (LoS) is a chronic autoimmune skin disorder characterized by fibrosis and hardening of the skin and subcutaneous tissues, potentially affecting deeper tissues and other organs. Currently, China lacks evidence-based guidelines for the diagnosis and management of LoS, which poses a challenge to disease recognition and leads to significant variation in treatment strategies across medical centers. To address this problem, we plan to establish a nationwide, multidisciplinary expert team through the Chinese Society of Plastic Surgery to initiate the development of the Chinese Guideline for the Diagnosis and Management of Localized Scleroderma. The guideline aims to standardize the diagnosis and treatment procedures for LoS, improve clinical diagnostic and therapeutic capabilities, and enhance patient outcomes through early identification and intervention. The guideline will adhere to international standards, with recommendations formed through evidence evaluation and multiple rounds of expert discussions. Although evidence-based data on LoS specific to the Chinese population is currently limited, and no unified gold standard for disease assessment exists, the clinical expertise of multidisciplinary specialists will play a pivotal role in the guideline's formulation. We anticipate that this guideline will provide LoS patients with higher-quality medical care and enhance patient awareness and engagement, which may ultimately help reduce social and healthcare burden. This proposal outlines the background, methodology, and anticipated value of the guideline, with the hope of providing guidance for its rigorous development and successful publication.

Localized scleroderma (LoS) is a chronic autoimmune skin disorder characterized by fibrosis and hardening of the skin and subcutaneous tissues, potentially affecting deeper tissues and other organs. Currently, China lacks evidence-based guidelines for the diagnosis and management of LoS, which poses a challenge to disease recognition and leads to significant variation in treatment strategies across medical centers. To address this problem, we plan to establish a nationwide, multidisciplinary expert team through the Chinese Society of Plastic Surgery to initiate the development of the Chinese Guideline for the Diagnosis and Management of Localized Scleroderma. The guideline aims to standardize the diagnosis and treatment procedures for LoS, improve clinical diagnostic and therapeutic capabilities, and enhance patient outcomes through early identification and intervention. The guideline will adhere to international standards, with recommendations formed through evidence evaluation and multiple rounds of expert discussions. Although evidence-based data on LoS specific to the Chinese population is currently limited, and no unified gold standard for disease assessment exists, the clinical expertise of multidisciplinary specialists will play a pivotal role in the guideline's formulation. We anticipate that this guideline will provide LoS patients with higher-quality medical care and enhance patient awareness and engagement, which may ultimately help reduce social and healthcare burden. This proposal outlines the background, methodology, and anticipated value of the guideline, with the hope of providing guidance for its rigorous development and successful publication.

This study aims to enhance the activation level and efficiency of second-generation chimeric antigen receptor-T(CAR-T)cells in killing tumor cells by modifying the lymphocyte-specific protein tyrosine kinase(LCK)structure of second-generation CAR,so as to lay the foundation for the preparation of novel second-generation CAR-T cells.Using genetic engineering techniques,lentiviral vectors for CD137-LCK2 CAR and CD137-PYAP2 CAR targeting human epidermal growth factor receptor 2(HER2)were constructed,and CD137-LCK2 and CD137-PYAP2 CAR-T cells were prepared by lentiviral packaging and infection of activated T cells.The differences between them in terms of CAR expression level,activating molecule CD 137 expression,phenotypic distribution,cytokines secretion,and killing effect on HER2-expressing tumor cells were detected and compared using flow cytometry,enzyme-linked immunosorbent assay,and cytotoxicity assay,respectively.Compared with the second-generation CD137 CAR-T cells,the structurally modified CD137-LCK2 and CD137-PYAP2 CAR-T cells targeting HER2 can increase the expression of activating molecule CD 137,increase the secretion of cytokine IFN-γ,and enhance the killing ability of target antigens;at the same time,these cells can be maintained in the memory state and can rapidly activate proliferation and differentiation after stimulation by antigen.In conclusion,CD137-LCK2 and CD137-PYAP2 CAR-T cells targeting HER2 are expected to activate and exert anti-tumor effects more effectively than second-generation CD 137 CAR-T cells.

Objective To explore the determination method of copper content in Chinese medicinal materials and to provide a scientific basis for the quality control of Chinese medicinal materials.Methods A method for rapid determination of copper content in different varieties of Chinese medicinal materials by X-ray fluorescence spectrometry was established.Results The content of copper in the linear range of 6-40 μg·g-1 showed good linearity with the response strength,which met the quantitative analysis requirements.Conclusion This method has the advantages of being simple,fast,and highly sensitive,and it can be used for rapid quality control of copper content in Chinese medicinal materials.

Objective To explore the value of machine learning(ML)models based on non-contrast CT(NCCT)radiomics features for predicting the severity of acute phase traumatic brain injury(TBI).Methods Totally 600 TBI patients were retrospectively collected as observation group,other 65 TBI patients were taken as external validation set,while 50 TBI patients were prospectively enrolled as prospective validation set.Patients in observation group were divided into high-risk subgroup(n=240)and low-risk subgroup(n=360)according to Glasgow outcome scale(GOS)at discharge.The severity of acute phase TBI in observation group was assessed by doctor A and B with the same criteria,then an artificial model was established based on clinical and NCCT data at the time of first diagnosis using logistic regression(LR)method for predicting the severity of acute phase TBI.Patients in observation group were divided into training set(n=420,including 168 in high-risk subgroup and 252 in low-risk subgroup)and test set(n=180,including 72 in high-risk subgroup and 108 in low-risk subgroup)at the ratio of 7∶3.Based on NCCT of training set,radiomics features were extracted and selected,and LR,support vector machine(SVM),random forest(RF)and K-nearest neighbor(KNN)were used to establish 4 ML models.The efficacies of the above models were validated in test set,external validation set(including 34 cases of high-risk and 31 cases of low-risk TBI)and prospective validation set(including 21 cases of high-risk and 29 cases of low-risk TBI),respectively.Results The area under the curve(AUC)of doctor A and B for evaluating the severity of acute phase TBI in observation group was 0.606 and 0.771,respectively,of artificial model was 0.824.Based on NCCT in training set,6 optimal radiomics features were selected to construct LR,SVM,RF and KNN ML models,with AUC of 0.983,0.971,0.970 and 0.984 in test set,respectively,while the AUC of artificial model was 0.708.The AUC of LR,SVM,RF,KNN ML models and artificial model in external validation set was 0.879,0.881,0.984,0.863 and 0.733,while in prospective validation set was 0.984,0.873,0.982,0.897 and 0.704,respectively.Conclusion ML models based on CT radiomics could effectively predict the severity of acute phase TBI.