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.

Based on the holistic view of "spleen-vessels-heart-spirit" system， this article explores the pathogenesis and progression of atrial fibrillation. It is proposed that the onset of atrial fibrillation is due to failure of the spleen to transport and disharmony of blood vessels； phlegm and blood stasis obstructing the collaterals and damage to the heart structure are the basis of its pathogenesis； the unclear mind and disorder of body and spirit are the causes of its progression. Based on the characteristics of pathological changes in different stages of the disease， it is proposed that early treatment should focus on restoring the middle jiao， clearing and promoting blood vessels， using modified Yigong Powder （异功散）； during the progression of the disease， treatment should remove blood stasis and phlegm， nourish heart and protect the pulse， using self-prescribed modified Mengshi Tongmai Decoction （礞石通脉汤）； meanwhile， calming mind and stabilizing palpitations， and regulating spirit should be sequentially incorporated， with self-prescribed Jiazao Ningmai Decoction （甲枣宁脉汤） or Shenying Dingji Decoction （参英定悸汤） and modified as appropriate. Clinical treatment should focus on the whole disease course of atrial fibrillation， implementing stage-based treatments to enable early intervention and holistic regulation.

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 analyze the application effects of artificial intelligence (AI) software and Mimics software in preoperative three-dimensional (3D) reconstruction for thoracoscopic anatomical pulmonary segmentectomy. Methods A retrospective analysis was conducted on patients who underwent thoracoscopic pulmonary segmentectomy at the Second People's Hospital of Huai'an from October 2019 to March 2024. Patients who underwent AI 3D reconstruction were included in the AI group, those who underwent Mimics 3D reconstruction were included in the Mimics group, and those who did not undergo 3D reconstruction were included in the control group. Perioperative related indicators of each group were compared. Results A total of 168 patients were included, including 73 males and 95 females, aged 25-81 (61.61±10.55) years. There were 79 patients in the AI group, 53 patients in the Mimics group, and 36 patients in the control group. There were no statistical differences in gender, age, smoking history, nodule size, number of lymph node dissection groups, postoperative pathological results, or postoperative complications among the three groups (P>0.05). There were statistical differences in operation time (P<0.001), extubation time (P<0.001), drainage volume (P<0.001), bleeding volume (P<0.001), and postoperative hospital stay (P=0.001) among the three groups. There were no statistical differences in operation time, extubation time, bleeding volume, or postoperative hospital stay between the AI group and the Mimics group (P>0.05). There was no statistical difference in drainage volume between the AI group and the control group (P=0.494), while there were statistical differences in operation time, drainage tube retention time, bleeding volume, and postoperative hospital stay (P<0.05). Conclusion For patients requiring thoracoscopic anatomical pulmonary segmentectomy, preoperative 3D reconstruction and preoperative planning based on 3D images can shorten the operation time, postoperative extubation time and hospital stay, and reduce intraoperative bleeding and postoperative drainage volume compared with reading CT images only. The use of AI software for 3D reconstruction is not inferior to Mimics manual 3D reconstruction in terms of surgical guidance and postoperative recovery, which can reduce the workload of clinicians and is worth promoting.

Objective To investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. Results A total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. Conclusion Male, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

Pancreatic cancer is a kind of highly malignant tumor with a low survival rate and poor prognosis. The effectiveness of gemcitabine as a first-line chemotherapy drug is limited; however, it can activate dendritic cells and improve antigen presentation which increase the sensitivity of tumor cell to immunotherapy. Although immunotherapy has made some advancements in cancer treatment, the therapeutic benefit of programmed cell death receptor 1/programmed death receptor-ligand 1 (PD-1/PD-L1) blockade therapy remains relatively low. The chemokine C-X-C chemokine ligand 12 (CXCL12) contributes to an immunosuppressive tumor microenvironment by recruiting immunosuppressive cells. The receptor C-X-C motif chemokine receptor 4 (CXCR4), highly expressed in various tumors including pancreatic cancer, plays a crucial role in tumor development and progression. In this study, the anti-tumor immune response of human peripheral blood mononuclear cell (hPBMC) was enhanced using the combination of BsNb PX4 (anti-PD-L1&CXCR4 bispecific nanobody) and gemcitabine. In a co-culture system of gemcitabine-pretreated hPBMCs with tumor cells, the BsNb PX4 synergized gemcitabine to improve the cytotoxic activity of hPBMCs against tumor cells. Flow cytometry analysis confirmed increased ratio of CD8⁺ to CD4⁺ T cells in combination treatment. In NOD/SCID mice bearing pancreatic cancer, the combination treatment exhibited more infiltration of CD8⁺ T cells into tumor tissues, contributing to an effective anti-tumor response. This study presents potential new therapies for the treatment of pancreatic cancer. Ethical approval was obtained for collection of hPBMC samples from the Local Ethics Committee of Shanghai Jiao Tong University. All animal experiments were approved by the Animal Ethic Committee of Shanghai Jiao Tong University (authorizing number: A2024246).

OBJECTIVE To provide medication reference for duloxetine use in clinical settings， particularly for patients with depression in primary medical institutions in Xinjiang that lack therapeutic drug monitoring conditions. METHODS The medical records of 281 depression inpatients taking duloxetine in the First Affiliated Hospital of Xinjiang Medical University from January 2022 to December 2023 were retrospectively collected. They were divided into training set （196 cases） and test set （85 cases） in the ratio of 7∶3. Feature selection was performed by encapsulating random forests （RF） with recursive feature elimination. Four machine learning algorithms， namely support vector machine， RF， extreme gradient boosting （XGBoost） and artificial neural network， were used to construct duloxetine blood concentration prediction model. The prediction performance of the models was evaluated and compared by coefficient of determination （R2）， mean absolute error （MAE） and root mean squared error （RMSE）. The feature of the selected optimal model was explained by Shapley additive explanation method， and the importance ranking of the features and the influence on the prediction results of duloxetine blood concentration were determined. RESULTS A total of 29 characteristic variables were selected， including age， ethnicity， body mass index（BMI）， etc. XGBoost showed the highest R2 （0.808）， and the lowest MAE （7.644） and RMSE （10.808）. The ranking of feature importance for predicting the blood concentration of duloxetine was as follows： BMI＞age＞other 20 feature sets （including liver and kidney function and biochemical indicators）＞daily dosage＞comorbidities＞combination therapy＞ethnicity＞white blood cell count＞hemoglobin＞height. CONCLUSIONS XGBoost model possesses the best prediction performance of duloxetine blood concentration； BMI and age have a greater impact on the prediction of duloxetine blood concentration.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4⁺ T lymphocytes. Additionally, spleen CD4⁺ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4⁺ and CD8⁺ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4⁺ and CD8⁺ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4⁺ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4⁺ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.