Background/Aims: Transmembrane 4 L six family member 1 (TM4SF1) is highly expressed and contributes to the progression of various malignancies. However, how it modulates hepatocellular carcinoma (HCC) progression and senescence remains to be elucidated. Methods: TM4SF1 expression in HCC samples was evaluated using immunohistochemistry and flow cytometry. Cellular senescence was assessed through SA-β-gal activity assays and Western blot analysis. TM4SF1-related protein interactions were investigated using immunoprecipitation-mass spectrometry, co-immunoprecipitation, bimolecular fluorescence complementation, and immunofluorescence. Tumor-infiltrating immune cells were analyzed by flow cytometry. The HCC mouse model was established via hydrodynamic tail vein injection. Results: TM4SF1 was highly expressed in human HCC samples and murine models. Knockdown of TM4SF1 suppressed HCC proliferation both in vitro and in vivo, inducing non-secretory senescence through upregulation of p16 and p21. TM4SF1 enhanced the interaction between AKT1 and PDPK1, thereby promoting AKT phosphorylation, which subsequently downregulated p16 and p21. Meanwhile, TM4SF1-mediated AKT phosphorylation enhanced PD-L1 expression while reducing major histocompatibility complex class I level on tumor cells, leading to impaired cytotoxic function of CD8+ T cells and an increased proportion of exhausted CD8+ T cells. In clinical HCC samples, elevated TM4SF1 expression was associated with resistance to anti-PD-1 immunotherapy. Targeting TM4SF1 via adeno-associated virus induced tumor senescence, reduced tumor burden and synergistically enhanced the efficacy of anti-PD-1 therapy. Conclusions Our results revealed that TM4SF1 regulated tumor cell senescence and immune evasion through the AKT pathway, highlighting its potential as a therapeutic target in HCC, particularly in combination with first-line immunotherapy.

Background/Aims: Transmembrane 4 L six family member 1 (TM4SF1) is highly expressed and contributes to the progression of various malignancies. However, how it modulates hepatocellular carcinoma (HCC) progression and senescence remains to be elucidated. Methods: TM4SF1 expression in HCC samples was evaluated using immunohistochemistry and flow cytometry. Cellular senescence was assessed through SA-β-gal activity assays and Western blot analysis. TM4SF1-related protein interactions were investigated using immunoprecipitation-mass spectrometry, co-immunoprecipitation, bimolecular fluorescence complementation, and immunofluorescence. Tumor-infiltrating immune cells were analyzed by flow cytometry. The HCC mouse model was established via hydrodynamic tail vein injection. Results: TM4SF1 was highly expressed in human HCC samples and murine models. Knockdown of TM4SF1 suppressed HCC proliferation both in vitro and in vivo, inducing non-secretory senescence through upregulation of p16 and p21. TM4SF1 enhanced the interaction between AKT1 and PDPK1, thereby promoting AKT phosphorylation, which subsequently downregulated p16 and p21. Meanwhile, TM4SF1-mediated AKT phosphorylation enhanced PD-L1 expression while reducing major histocompatibility complex class I level on tumor cells, leading to impaired cytotoxic function of CD8+ T cells and an increased proportion of exhausted CD8+ T cells. In clinical HCC samples, elevated TM4SF1 expression was associated with resistance to anti-PD-1 immunotherapy. Targeting TM4SF1 via adeno-associated virus induced tumor senescence, reduced tumor burden and synergistically enhanced the efficacy of anti-PD-1 therapy. Conclusions Our results revealed that TM4SF1 regulated tumor cell senescence and immune evasion through the AKT pathway, highlighting its potential as a therapeutic target in HCC, particularly in combination with first-line immunotherapy.

Background/Aims: Transmembrane 4 L six family member 1 (TM4SF1) is highly expressed and contributes to the progression of various malignancies. However, how it modulates hepatocellular carcinoma (HCC) progression and senescence remains to be elucidated. Methods: TM4SF1 expression in HCC samples was evaluated using immunohistochemistry and flow cytometry. Cellular senescence was assessed through SA-β-gal activity assays and Western blot analysis. TM4SF1-related protein interactions were investigated using immunoprecipitation-mass spectrometry, co-immunoprecipitation, bimolecular fluorescence complementation, and immunofluorescence. Tumor-infiltrating immune cells were analyzed by flow cytometry. The HCC mouse model was established via hydrodynamic tail vein injection. Results: TM4SF1 was highly expressed in human HCC samples and murine models. Knockdown of TM4SF1 suppressed HCC proliferation both in vitro and in vivo, inducing non-secretory senescence through upregulation of p16 and p21. TM4SF1 enhanced the interaction between AKT1 and PDPK1, thereby promoting AKT phosphorylation, which subsequently downregulated p16 and p21. Meanwhile, TM4SF1-mediated AKT phosphorylation enhanced PD-L1 expression while reducing major histocompatibility complex class I level on tumor cells, leading to impaired cytotoxic function of CD8+ T cells and an increased proportion of exhausted CD8+ T cells. In clinical HCC samples, elevated TM4SF1 expression was associated with resistance to anti-PD-1 immunotherapy. Targeting TM4SF1 via adeno-associated virus induced tumor senescence, reduced tumor burden and synergistically enhanced the efficacy of anti-PD-1 therapy. Conclusions Our results revealed that TM4SF1 regulated tumor cell senescence and immune evasion through the AKT pathway, highlighting its potential as a therapeutic target in HCC, particularly in combination with first-line immunotherapy.

OBJECTIVE To optimize the prescription pre-review system in our hospital and evaluate its application effects. METHODS Aiming at the problems of imperfect rule base and high false positive rate in the early operation of the system， optimization measures were taken， including improving the content of the rule base， adjusting the interception level and prompt mode， refining the working model of prescription review pharmacists， and strengthening clinical communication. A retrospective cohort study was conducted， with prescription data from June to December 2023 （before optimization） as the control group and June to December 2024 （after optimization） as the observation group. Through inter group comparative analysis， the actual effect of optimizing the prescription pre-approval system was evaluated. RESULTS The prescription qualified rate increased from （82.51± 4.04）% before optimization to （90.98±1.55）% after optimization； the false positive rate decreased from （20.87±1.64）% before optimization to （7.41±2.04）% after optimization. The monthly range of prescription qualified rate narrowed from 10.24% to 4.11%， and the coefficient of variation decreased from 4.92% to 1.73%. The monthly range of false positive rate slightly increased from 4.40% to 5.34%， the coefficient of variation rose from 8.32% to 26.18%. CONCLUSIONS Through multi-dimensional optimizations of the prescription pre-review system in our hospital， its prescription review efficiency has been significantly enhanced， the quality of prescriptions has steadily improved， and the accuracy of reviews has notably improved.

Objective:To investigate the current situation and organizational management policies of government procurement in public hospitals,and to improve the level of standardized management of government procurement.Methods:An electronic questionnaire survey was conducted to investigate the current status of organization and administration of government procurement in different types and levels of public hospitals across the country.The current situation of the organizational structure,management system,working mode,supervision and evaluation,budget establishment,bidding and procurement,contract signing,acceptance process,payment management,and other aspects of government procurement management in public hospitals were analyzed.Results:A total of 216 valid questionnaires were collected from 216 public hospitals in 28 provinces,municipalities and autonomous regions across the country,including 165 general hospitals,37 specialized hospitals and 13 traditional Chinese medicine hospitals,accounting for 76.39％,17.13％and 6.02％respectively;among the hospital levels,there were 202 tertiary hospitals(accounting for 93.52％).Among the surveyed government procurement management institutions of public hospitals,there were 112,103,110 and 112 organizations at the four levels of procurement management committee,procurement management office,procurement center and business and administrative logistics department,accounting for 51.85％,47.69％,50.93％and 51.85％respectively.The quota standards for public bidding for government procurement in all hospitals were in line with the requirements of national laws and regulations.The approval of funds payment must conditions of each hospital complied with relevant requirements.In terms of management effects of risk prevention and control,the hospitals with very good,good,average and inadequate were 48,125,34 and 9 respectively,accounting for 22.22％,57.87％,15.74％and 4.17％.Conclusion:The organizational framework and management system of government procurement in public hospitals are becoming increasingly standardized,and there are certain differences in the work mode and process of government procurement in different hospitals,and the supervision and evaluation are relatively weak,which is worthy of attention and strengthened administration.

Objective:To evaluate the value of CT for differentiating gastric leiomyoma (GLM) from gastric schwannoma (GS).Methods:The clinical and imaging data of 42 patients with GLM (GLM group) and 41 patients with GS (GS group) were analyzed retrospectively. The general information and CT features were compared between two groups. The independent factors for differentiating GLM from GS were obtained by multivariate Logistic regression analysis. The receiver operating characteristic curve (ROC) was used to evaluate the diagnostic efficiency of the model.Results:The proportion of female and age in GLM group were significantly lower than those in GS group: 59.52% (25/42) vs. 85.37% (35/41), (51.83 ± 10.52) years old vs. (58.80 ± 10.63) years old, and there were statistical differences ( P<0.01). The upper part of the stomach rate, irregular shape rate, intraluminal growth rate, ratio of long diameter to short diameter and mild to moderate enhancement rate in GLM group were significantly higher than those in GS group: 71.43% (30/42) vs. 14.63% (6/41), 52.38% (22/42) vs. 21.95% (9/41), 92.86% (39/42) vs. 19.51% (8/41), 1.90 ± 0.55 vs. 1.34 ± 0.28 and 92.86% (39/42) vs. 51.22% (21/41), the cystic degeneration rate, ulcer rate, incidence of tumor-associated lymph node, CT values of venous phase and delayed phase in GLM group were significantly lower than those in GS group: 2.38% (1/42) vs. 26.83% (11/41), 7.14% (3/42) vs. 24.39% (10/41), 2.38% (1/42) vs. 60.98% (25/41), (59.21 ± 9.75) HU vs. (66.22 ± 10.33) HU and (65.02 ± 8.62) HU vs. (76.85 ± 11.89) HU, and there were statistical differences ( P<0.01 or <0.05); there were no statistical difference in the rate of calcification and the CT values of plain scan and arterial phase between the two groups ( P>0.05). Multivariate Logistic regression analysis result showed that the tumor location, growth mode, tumor-associated lymph node and ratio of long diameter to short diameter were the independent factors for differentiating GLM from GS ( OR = 34.385, 25.314, 0.023 and 97.700; 95% CI 2.848 to 415.171, 2.674 to 239.670, 0.001 to 0.637 and 3.113 to 3 066.549; P<0.01 or <0.05); when the model threshold was >0.647, the area under the curve was 0.988 (95% CI 0.934 to 1.000), with a sensitivity of 92.9% and specificity of 97.6%. Conclusions:When the tumor is prone to the upper part of the stomach, intraluminal growth, ratio of long diameter to short diameter >1.28, and the absence of the tumor-associated lymph node, GLM tends to be considered, on the contrary, it tends to be GS. Therefore, CT imaging features have certain value in differentiating GLM from GS before surgery.

BACKGROUND: Pneumonia-like primary pulmonary lymphoma (PPL) was commonly misdiagnosed as infectious pneumonia, leading to delayed treatment. The purpose of this study was to establish a computed tomography (CT)-based radiomics model to differentiate pneumonia-like PPL from infectious pneumonia. METHODS: In this retrospective study, 79 patients with pneumonia-like PPL and 176 patients with infectious pneumonia from 12 medical centers were enrolled. Patients from center 1 to center 7 were assigned to the training or validation cohort, and the remaining patients from other centers were used as the external test cohort. Radiomics features were extracted from CT images. A three-step procedure was applied for radiomics feature selection and radiomics signature building, including the inter- and intra-class correlation coefficients (ICCs), a one-way analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO). Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and construct a clinical factor model. Two radiologists reviewed the CT images for the external test set. Performance of the radiomics model, clinical factor model, and each radiologist were assessed by receiver operating characteristic, and area under the curve (AUC) was compared. RESULTS: A total of 144 patients (44 with pneumonia-like PPL and 100 infectious pneumonia) were in the training cohort, 38 patients (12 with pneumonia-like PPL and 26 infectious pneumonia) were in the validation cohort, and 73 patients (23 with pneumonia-like PPL and 50 infectious pneumonia) were in the external test cohort. Twenty-three radiomics features were selected to build the radiomics model, which yielded AUCs of 0.95 (95% confidence interval [CI]: 0.94-0.99), 0.93 (95% CI: 0.85-0.98), and 0.94 (95% CI: 0.87-0.99) in the training, validation, and external test cohort, respectively. The AUCs for the two readers and clinical factor model were 0.74 (95% CI: 0.63-0.83), 0.72 (95% CI: 0.62-0.82), and 0.73 (95% CI: 0.62-0.84) in the external test cohort, respectively. The radiomics model outperformed both the readers' interpretation and clinical factor model ( P <0.05). CONCLUSIONS The CT-based radiomics model may provide an effective and non-invasive tool to differentiate pneumonia-like PPL from infectious pneumonia, which might provide assistance for clinicians in tailoring precise therapy.
Humans ; Retrospective Studies ; Pneumonia/diagnostic imaging* ; Analysis of Variance ; Tomography, X-Ray Computed ; Lymphoma/diagnostic imaging*