Objective To investigate the effect of remote ischemic postconditioning （RIPostC） on the serum levels of matrix metallopeptidase-9 （MMP-9）， hypoxia-inducible factor 1α （HIF-1α）， and interleukin-1β （IL-1β） in patients with acute ischemic stroke （AIS）， and to further clarify the mechanism and clinical significance of RIPostC in the treatment of AIS. Methods A total of 115 AIS patients who were admitted to Suzhou First People’s Hospital from May 2024 to February 2025 were enrolled， among whom 60 patients receiving conventional treatment were enrolled as control group， and 55 patients receiving RIPostC combined with conventional treatment for 7 consecutive days were enrolled as experimental group. ELISA was used to measure the serum levels of MMP-9， HIF-1α， and IL-1β， and National Institutes of Health Stroke Scale （NIHSS） was used to assess neurological function. Results After treatment， the experimental group had a significant increase in the level of HIF-1α （P<0.001） and significant reductions in the levels of MMP-9 and IL-1β （P<0.001）. The experimental group had a significantly better NIHSS score than the control group （P<0.001）. The increase in the serum level of HIF-1α could promote neurological function recovery. Conclusion RIPostC combined with conventional treatment can promote early neurological recovery in AIS patients， possibly by regulating the HIF-1α signaling pathway.

OBJECTIVES: The application of photodynamic therapy in solid tumors has attracted increasing attention in recent years, and the efficiency of photosensitizers is a crucial determinant of therapeutic efficacy. This study aims to evaluate the cytotoxic effects of a novel photosensitizer, PEG-MTPABZ-PyC, in photodynamic therapy against gastric cancer cells. METHODS: Gastric cancer MKN45 cells were treated with PEG-MTPABZ-PyC. A high-content live-cell imaging system was used to assess the cellular uptake kinetics and subcellular localization of the photosensitizer. The cytotoxic effects of PEG-MTPABZ-PyC-mediated photodynamic therapy were examined using the cell counting kit-8 (CCK-8) assay and flow cytometry, while the intrinsic cytotoxicity of the photosensitizer alone was verified by the CCK-8 assay. Intracellular reactive oxygen species (ROS) generation after photodynamic therapy was detected using 2'-7'-dichlorodihydrofluorescein diacetate (DCFH-DA). RESULTS: PEG-MTPABZ-PyC alone exhibited no cytotoxicity toward MKN45 cells, indicating excellent cytocompatibility. The compound efficiently entered cells within 6 hours and localized predominantly in lysosomes. Upon light irradiation, PEG-MTPABZ-PyC-mediated photodynamic therapy induced significant cytotoxicity compared with the control group (P<0.05) and generated abundant intracellular ROS. CONCLUSIONS The novel photosensitizer PEG-MTPABZ-PyC demonstrates potent photodynamic cytotoxicity against gastric cancer cells, showing promising potential for further development in gastric cancer photodynamic therapy.
Humans ; Stomach Neoplasms/drug therapy* ; Photochemotherapy/methods* ; Photosensitizing Agents/pharmacology* ; Cell Line, Tumor ; Polyethylene Glycols/chemistry* ; Reactive Oxygen Species/metabolism* ; Mesoporphyrins/pharmacology*

Objective:This study aims to develop a rapid identification technique for various genotypes of extended-spectrum β-lactamase (ESBL) producing Escherichia coli using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in conjunction with machine learning algorithms. Methods:A total of 158 Escherichia coli strains were isolated from the clinical laboratory of the First Hospital of Jilin University from August 2018 to December 2022. Polymerase chain reaction (PCR) was employed to detect the CTX-M-1, CTX-M-8, CTX-M-9, and SHV genes. Mass spectral data of the bacterial strains were acquired by MALDI-TOF MS with a cooperative matrix of (E)-propyl α-cyano-4-hydroxycinnamate (CHCA-C3). Models based on random forest (RF), logistic regression (LR), and support vector machine (SVM) algorithms were constructed. The performance of the constructed models was evaluated using metrics including accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Mass spectral peaks exhibiting sensitivity and specificity exceeding 80% in the models were designated as characteristic peaks. To validate the efficacy of the cooperative matrix of CHCA-C3, clinical isolates of ESBL-producing Escherichia coli were analyzed by MALDI-TOF MS using the conventional CHCA matrix for comparative purposes. Results:Among the 158 strains of Escherichia coli, 91 strains produced ESBL, all of which were CTX-M genotype. The AUC values for the respective models were as follows: CTX-M-1 genotype exhibited AUC values of 0.98 for LR, 1.00 for RF, and 0.73 for SVM; CTX-M-9 genotype exhibited AUC values of 0.93 for LR, 0.99 for RF, and 0.76 for SVM; for CTX-M-8, all models achieved an AUC of 1.00, indicating excellent classification performance with respect to accuracy, specificity, and sensitivity. The characteristic mass spectral peaks associated with each genotype included: CTX-M-1 genotype at m/z 6 390; CTX-M-8 genotype at m/z 5 224, m/z 5 393, and m/z 9 021; CTX-M-9 genotype at m/z 5 161 and m/z 5 273. In the MALDI-TOF MS analysis conducted with the conventional CHCA matrix, the characteristic peak at m/z 9 021 for CTX-M-8 was the only one detected, with the characteristic peaks for CTX-M-1 and CTX-M-9 remaining undetected. Conclusion:The application of cooperative matrix of CHCA-C3 in conjunction with MALDI-TOF MS and machine learning algorithms facilitates the rapid and precise identification of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli. This approach offers a feasible solution for evidence-based clinical therapy and the control of healthcare-associated infections.

The Split-Cre system consists of two inactive polypeptides: NCre and CCre, which can be recombined into an active full-length Cre under certain conditions. This system is typically used with LoxP. To develop an efficient Split-Cre system, this study used Rma intein from Rhodothermus marinus to split Cre and screened out the split site S102 which could efficiently mediate the recombination of Cre in the "Traffic Light" reporter cell line. Moreover, the S102 Split-Cre system was delivered to mice by dual-adeno-associated virus (AAV), and it was demonstrated that the efficiency of the Rma intein-mediated S102 Split-Cre system was comparable to the full-length Cre in mice. This system lays a foundation for both basic and applied research on Split-Cre.
Inteins/genetics* ; Animals ; Integrases/biosynthesis* ; Mice ; Dependovirus/metabolism* ; Bacterial Proteins/genetics* ; Recombination, Genetic ; Humans

Objective:To analyze the incidence and influencing factors of lymphopenia in prostate cancer patients undergoing pelvic radiotherapy.Methods:A retrospective analysis was conducted on 123 prostate cancer patients treated at the Department of Radiation Oncology, Peking University First Hospital, from November 2011 to May 2015. Radiotherapy was administered using conventional fractionated intensity-modulated radiotherapy. Blood routine, including absolute lymphocyte count (ALC), was performed on patients before radiotherapy, weekly during radiotherapy, and at the end of radiotherapy. Severe lymphopenia was defined as an ALC <500 cells/μl. Based on whether the minimum ALC during radiotherapy was lower than 500 cells/μl, the entire cohort and 55 patients (excluding those with undelineated pelvic bone marrow due to radiotherapy planning system issues) with delineated pelvic bone marrow (divided into pelvic bone marrow, iliac bone marrow, and lower pelvic bone marrow) were stratified into a severe lymphopenia group (33 cases and 16 cases, respectively) and a mild lymphopenia group (90 cases and 39 cases, respectively). Differences in clinical factors and dosimetric parameters were compared between the groups using the chi-square test (or Fisher's exact test), t-test, and Wilcoxon rank-sum test. Univariate and multivariate logistic regression analyses were performed to identify the clinical and dosimetric factors influencing severe lymphopenia. Results:All 123 prostate cancer patients experienced lymphopenia during radiotherapy, with a median minimum ALC of 0.6×10 9/L [range: (0.2-2.3)×10 9/L]. Severe lymphopenia occurred in 26.8% (33 cases) of patients. Univariate analysis of the entire cohort showed that pre-radiotherapy baseline ALC, initial neutrophil-to-lymphocyte ratio, prostate-specific antigen value, Gleason score, and pelvic radiotherapy were promoting factors for severe lymphopenia ( P<0.05). Multivariate analysis identified pre-radiotherapy baseline ALC ( OR=0.217, 95% CI: 0.072-0.650, P=0.006) and pelvic radiotherapy ( OR=23.852, 95% CI: 2.834-200.787, P=0.004) as promoting factors for severe lymphopenia. In patients with delineated pelvic bone marrow, univariate analysis showed that pelvic bone marrow V 30 Gy and V 40 Gy, iliac bone marrow V 30 Gy and V 40 Gy, lower pelvic bone marrow V 30 Gy and V 40 Gy were promoting factors for severe lymphopenia during treatment ( P<0.05). Conclusions:Lymphopenia is common in prostate cancer patients undergoing radiotherapy, with a high incidence of severe lymphopenia. Pre-radiotherapy baseline ALC, as well as pelvic, iliac, and lower pelvic bone marrow V 30 Gy and V 40 Gy, are promoting factors for severe lymphopenia during radiotherapy.

Objective To predict potential quality markers(Q-Markers)of Gastrodia elata using fingerprinting,chemical pattern recognition and network pharmacology methods.Methods A total of 46 batches of Gastrodia elata were analyzed using high-performance liquid chromatography(HPLC)to establish fingerprint profiles,and common peaks were identified.Systematic cluster analysis(HCA),principal component analysis(PCA),and orthogonal partial least squares discriminant analysis(OPLS-DA)were employed to evaluate the 46 batches of samples.Additionally,The network diagram of"components-targets-pathways"was constructed using network pharmacology.Q-Marker of Gastrodia elata was predicted and quantitative analysis was conducted simultaneously.Results Seven substances were identified among the 13 common peaks in the fingerprint profiles.Results from HCA,PCA,and OPLS-DA were consistent,while network pharmacology identified 17 core active ingredients,86 core targets,and 181 key pathways.Integrating fingerprinting and network pharmacology,Gastrodin,p-hydroxybenzyl alcohol,parishin A,parishin B,parishin C,and parishin E were selected as potential Q-Markers of Gastrodia elata.The total contents of GAS and HBA alcohol in 46 batches of Gastrodia gastrodia decoction pieces ranged from 0.17%to 2.08%.Conclusion Integration of fingerprinting and network pharmacology analyses predicted potential Q-Markers of Gastrodia elata,and providing a scientific basis for comprehensive quality control and evaluation.

Objective To predict potential quality markers(Q-Markers)of Gastrodia elata using fingerprinting,chemical pattern recognition and network pharmacology methods.Methods A total of 46 batches of Gastrodia elata were analyzed using high-performance liquid chromatography(HPLC)to establish fingerprint profiles,and common peaks were identified.Systematic cluster analysis(HCA),principal component analysis(PCA),and orthogonal partial least squares discriminant analysis(OPLS-DA)were employed to evaluate the 46 batches of samples.Additionally,The network diagram of"components-targets-pathways"was constructed using network pharmacology.Q-Marker of Gastrodia elata was predicted and quantitative analysis was conducted simultaneously.Results Seven substances were identified among the 13 common peaks in the fingerprint profiles.Results from HCA,PCA,and OPLS-DA were consistent,while network pharmacology identified 17 core active ingredients,86 core targets,and 181 key pathways.Integrating fingerprinting and network pharmacology,Gastrodin,p-hydroxybenzyl alcohol,parishin A,parishin B,parishin C,and parishin E were selected as potential Q-Markers of Gastrodia elata.The total contents of GAS and HBA alcohol in 46 batches of Gastrodia gastrodia decoction pieces ranged from 0.17%to 2.08%.Conclusion Integration of fingerprinting and network pharmacology analyses predicted potential Q-Markers of Gastrodia elata,and providing a scientific basis for comprehensive quality control and evaluation.

Objective:This study aims to develop a rapid identification technique for various genotypes of extended-spectrum β-lactamase (ESBL) producing Escherichia coli using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in conjunction with machine learning algorithms. Methods:A total of 158 Escherichia coli strains were isolated from the clinical laboratory of the First Hospital of Jilin University from August 2018 to December 2022. Polymerase chain reaction (PCR) was employed to detect the CTX-M-1, CTX-M-8, CTX-M-9, and SHV genes. Mass spectral data of the bacterial strains were acquired by MALDI-TOF MS with a cooperative matrix of (E)-propyl α-cyano-4-hydroxycinnamate (CHCA-C3). Models based on random forest (RF), logistic regression (LR), and support vector machine (SVM) algorithms were constructed. The performance of the constructed models was evaluated using metrics including accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Mass spectral peaks exhibiting sensitivity and specificity exceeding 80% in the models were designated as characteristic peaks. To validate the efficacy of the cooperative matrix of CHCA-C3, clinical isolates of ESBL-producing Escherichia coli were analyzed by MALDI-TOF MS using the conventional CHCA matrix for comparative purposes. Results:Among the 158 strains of Escherichia coli, 91 strains produced ESBL, all of which were CTX-M genotype. The AUC values for the respective models were as follows: CTX-M-1 genotype exhibited AUC values of 0.98 for LR, 1.00 for RF, and 0.73 for SVM; CTX-M-9 genotype exhibited AUC values of 0.93 for LR, 0.99 for RF, and 0.76 for SVM; for CTX-M-8, all models achieved an AUC of 1.00, indicating excellent classification performance with respect to accuracy, specificity, and sensitivity. The characteristic mass spectral peaks associated with each genotype included: CTX-M-1 genotype at m/z 6 390; CTX-M-8 genotype at m/z 5 224, m/z 5 393, and m/z 9 021; CTX-M-9 genotype at m/z 5 161 and m/z 5 273. In the MALDI-TOF MS analysis conducted with the conventional CHCA matrix, the characteristic peak at m/z 9 021 for CTX-M-8 was the only one detected, with the characteristic peaks for CTX-M-1 and CTX-M-9 remaining undetected. Conclusion:The application of cooperative matrix of CHCA-C3 in conjunction with MALDI-TOF MS and machine learning algorithms facilitates the rapid and precise identification of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli. This approach offers a feasible solution for evidence-based clinical therapy and the control of healthcare-associated infections.

Objective:To analyze the incidence and influencing factors of lymphopenia in prostate cancer patients undergoing pelvic radiotherapy.Methods:A retrospective analysis was conducted on 123 prostate cancer patients treated at the Department of Radiation Oncology, Peking University First Hospital, from November 2011 to May 2015. Radiotherapy was administered using conventional fractionated intensity-modulated radiotherapy. Blood routine, including absolute lymphocyte count (ALC), was performed on patients before radiotherapy, weekly during radiotherapy, and at the end of radiotherapy. Severe lymphopenia was defined as an ALC <500 cells/μl. Based on whether the minimum ALC during radiotherapy was lower than 500 cells/μl, the entire cohort and 55 patients (excluding those with undelineated pelvic bone marrow due to radiotherapy planning system issues) with delineated pelvic bone marrow (divided into pelvic bone marrow, iliac bone marrow, and lower pelvic bone marrow) were stratified into a severe lymphopenia group (33 cases and 16 cases, respectively) and a mild lymphopenia group (90 cases and 39 cases, respectively). Differences in clinical factors and dosimetric parameters were compared between the groups using the chi-square test (or Fisher's exact test), t-test, and Wilcoxon rank-sum test. Univariate and multivariate logistic regression analyses were performed to identify the clinical and dosimetric factors influencing severe lymphopenia. Results:All 123 prostate cancer patients experienced lymphopenia during radiotherapy, with a median minimum ALC of 0.6×10 9/L [range: (0.2-2.3)×10 9/L]. Severe lymphopenia occurred in 26.8% (33 cases) of patients. Univariate analysis of the entire cohort showed that pre-radiotherapy baseline ALC, initial neutrophil-to-lymphocyte ratio, prostate-specific antigen value, Gleason score, and pelvic radiotherapy were promoting factors for severe lymphopenia ( P<0.05). Multivariate analysis identified pre-radiotherapy baseline ALC ( OR=0.217, 95% CI: 0.072-0.650, P=0.006) and pelvic radiotherapy ( OR=23.852, 95% CI: 2.834-200.787, P=0.004) as promoting factors for severe lymphopenia. In patients with delineated pelvic bone marrow, univariate analysis showed that pelvic bone marrow V 30 Gy and V 40 Gy, iliac bone marrow V 30 Gy and V 40 Gy, lower pelvic bone marrow V 30 Gy and V 40 Gy were promoting factors for severe lymphopenia during treatment ( P<0.05). Conclusions:Lymphopenia is common in prostate cancer patients undergoing radiotherapy, with a high incidence of severe lymphopenia. Pre-radiotherapy baseline ALC, as well as pelvic, iliac, and lower pelvic bone marrow V 30 Gy and V 40 Gy, are promoting factors for severe lymphopenia during radiotherapy.