Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.

Objective To study the relationship between serum visfatin, neutrophil-to-lymphocyte ratio (NLR) and disease severity of coronary heart disease (CHD) in elderly patients (≥90 years old). Methods One hundred and two elderly patients (≥90 years old) with CHD who received coronary CT angiography (CTA) were selected from January 2020 to June 2024. In addition, thirty-five elderly patients (≥90 years old) without CHD who underwent coronary CTA during the same period were included in the control group. The CHD patients were divided into mild group, moderate group and severe group by CT-SYNTAX score. The clinical data and levels of serum visfatin and NLR were compared, and the correlation and diagnostic value of the above levels with disease severity of CHD in elderly patients were analyzed. Results Serum visfatin and NLR were manifested as severe group>moderate group>mild group>control group (P<0.05). Pearson correlation analysis found that serum visfatin and NLR were moderately positively correlated with CT-SYNTAX score (r=0.574, 0.482, P<0.001). Receiver operating characteristics (ROC) curve indicated that the area under the curve (AUC) of combination of serum visfatin and NLR in diagnosing severe lesion in elderly patients (≥90 years old) with CHD was 0.882, which was higher than that of visfatin or NLR alone, and its 95%CI was 0.803-0.938. Conclusion There is a certain correlation between serum visfatin, NLR and disease severity of CHD in elderly patients. The combination of the above indicators has a higher predictive value on severe lesion.

Objective To investigate the role and mechanism of the zinc finger protein Kruppel-like transcription factor 9 (KLF9) in the stimulation of type I interferon expression induced by herpes simplex virus type 1 (HSV-1) in macrophages. Methods Agarose Gel electrophoresis, quantitative real-time PCR (qRT-PCR) and western blot analyses were employed to detect the KLF9 relative expression in bone marrow-derived macrophages (BMDMs) from Klf9^-/- (gKO) mice and wild-type (WT) mice. RNA-seq analysis was utilized to identify the potential targeted genes upon HSV-1 stimulation in BMDMs. ELISA was used to measure the potent of IFN-β in the supernatant of BMDMs derived from gKO and WT mice after HSV-1 stimulation. qRT-PCR analysis was employed to further confirm the changes of Ifnb1 and interferon-stimulated gene (ISG) such as interferon-induced protein with tetratricopeptide repeats 1 (Ifit1), interferon-stimulated exonuclease gene 20 (Isg20), cholesterol 25-hydroxylase (Ch25h) and 2'-5' oligoadenylate synthetase-like 1 (Oasl1). Western blot was used to detect the expression of phosphorylated interferon regulatory factor-3 (p-IRF3), IRF3, phosphorylated interferon regulatory factor-7 (p-IRF7), IRF7, phosphorylated nuclear factor-kappa B p65 (p-NF-κB p65) and NF-κB p65. CUT-Tag and ChIP-qPCR assay were utilized to confirm the binding region of KLF9 in Ifnb1. Results The KLF9 expression was significantly decreased in BMDMs from gKO mice compared with that from WT mice. The RNA-seq analysis showed that Klf9 deletion in BMDMs resulted in an impaired type I interferon signaling pathway. The qRT-PCR analysis revealed that Klf9 deletion in BMDMs led to a significant decrease of Ifnb1 and ISG such as Ifit1, Ch25h and Oasl1 except Isg20. Moreover, ELISA revealed that Klf9 knockout in BMDMs resulted in a significant decrease of IFN-β secreted from BMDMs. Mechanistically, KLF9 directly binds to the promoter of Ifnb1. Conclusion KLF9 is essential for macrophages to resist HSV-1 infection.
Animals ; Kruppel-Like Transcription Factors/physiology* ; Interferon-beta/metabolism* ; Macrophages/virology* ; Mice ; Herpesvirus 1, Human/physiology* ; Mice, Knockout ; Signal Transduction ; Mice, Inbred C57BL ; Interferon Regulatory Factor-3/genetics* ; Interferon Regulatory Factor-7/genetics* ; Gene Expression Regulation

OBJECTIVES: To investigate the effect of a variety of kidney-tonifying Chinese medicines on thymus regeneration after acute degeneration in mice. METHODS: Forty-eight 8-week-old male BALB/c mice were randomly divided into normal control group, model control group, negative control group, positive control group, the fructus of Cnidium monnieri (L.) Cuss. group, the fructus of Psoralea corylifolia (L.) group, the fructus of Rubus chingii Hu group, and the tuber onion seed group, with 6 mice in each group. Except for the normal control group, mice in the other groups received intraperitoneal injections of rapamycin (1 mg·kg^－1·d^－1) for 5 consecutive days followed by 14 h of starvation to induce acute thymus degeneration. After successful modeling, in treatment groups ethanol extract of the fructus of Cnidium monnieri (L.) Cuss. (0.78 g·kg^－1·d^－1), fructus of Psoralea corylifolia (L.) (0.39 g·kg^－1·d^－1), fructus of Rubus chingii Hu (0.78 g·kg^－1·d^－1) or the tuber onion seed(0.39 g·kg^－1·d^－1) was intraperitoneally injected once a day for 5 days; while the negative control group was given equal volume of normal saline, and the positive control group was given metformin (300 mg·kg^－1·d^－1). The grip strength was measured with a grip tester 2 h after the last administration. The pathological changes of thymus were observed by hematoxylin and eosin (HE) staining. The structure and distribution of thymic epithelial cells were observed by multiple immunofluorescence method. The proportion of T cell subsets in thymus and peripheral blood was analyzed by flow cytometry. The level of T cell receptor excision circles (TREC) in the genomic DNA of mouse spleen mononuclear cells was detected by quantitative polymerase chain reaction (PCR) for evaluation of thymic output function. The expression of thymus aging- and function-related factors in the thymus tissue were detected by quantitative reverse transcription PCR. The expression of cyclin-dependent kinase inhibitor 1A (p21) and tumor protein 53 (p53) were verified by immunohistochemistry. RESULTS: Rapamycin induced thymic atrophy and significantly reduced limb grip strength in mice (P<0.01). Compared with the negative control group, the limb grip strength of mice in the fructus of Psoralea corylifolia (L.) group, the fructus of Rubus chingii Hu group and the tuber onion seed group was significantly enhanced (all P<0.05), and the level of TREC in spleen of the mice in each administration group was reduced (all P<0.05). Among Chinese herb medicine-treatment groups, the recovery of thymus function and tissue structure in the tuber onion seed group was most obvious. Further study showed that compared with the negative control group, the proportion of CD4 single positive cells (CD3⁺TCR-β⁺CD4⁺CD8^－) in the thymus of the tuber onion seed group was significantly increased (P<0.01), and the proportion of CD3⁺CD28⁺ T cell and CD3⁺CD8⁺CD28⁺ T cell in peripheral blood was significantly increased (all P<0.01). The mRNA levels of IL-1α, IL-6, p21 and p53 in thymocytes were decreased (all P<0.05). The results of immunohistochemistry further confirmed the decrease in p21 and p53 expression. In normal mice, tuber onion seed was observed to enhance limb grip strength (P<0.01), while suppressing thymus output and change the distribution of T cell subsets, and there was no significant effect on thymus weight and the expression of Foxn1, SIRT1, p21, CXCL2 and PTMα. CONCLUSIONS The tuber onion seed and other kidney-tonifying traditional Chinese medicines can accelerate the regeneration process of mouse thymus after acute degeneration induced by rapamycin in mice, and the tuber onion seed exhibits the most pronounced therapeutic effect.
Animals ; Mice ; Male ; Mice, Inbred BALB C ; Thymus Gland/physiology* ; Drugs, Chinese Herbal/pharmacology* ; Sirolimus/adverse effects* ; Regeneration/drug effects*

Within the prefrontal-cingulate cortex, abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions, contributing to the development of mental disorders such as depression. Despite this understanding, the neural circuit mechanisms underlying this phenomenon remain elusive. In this study, we present a biophysical computational model encompassing three crucial regions, including the dorsolateral prefrontal cortex, subgenual anterior cingulate cortex, and ventromedial prefrontal cortex. The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes. The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks. Furthermore, our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex, and network functionality was restored through intervention in the dorsolateral prefrontal cortex. This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
Prefrontal Cortex/physiology* ; Humans ; Emotions/physiology* ; Cognition/physiology* ; Gyrus Cinguli/physiology* ; Computer Simulation ; Models, Neurological ; Neural Pathways/physiology* ; Nerve Net/physiology*

Objective:To investigate the therapeutic efficacy of autologous hematopoietic stem cell transplantation (auto-HSCT) for treatment of diffuse large B-cell lymphoma (DLBCL) and the factors affecting the prognosis.Methods:A retrospective case series study was conducted. The clinical data of 51 patients with DLBCL who underwent auto-HSCT in the First Affiliated Hospital of Xinjiang Medical University from March 2019 to January 2024 were retrospectively analyzed. Patients were divided into high-risk group (19 cases) and non-high-risk group (low-risk, low-moderate-risk and moderate-high-risk groups, 32 cases) based on different risk stratifications; patients were divided into the germinal center B-cell (GCB) group (29 cases) and non-GCB group (22 cases) based on different cellular origins; patients were divided into BEAM group (39 cases) and BeEAM group (12 cases) based on different conditioning regimens before auto-HSCT; patients were divided into auto-HSCT consolidation therapy group (41 cases) and auto-HSCT after relapsed/refractory group (10 cases) based on different transplantation timings. The Kaplan-Meier method was used for survival analysis and log-rank was used for subgroup comparison.Results:All 51 patients achieved the hematopoietic reconstitution with no transplantation-related death within 100 d. Before auto-HSCT, 39 cases achieved complete remission and 12 cases (23.5%) achieved partial remission. After auto-HSCT, all cases achieved complete remission. Follow-up was until May 31, 2024, and the median follow-up time [ M ( Q1, Q3)] of 51 DLBCL patients was 33 (8, 43) months. After 51 DLBCL patients receiving auto-HSCT, 7 patients relapsed and 6 cases died including 3 cases with relapse-related death and 3 cases with non relapse-related death. The 3-year progression-free survival (PFS) and overall survival (OS) rates were 78.5% (95% CI: 64.4%-92.6%) and 85.5% (95% CI: 73.2%-97.8%), respectively. The 3-year PFS rate was 94.7% (95% CI: 84.7%-104.7%) in the high-risk group, 82.2% (95% CI: 67.9%-96.5%) in the non-high-risk group, and the difference in the PFS was not statistically significant between the high-risk group and the non-high-risk group ( P = 0.158). The 3-year PFS rate was 80.1% (95% CI: 64.4%-95.8%) in the GCB group, 88.1% (95% CI: 72.3%-104.2%) in the non-GCB group, and the difference in PFS was not statistically significant between the 2 groups ( P = 0.803). The 3-year PFS rate was 84.9% (95% CI: 72.6%-97.2%) in BEAM group, 61.1% (95% CI: 25.0%-97.2%) in the BeEAM group, and the difference in PFS was not statistically significant between the 2 groups ( P = 0.106). The 3-year PFS rate was 85.4% (95% CI: 73.4%-97.4%) in the auto-HSCT consolidation therapy group, 64.3% (95% CI: 31.4%-96.4%) in the auto-HSCT after relapsed/refractory group, and the difference in PFS was not statistically significant between the 2 groups ( P = 0.171). Conclusions:auto-HSCT is an effective therapy method for DLBCL.

Objective:To investigate the efficacy and safety of venetoclax and azacitidine combined with GHA (human granulocyte colony stimulating factor, homoharringtonine and low-dose cytarabine) priming regimen in treatment of patients with relapsed/refractory acute myeloid leukemia.Methods:A retrospective case series study was conducted. Twenty-three patients with relapsed/refractory acute myeloid leukemia (non-acute promyelocytic leukemia) who received treatment with the combination of venetoclax and azacitidine with GHA priming regimen at the Second Affiliated Hospital of Xi'an Jiaotong University from October 2020 to July 2024 were selected, and the treatment efficacy, minimal residual disease (MRD)-negative rate in patients with comprehensive complete remission (cCR) (including complete remission, complete remission with partial hematologic recovery and complete remission with incomplete hematologic recovery) and the adverse reactions were analyzed; patients were followed-up, and their overall survival (OS) was analyzed by using Kaplan-Meier method.Results:The median age of the 23 patients was 60 years (range: 21-79 years), including 10 males and 13 females. The cCR rate for 1 course of treatment was 52.2% (12/23), with 4 cases of MRD negative among cCR patients; 5 cases received 2 courses of treatment, with 3 cases achieving cCR, of which 2 cases were MRD negative; 2 cases received 3 courses of treatment, with 1 case achieving complete remission with incomplete hematologic recovery. Six patients underwent allogeneic hematopoietic stem cell transplantation. The patients were followed up until July 31, 2024, and the median follow-up period was 5.3 months (range: 1.1-41.7 months). Ten cases survived, 12 cases died, 1 case was lost to follow-up, and the median OS time of 23 patients was 7.9 months. The 6-month OS rate was 60.2% (95% CI: 42.7%-84.8%), and the 12-month OS rate was 44.6% (95% CI: 26.8%-74.3%). Common adverse reactions during treatment included infection [69.6% (16/23)], nausea [56.5% (13/23)], febrile neutropenia [52.2% (12/23)], bleeding [52.2% (12/23)], vomiting [34.8% (8/23)], and pneumonia [34.8% (8/23)]. Conclusions:The combination of vinaclotide and azacitidine with GHA priming regimen has certain efficacy and good safety in the treatment of relapsed/refractory acute myeloid leukemia.