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.

AIM: To evaluate clinical efficacy of recombinant human epidermal growth factor(rhEGF)combined with adjuvant amniotic membrane transplantation in corneal alkaline burns. METHODS:In the prospective, randomized controlled study, patients with corneal alkaline burns treated in the hospital were enrolled between November 2022 and November 2024. After emergency treatment, patients were divided into combined treatment group and routine treatment group by random number table method. The routine treatment group was given basic treatment(rhEGF), while combined treatment group additionally underwent adjuvant amniotic membrane transplantation. The clinical efficacy, healing time of corneal epithelium, best corrected visual acuity, VAS scores, corneal neovascularization area, break-up time, score of corneal opacity, and levels of inflammatory factors(IL-6, hs-CRP, TNF-α)in the two groups were observed and compared. RESULTS:There were 110 patients(110 eyes)in this study, including 55 cases(55 eyes)in each group. The combination group had a mean age of 46.82±10.38 y, including 26 males and 29 females. The routine treatment group had a mean age of 45.13±11.57 y, with 31 males and 24 females. The total response rate of combined treatment group [94.5%(52/55)] was significantly higher than that of routine treatment group [81.8%(45/55), P<0.05]. The healing time of corneal epithelium in combined treatment group was significantly shorter than that in routine treatment group(P<0.001), and VAS score for pain severity after treatment was significantly lower than that in routine treatment group(P<0.001). The corneal neovascularization area in combined treatment group was significantly smaller than that in routine treatment group(P<0.001), break-up time was significantly longer than that in routine treatment group(P<0.001),and score of corneal opacity was significantly lower than that in routine treatment group(P<0.001). After treatment, levels of inflammatory factors in combined treatment group were significantly lower than those in routine treatment group(all P<0.05). CONCLUSION:Adjuvant amniotic membrane transplantation combined with rhEGF presents prominent clinical advantages in the treatment of alkaline corneal burns. It can enhance therapeutic efficacy, accelerate wound healing, relieve pain, reduce corneal neovascularization, prolong tear film break-up time, alleviate corneal opacification, and reduce the levels of inflammatory factors.

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.

Age-related macular degeneration (AMD) represents a predominant cause of blindness among older adults, with limited therapeutic options currently available. Oxidative stress, inflammation, and retinal pigment epithelium injury are recognized as key contributors to the pathogenesis of AMD. Regulated cell death plays a pivotal role in mediating cellular responses to stress, maintaining tissue homeostasis, and contributing to disease progression. Recent research has elucidated several regulated cell death pathways-such as apoptosis, ferroptosis, pyroptosis, necroptosis, and autophagy-that may contribute to the progression of AMD owing to cell death in the retinal pigment epithelium. These discoveries open new avenues for therapeutic interventions in patients with AMD. In this review, we provide a comprehensive summary and analysis of the latest advancements regarding the relationship between regulated cell death and AMD. Moreover, we examined the therapeutic potential of targeting regulated cell death pathways for the treatment and prevention of AMD, highlighting their roles as promising targets for future therapeutic strategies.

Traumatic brain injury (TBI), as a significant central nervous system damage disease with high frequency in the world, leads to a huge number of patients with impaired health and lower quality of life every year. Lung injury is a common and dangerous consequence, which dramatically raises the mortality of patients. Discovering the pathophysiology of lung injury after TBI and discovering viable therapeutic targets has become an important need for clinical diagnosis and therapy. Neurotransmitters, as the fundamental chemical agents of the nervous system for signal transmission, not only govern neuronal activity and apoptosis in TBI but also significantly influence the pathophysiological mechanisms of lung injury subsequent to TBI. The imbalance is intricately linked to the onset and progression of lung damage. This paper systematically reviews the clinical characteristics and predominant pathogenesis of lung injury following TBI, emphasizing the role of key neurotransmitters, including glutamate (Glu), γ-aminobutyric acid (GABA), norepinephrine (NE), dopamine (DA), and acetylcholine (ACh), in lung injury post-TBI. It examines their influence on inflammatory response, vascular permeability, and pulmonary circulation function. Additionally, the paper evaluates the research advancements and potential applications of targeted therapeutic strategies for various neurotransmitter systems, such as receptor antagonists, transporter inhibitors, and neurotransmitter analogues. This research aims to offer a theoretical framework for clarifying the neural regulatory mechanisms of lung injury following TBI and to establish a basis for the development of novel therapeutic strategies and enhancement of the prognosis of the patients.
Humans ; Brain Injuries, Traumatic/metabolism* ; Neurotransmitter Agents/metabolism* ; Lung Injury/metabolism* ; gamma-Aminobutyric Acid/metabolism* ; Glutamic Acid/metabolism* ; Norepinephrine/metabolism* ; Dopamine/metabolism* ; Acetylcholine/metabolism*

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology

Cervical spine health issues not only seriously affect patients' quality of life but also impose a heavy burden on the social healthcare system. Existing guidelines lack sufficient clinical guidance on lifestyle and work habits, such as exercise, posture, daily routine, and diet, making it difficult to meet practical needs. To address this, relying on the China Association of Chinese Medicine, Wangjing Hospital of China Academy of Chinese Medical Sciences took the lead and joined hands with more than ten institutions to form a multidisciplinary guideline development group. For the first time, the group developed the Guidelines for Cervical Spine Health Intervention based on evidence-based medicine methods, strictly following the standardized procedures outlined in the World Health Organization Handbook for Guideline Development and the Guiding Principles for the Formulation/Revision of Clinical Practice Guidelines in China (2022 Edition). This proposal systematically explains the methods and steps for developing the guideline, aiming to make the guideline development process scientific, standardized, and transparent.
Humans ; Practice Guidelines as Topic/standards* ; Cervical Vertebrae ; China

OBJECTIVE: To analyze the efficacy and safety of decitabine-based myeloablative preconditioning regimen for allogeneic hematopoietic stem cell transplantation (allo-HSCT) in patients with acute myeloid leukemia (AML). METHODS: The clinical characteristics and efficacy of 115 AML patients who underwent allo-HSCT at the First Medical Center of Chinese PLA General Hospital from August 2018 to August 2022 were retrospectively analyzed, including 37 patients treated with decitabine conditioning regimen (decitabine group) and 78 patients without decitabine conditioning regimen (non-decitabine group). The cumulative incidence of relapse (CIR), overall survival (OS), leukemia-free survival (LFS), non-relapse mortality (NRM) and graft versus host disease (GVHD) were analyzed. RESULTS: For the patients in first complete remission (CR1) state before allo-HSCT, the 1-year relapse rates of decitabine group(22 cases) and non-decitabine group(69 cases) were 9.1% and 29.6%, respectively, the difference was statistically significant(P =0.042). The 1-year cumulative incidence of acute graft-versus-host disease (aGVHD) in decitabine group and non-decitabine group was 62.2% and 70.5%, respectively, and the 1-year cumulative incidence of chronic inhibitor-versus-host disease (cGVHD) was 18.9% and 14.1%, respectively, there were no significant differences in the incidence of aGVHD and cGVHD between the two groups (P >0.05). Of the 115 patients, there were no significantly differences in the 1-year CIR(21.7% vs 28.8%, P =0.866), NRM(10.9% vs 3.9%, P =0.203), OS(75.2% vs 83.8%, P =0.131) and LFS(74.6% vs 69.1%, P =0.912) between the decitabine group(37 cases) and the non-decitabine group(78 cases). CONCLUSION Decitabine-based conditioning regimen could reduce the relapse rate of AML CR1 patients with good safety.
Humans ; Leukemia, Myeloid, Acute/therapy* ; Hematopoietic Stem Cell Transplantation/methods* ; Decitabine/therapeutic use* ; Transplantation Conditioning/methods* ; Retrospective Studies ; Graft vs Host Disease ; Transplantation, Homologous ; Male ; Female ; Adult ; Middle Aged ; Adolescent ; Young Adult

OBJECTIVE: To explore the clinical characteristics and prognosis of children with SIL-TAL1-positive T-cell acute lymphoblastic leukemia ( SIL-TAL1⁺ T-ALL). METHODS: The clinical data of 110 children with newly diagnosed T-ALL admitted to the pediatric department of our hospital from January 2010 to December 2018 were reviewed to compare the clinical characteristics, treatment response and prognosis between SIL-TAL1⁺ group and SIL-TAL1^-group. RESULTS: Among the 110 children with T-ALL, 25 cases (22.7%) were in the SIL-TAL1⁺ group and 85 cases (77.3%) in the SIL-TAL1^- group. The white blood cell (WBC) count in the SIL-TAL1⁺ group was significantly higher than that in the SIL-TAL1^- group (P < 0.05), while the other clinical characteristics and treatment response were not significantly different between the two groups. The 5-year overall survival (OS) rates of SIL-TAL1⁺ group and SIL-TAL1^- group were 80.0% and 75.5%, and 5-year disease-free survival (DFS) rates were 76.0% and 72.9%, respectively. There were no significant differences in OS rate and DFS rate between the two groups ( P >0.05). In children aged < 10 years, the 5-year OS rate of SIL-TAL1⁺ group and SIL-TAL1^- group was 100% and 75.1%, respectively, and the difference between the two groups was statistically significant (P < 0.05). CONCLUSION Although the WBC level is significantly higher in children with SIL-TAL1⁺ T-ALL than that in those with SIL-TAL1^- T-ALL, the treatment efficacy is similar between the two groups. In children aged < 10 years, the longterm survival rate is superior in the SIL-TAL1⁺ group.
Humans ; Precursor T-Cell Lymphoblastic Leukemia-Lymphoma/diagnosis* ; Prognosis ; Child ; Male ; Female ; Survival Rate ; T-Cell Acute Lymphocytic Leukemia Protein 1 ; Child, Preschool ; Oncogene Proteins, Fusion ; Leukocyte Count