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 provide a reference for the establishment, development and application of the adverse drug reaction （ADR） automated monitoring system, through verifying and quantifying the research hotspots and advantages of the system by CiteSpace software and systematic review. Methods Literature on ADR automated monitoring up to December 2023 were retrieved and screened from CNKI and web of science databases. CiteSpace 6.4.R1 software was used to conduct co-occurrence, clustering and emergence analysis, and to visualize and comparatively analyze the research hotspots, rules and distribution in the field of automated monitoring of ADR at home and abroad. In compliance with the preferred reporting items for systematic reviews and Meta-analyses （PRISMA）, literature covering publications in English and Chinese including detection rates of ADR collected using Incident Reporting Systems （IRSs） and/or automated monitoring systems were retrieved and screened. The advantages and disadvantages of automated monitoring systems were analyzed by comparing the differences between these two systems in terms of the number of ADR reports and the types of positive signals. Results A total of 56 articles in English and 80 articles in Chinese were indexed by CiteSpace. The research hotspots in recent years included data mining, deep learning, text classification techniques, machine learning and so on. A total of seven studies compiled with the inclusion criteria for the systematic evaluation, all of which were completed between 1991 and 2021 in hospitals in four countries. 150 526 medical records were reviewed from 15 institutions. A total of 194 ADR reports were collected by IRSs. A total of 2 090 ADR reports were collected by the automated monitoring system over the same period, indicating a 977% increase in the number of ADR reports （P=0.0156） compared with the IRSs. Conclusion The ADR automatic monitoring system had significantly improved the level of drug risk identification and reduced costs, but it was necessary to optimize the algorithm, expand the data source and carry out standardization construction to overcome the current limitations.

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 investigate the characteristics of malignant tumor incidence and mortality in cancer registration areas of Zhejiang Province in 2021. Methods: Based on the 2021 cancer registration data from 22 national cancer registries in Zhejiang Province, the crude incidence, crude mortality, and cumulative rate for 0 to 74 years were calculated. Age standardized was performed using the age composition of the standard population from the Fifth National Population Census in 2000 and Segi's world standard population. The incidence and mortality characteristics of malignant tumor in different genders, urban/rural areas and ages were described. The order of crude incidence and mortality of malignant tumor were analyzed. Results: In 2021, there were 116 639 new malignant tumor cases in Zhejiang Province. The crude, Chinese population standardized, and world population-standardized incidences were 530.93/100 000, 304.83/100 000, and 288.20/100 000, respectively. The cumulative incidence for 0 to 74 years was 31.92%. There were 40 475 death cases. The crude, Chinese population-standardized, and world population-standardized mortalities were 184.24/100 000, 79.40/100 000, and 78.97/100 000, respectively. The cumulative mortality for 0 to 74 years was 8.37%. The Chinese population-standardized incidence for males and females were 286.34/100 000 and 323.45/100 000, respectively, and the Chinese population-standardized mortality were 106.25/100 000 and 54.17/100 000, respectively. The Chinese population-standardized incidence for urban and rural were 316.85/100 000 and 285.11/100 000, respectively, and the Chinese population-standardized mortality were 75.59/100 000 and 85.48/100 000, respectively. The crude incidence and crude mortality of malignant tumor both increased with age, peaking in the groups aged 80-<80 and ≥85 years at 1 845.06/100 000 and 1 656.88/100 000, respectively. The top ten malignant tumors with the highest crude incidence were, in descending order: lung cancer, thyroid cancer, breast cancer, prostate cancer, colorectal cancer, gastric cancer, liver cancer, cervical cancer, lymphoma, and brain tumors. These accounted for 80.34% of all new malignant tumor cases. The top ten malignant tumors with the highest crude mortality were, in descending order: lung cancer, liver cancer, colorectal cancer, gastric cancer, pancreatic cancer, prostate cancer, breast cancer, esophageal cancer, lymphoma, and gallbladder cancer. These accounted for 82.26% of all malignant tumor deaths. Conclusions In 2021, the cancer registration areas of Zhejiang Province were characterized by a relatively high malignant tumor incidence and a comparatively low mortality compared to national data. Males and the elderly emerged as key populations for targeted prevention and control. It is recommended to enhance screening, early diagnosis, and early treatment for lung cancer, thyroid cancer, prostate cancer, breast cancer, and gastric cancer malignancies.

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

BACKGROUND: Spinal cord injury (SCI) survivors often experience constipation, which contributes to a reduced sense of well-being and a lower quality of life. Acupressure offers a non-pharmacological and non-invasive alternative therapy for treating constipation. OBJECTIVE: This study examined the effects of home-based acupressure on constipation and subjective well-being among SCI survivors. DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS: This randomized controlled trial randomly assigned 80 adults from Hong Kong with SCI to two study groups. Using a video demonstration filmed by a registered traditional Chinese medicine practitioner, the intervention group performed home-based acupressure (self-administered or caregiver-assisted) twice daily, 15 min/session, for 10 consecutive days. The control group performed manual light touching of the abdomen with the same frequency and duration as the intervention group. Both groups received defecation education through a structured booklet. MAIN OUTCOMES MEASURES: The primary outcome was constipation severity. Secondary outcomes included bowel habits, psychological well-being, and quality of life. Focus group interviews were conducted after the intervention to collect subjective feedback from participants. RESULTS: Significant group-by-time interaction effects on constipation severity (P = 0.005) and quality of life (P = 0.001) revealed that home-based acupressure produced better results than the control. These treatment effects persisted at the one-month follow-up and continued to have a large effect size (Cohen's d > 0.8). Compared to the control group, the acupressure group also had improvements in anxiety (Cohen's d = 0.69) and depression (Cohen's d = 0.72) at the end of the intervention period. Three qualitative categories were identified from the focus group interviews: improvements in bowel function and management; reduced psychological distress following relief from constipation; and acceptability of home-based acupressure. CONCLUSION: Acupressure effectively relieves constipation, enhances psychological well-being, and improves quality of life in people with SCI. These data provide novel evidence supporting the use of home-based acupressure as an acceptable and effective therapy for treating constipation after SCI. TRIAL REGISTRATION ClinicalTrials.gov (NCT05558657). Please cite this article as: Li MQ, Li Y, Lam W, Yeung WF, Ho YS, Li JY, Sun TC, Yuen S, Hu YL, Yorke J. Home-based acupressure for managing constipation and subjective well-being in spinal cord injury survivors: A randomized controlled trial. J Integr Med. 2025; 23(6):660-669.
Humans ; Acupressure/methods* ; Constipation/psychology* ; Male ; Female ; Spinal Cord Injuries/complications* ; Middle Aged ; Adult ; Quality of Life ; Aged

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged