BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Objective: Whether elevation in plasma levels of amyloid and tau protein biomarkers are better indicators of cognitive decline than higher baseline levels in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) remains understudied. Methods: We included 67 participants with twice testing for AD-related plasma biomarkers via immunomagnetic reduction (IMR) assays (amyloid beta [Aβ]1-40, Aβ1-42, total tau [t-Tau], phosphorylated tau [p-Tau] 181, and alpha-synuclein [α-Syn]) and the Mini-Mental State Examination (MMSE) over a 1-year interval. We examined the correlation between biomarker levels (baseline vs. longitudinal change) and annual changes in the MMSE scores. Receiver operating characteristic curve analysis was conducted to compare the biomarkers. Results: After adjustment, faster cognitive decline was correlated with lower baseline levels of t-Tau (β=0.332, p=0.030) and p-Tau 181 (β=0.369, p=0.015) and rapid elevation of t-Tau (β=-0.330, p=0.030) and p-Tau 181 levels (β=-0.431, p=0.004). However, the levels (baseline and longitudinal changes) of Aβ1-40, Aβ1-42, and α-Syn were not correlated with cognitive decline. aMCI converters had lower baseline levels of p-Tau 181 (p=0.002) but larger annual changes (p=0.001) than aMCI non-converters. The change in p-Tau 181 levels showed better discriminatory capacity than the change in t-Tau levels in terms of identifying AD conversion in patients with aMCI, with an area under curve of 86.7% versus 72.2%. Conclusion We found changes in p-Tau 181 levels may be a suitable biomarker for identifying AD conversion.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

ObjectiveTo identify the active components in Maimendong decoction (MMDD) against pulmonary fibrosis (PF) and validate their molecular effects in vitro, while focusing on the role of methylophiopogonanone B in regulating fibrosis.MethodsData on MMDD components and targets were gathered from databases including BATMAN-TCM and PubMed, whereas the PF gene data were sourced from GeneCards, OMIM, and TTD. Shared targets were determined using the STRING database, and molecular docking was used to analyze the essential molecules associated with fibrosis. To simulate PF conditions, human embryonic lung fibroblasts (HPF) and A549 cells were exposed to transforming growth factor-β1 (TGF-β1). Various assays were used to determine the effects of MMDD and methylophiopogonanone B on signaling pathways, apoptosis, and epithelial–mesenchymal transition.ResultsWe identified 11 active components from MMDD extracts that targeted 511 shared proteins associated with PF, revealing 10 key targets in network analysis. Gene ontology analysis indicated that processes and pathways such as apoptosis regulation and PI3K/Akt signaling were involved. In vitro experiments revealed that MMDD downregulated the expression of α-smooth muscle actin (α-SMA), collagen type I (COL-I), and collagen type III and regulated Bcl-2/Bax signaling pathways to promote apoptosis. The flow cytometry apoptosis assay revealed that MMDD promoted the TGF-β1-induced apoptosis of myofibroblasts. The primary active ingredient in MMDD, methylophiopogonanone B, reduced α-SMA, COL-I, and PI3K/Akt/mTOR-related protein levels in TGF-β1-treated HPF cells, decreased Bcl-2 and cleaved caspase 3, and increased Bax. Moreover, methylophiopogonanone B increased E-cadherin levels and reduced α-SMA, fibronectin, N-cadherin, vimentin, and snail in TGF-β1-treated A549 cells.ConclusionMethylophiopogonanone B demonstrated the potential to treat PF by inducing myofibroblast apoptosis and inhibiting EMT. However, despite encouraging initial results, further clinical research is warranted to verify the safety and efficacy of methylophiopogonanone B in the management of PF

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To investigate the clinical outcomes of arthroscopic suture anchor fixation for acute bony Bankart lesions.Methods:Data of 49 patients with acute bone Bankart injury treated with suture anchor fixation under arthroscopy at the Affiliate Nanjing Drum Tower Hospital of Nanjing University School of Medicine from February 2019 to July 2024 were retrospectively analyzed, including 34 males and 15 females, aged 46.4±17.7 years (range, 18-81 years). Body mass index was 26.3±4.2 kg/m 2 (range, 19.8-37.9 kg/m 2). There were 17 patients with left shoulder and 32 patients with right shoulder. The time from injury to operation was 12.6±10.5 d (range, 1-50 d). CT three-dimensional reconstruction showed that the area of bone defect accounted for 20.1%±11.4% (range, 8%-49%) of the glenoid area. According to the degree of bone defect, there were 38 cases in the bone defect area ≤25% group and 11 cases in the bone defect area >25% group. All 49 patients received shoulder arthroscopic fixation with wire anchor. All 49 the patients were treated under shoulder arthroscopy using suture anchor technique. Using American Shoulder & Elbow Surgeon (ASES) score, University of California, Los Angeles (UCLA) score, Rowe score as well as shoulder range of motion to evaluate shoulder function. The position and healing of the fracture mass were evaluated with shoulder joint CT and three-dimensional reconstruction at immediate and final follow-up. Results:The incision healed in one stage and no infection occurred in all patients. All 49 patients were followed up for a period of 3 to 81 months, with an average follow-up of 23.8±20.2 months. At the final follow-up, the mean forward elevation, external rotation, and internal rotation improved from 126.1°±20.3°, 36.9°±14.0°, and 10±2 preoperatively to 167.1°±15.5°, 66.8°±8.3°, and 6±1 at the last follow-up, respectively ( P<0.05). At the final follow-up, the mean ASES score, UCLA score, and Rowe score were all significantly improved from 41.3±11.9, 14.2±6.1 and 46.9±14.7 preoperatively to 89.7±7.8, 31.5±3.6 and 92.4±7.4, respectively ( P<0.05). The differences between the final follow-up and preoperative values for forward elevation in the bone defect area >25% group and the bone defect area ≤25% group were 43°±20° and 41°±21°, respectively. The differences in lateral external rotation were 34°±8° and 29°±18°, while the differences in internal rotation (measured by hand-behind-back reach) were 5±2 and 4±2, respectively. None of these differences were statistically significant. The differences between the final follow-up and preoperative scores in the bone defect area >25% fracture fragment group and the bone defect area ≤25% group were as follows: ASES score, 50.9±14.4 vs. 47.7±12.8; UCLA score, 18.4±3.2 vs. 17.0±6.9; and Rowe score, 40.5±13.5 vs. 46.9±15.0. None of these differences were statistically significant. CT examination at the last follow-up showed that all fractures were healed, all patients in the bone defect area ≤25% group achieved good reduction, and 3 patients in the bone defect area >25% group had step-offs on the glenoid surface. Postoperative shoulder adhesion occurred in 5 patients, which was improved after intensive abduction and external rotation exercise. Conclusions:Arthroscopic suture anchor fixation is effective for the bone defect area ≤25% bony Bankart lesions, offering advantages of minimal invasiveness and rapid recovery. For lesions involving more than the bone defect area 25% of the glenoid surface, enhanced fixation strength is recommended to prevent fracture fragment displacement.