Objective To understand the current status of low-density lipoprotein cholesterol (LDL-C) control in patients after coronary artery bypass grafting (CABG). Methods Clinical data of patients who underwent isolated CABG in Beijing Anzhen Hospital in 2023 were collected. All patients returned to our hospital approximately one year after surgery (10-13 months) for a lipid level recheck. We analyzed their LDL-C attainment status and influencing factors. Patients were categorized into two groups based on whether their LDL-C met the target: a LDL-C attainment group and a LDL-C non-attainment group. Results This study included 1456 patients who underwent CABG, including 320 females and 1136 males, with an average age of (61.41±9.12) years. One year post-surgery, 234 patients achieved the LDL-C target, with an attainment rate of 16.07%. The proportion of patients in the LDL-C attainment group who were ultra-high risk (77.35% vs. 92.06%, P＜0.001), female (16.24% vs. 23.08%, P=0.021), and those with comorbid hypertension (55.98% vs. 63.18%, P=0.038) was significantly lower than those in the LDL-C non-attainment group. Additionally, the baseline body mass index (BMI) [(25.37±3.24) kg/m2 vs. (26.03±3.56) kg/m2, P=0.017], total cholesterol levels [(3.30±0.84) mmol/L vs. (4.01±1.03) mmol/L, P＜0.001], LDL-C [(1.62±0.63) mmol/L vs. (2.25±0.85) mmol/L, P＜0.001], and high-density lipoprotein cholesterol [(0.98±0.26) mmol/L vs. (1.02±0.24) mmol/L, P=0.049] upon admission in the attainment group were all lower than those in the non-attainment group. Moreover, the lipid-lowering drug usage rate in the attainment group (100.00% vs. 96.24%, P=0.003) and the proportion using two types of drugs together (25.21% vs. 10.72%, P＜0.001) were both higher than those in the non-attainment group, while the statin monotherapy rate was lower than that in the non-attainment group (74.79% vs. 85.19%, P＜0.001). Logistic regression analysis showed that baseline BMI (OR=0.928, P=0.012) and baseline LDL-C levels (OR=0.207, P<0.001), patient cardiovascular risk stratification (OR=0.155, P<0.001) and lipid-lowering drug treatment regimen (OR=3.758, P<0.001) are significant factors affecting the LDL-C control status. Conclusion The LDL-C compliance rate of patients undergoing CABG is at a relatively low level 1 year after surgery. Patients with very high risk of atherosclerotic cardiovascular disease, high baseline LDL-C levels, and overweight or obesity should be strengthened lipid management. For these patients, the intensity of lipid-lowering drug use or combination medication should be increased upon discharge.

Compared to traditional machine learning algorithms,which often suffer from low feature extraction efficiency,insufficient nonlinear pattern recognition capabilities and slow training speeds,the broad learning system(BLS)enhances the learning ability and efficiency by horizontally expanding the network structure.BLS offers advantages such as a simple structure,fast training speed,and strong generalization capabilities.While BLS has demonstrated potential in various fields,but its application in identification of complex samples has not been fully explored.This research investigated the feasibility of using BLS algorithm for identification of complex samples based on physicochemical indicators.Using the iris,wine,and breast cancer datasets,the length and width of petals and sepals of iris flowers,the physicochemical properties of wine,and the nuclear characteristics of breast cancer cells were used as input variables to establish BLS models for identifying iris species,wine varieties,and benign versus malignant nucleus.The model performance was evaluated by confusion matrices,accuracy,and runtime.Compared with partial least squares-discriminant analysis(PLS-DA),soft independent modeling of class analogies(SIMCA),and artificial neural networks(ANN),the results indicated that BLS demonstrated significant advantages in computational efficiency and recognition accuracy.Thus,BLS was an efficient and reliable method for identification of complex samples.

Objective:To investigate the expression and clinical significance of long noncoding RNA (lncRNA) AP006284.1 in bladder cancer tissues, and to analyze the regulatory effect and downstream mechanism of AP006284.1 knockdown on the proliferation and migration of bladder cancer cells. Methods:The expression of AP006284.1 in bladder cancer tissues, and the relationship between AP006284.1 expression and tumor stage and disease-free survival of bladder cancer patients were analyzed in the gene expression omnibus (GEO) database. AP006284.1 gene expression in bladder cancer cell lines, including MGH-U3, T24, UMUC-3, J82 and 5637, and bladder epithelial immortalized SV-HUC-1 cell were detected by real-time reverse transcription-PCR (RT-qPCR) assay. J82 cells were divided into the control group and the transfection group, and transfected with control plasmid and AP006284.1 knockdown plasmid, respectively. The effect of AP006284.1 knockdown on the proliferation of J82 cells was detected by RT-qPCR and cell counting kit-8 (CCK-8) assay. The effect of AP006284.1 knockdown on the migration of J82 cells was determined by the scratch healing assay. The target gene of AP006284.1 was predicted by LncRNA2Target and LncRNome databases. The target fragment of wild-type AP006284.1 ( AP006284.1-Wt) or mutant AP006284.1 ( AP006284.1-Mut) was constructed into pGL3 plasmid by dual luciferase gene reporter assay. J82 cells were co-transfected with miR-205-3p or miR-negtive control (miR-NC) to validate the targeting relationship between AP006284.1 and miR-205-3p. The correlation between miR-205-3p and AP006284.1 expression in bladder cancer tissues was further analyzed by the GEO database. The effect of AP006284.1 knockdown on the expression of miR-205-3p gene in J82 cells was detected by RT-qPCR assay. The effect of AP006284.1 knockdown on the expression of phosphorylated Ras protein (p-Ras), phosphorylated Raf protein (p-Raf), phosphorylated mitogen-activated protein kinase kinase (p-MEK), and phosphorylated extracellular signal-regulated kinase (p-ERK) of the ERK pathway was detected by Western blotting in J82 cells. Results:GEO database analysis showed that the relative expression of AP006284.1 in bladder cancer tissues ( n=304) was significantly higher than that in normal tissues ( n=28, P<0.01). The relative expression of AP006284.1 was positively correlated with the tumor stage of the bladder cancer patients ( P<0.01). Compared with bladder cancer patients with low expression of AP006284.1, patients with high expression had a lower disease-free survival ( P<0.01). Compared with the SV-HUC-1 cell (1.02±0.34), the expression level of AP006284.1 gene was upregulated in MGH-U3 cell (5.77±0.37), T24 cell (3.02±0.40), UMUC-3 cell (3.62±0.59), J82 cell (7.19±0.24) and 5637 cell (5.59±0.30) (all P<0.01). The expression level of the AP006284.1 gene was the highest in J82 cells, therefore, the J82 cells were selected for the study. The expression level of AP006284.1 gene in the control group (7.20±0.26) was 6.92 times higher than that in the transfection group (1.04±0.28, t=16.16, P<0.01). Compared with the control group (0.74±0.11, 1.35±0.09, 1.63±0.14, 1.74±0.11), the absorbance ( A) values of J82 cells in the transfection group (0.49±0.06, 0.95±0.14, 1.09±0.08, 1.13±0.11) were reduced than those in the control group at the 24, 36, 48 and 60 h after AP006284.1 knockdown (all P<0.05). The migration distance of J82 cells in the control group was significantly longer than that in the transfection group. The migration rate of the control group [(65.03±6.20)%], which was 2.58 times higher than that of the transfection group [(25.22±3.45)%, t=5.61, P<0.01]. The target site of miR-205-3p containing AP006284.1 was predicted by LncRNA2Target and LncRNome databases. Compared with miR-NC group (1.00±0.11), the relative activity of dual luciferase of AP006284.1-Wt gene was significantly downregulated in the miR-205-3p group (0.31±0.07, t=5.47, P<0.01). Compared with the miR-NC group (0.97±0.14), the relative activity of dual luciferase of AP006284.1-Mut vector (0.98±0.07) was not significantly change ( t=0.09, P>0.05). The GEO database analysis showed that the expression of AP006284.1 in bladder cancer tissues was negatively correlated with the expression of miR-205-3p ( P<0.01). The expression level of miR-205-3p gene in the transfection group (5.42±0.24) was 5.21 times higher than that in the control group (1.04±0.40, t=9.40, P<0.01). Compared with the control group (3.22±0.17, 5.56±0.19, 4.38±0.17, 5.74±0.36), the expressions of p-Ras (2.33±0.12), p-Raf (1.61±0.20), p-MEK (1.57±0.25), and p-ERK (2.40±0.28) of the ERK pathway were decreased in the transfected J82 cells (all P<0.01). Conclusions:AP006284.1 is highly expressed in bladder cancer tissues. Knockdown of AP006284.1 can inhibit the proliferation and migration of bladder cancer cells by regulating the miR-205-3p and ERK pathway proteins.

Objective:To establish a quality control method for the standard decoction of Polygoni Avicularis Herba.Methods:Totally 12 batches of decoction pieces from different origins were collected, the standard decoction was prepared and the quality evaluation method was established, the content of index components in the decoction pieces and the standard decoction was determined with HPLC, the index components, solution pH and other parameters were calculated, and the similarity analysis was carried out against the fingerprints.Results:The total content of myricetin in 12 batches of decoction pieces was >0.12%, and the content of myricetin in the standard decoction was >0.03%, which met the standard of the 2020 edition of the Chinese Pharmacopoeia. The pH value was 5.1-5.5, the transfer rate of myricetin components ranged from 50.0%-106.3%, and the fingerprint study showed that there were 7 common peaks. The similarity analysis results indicated that the standard decoction of 12 batches of decoction pieces of Polygoni Avicularis Herba had good consistency.Conclusion:The preparation process is stable and feasible in line with the traditional decoction preparation method, and can be used for the research and quality evaluation of the standard decoction.

Objective: To predict and screen potential biomarkers of systemic lupus eythematosus(SLE) based on machine learning algorithms and structural biology, and to reveal their mechanisms of action and to provide new targets for disease diagnosis and treatment. Methods: Four machine learning algorithms, random forest(RF), eXtreme gradient boosting(XGBoost), support vector machine(SVM), least absolute shrinkage and selection operator(LASSO), were used to analyze the gene expression data of SLE patients in GEO(datasets: GSE121239 and GSE11907) to analyze the gene expression data of SLE patients and screen key markers. Peripheral blood single nucleated cells(PBMCs) from SLE patients were collected and RT-qPCR was used to detect differential gene expression levels. Subsequently, GSEA enrichment analysis was used to identify biomarker-related pathways. CIBERSORT immune infiltration analysis and protein interactions network were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Interaction relationships in combination with AlphaFold3(AF3) were predicted. Results: Multiple algorithms were screened together to identify the unique marker gene HERC5 , and expression analysis of multiple datasets showed that HERC5 was highly expressed in SLE compared to the normal group (P < 0. 05) , and RT⁃qPCR verified the same trend (P = 0. 006 2) . Functional enrichment analysis identified the major pathway promoted by HERC5 in SLE as the interferon receptor signalling pathway (P < 0. 05) . Immune infiltration analysis showed that HERC5 was closely associated with immune cells (Neutrophils : r = 0. 39 , P < 0. 05 ; Memory B cells : r = 0. 33 , P < 0. 05 ; Activated dendritic cell : r = 0. 52 , P < 0. 05) . Most HERC5 ⁃related interacting proteins were associated with SLE ,and potential transcription factors of HERC5 and its related genes were also significantly associated with immune responses. Conclusion The HERC5 gene is an important biomarker for SLE , which upregulates the interferon pathway to promote SLE progression and provides a new target for SLE diagnosis and treatment.

Histone deacetylase 3 (HDAC3) is an epigenetic modification enzyme that plays a crucial role in the development and progression of diabetes and its complications. Studies have reported that increased HDAC3 activity is associated with pancreatic β-cell dysfunction in type 1 diabetes, while in type 2 diabetes, HDAC3 affects insulin resistance and signaling by regulating the metabolism of the liver, adipose tissue, and muscle. Additionally, HDAC3 plays a key role in diabetic complications such as cardiomyopathy, retinopathy, and nephropathy. Selective inhibition of HDAC3 has the potential to improve insulin sensitivity, reduce chronic inflammation, and enhance pancreatic cell function, offering a promising new therapeutic strategy for diabetes and its complications.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic

OBJECTIVES: This study aimed to investigate the impact of foam macrophages (FMs) on the intracellular survival of Mycobacterium tuberculosis (MTB) and identify the molecular mechanisms influencing MTB survival. METHODS: An in vitro FM model was established using oleic acid induction. Transcriptomic and metabolomic analyses were conducted to identify the key molecular pathways involved in FM-mediated MTB survival. RESULTS: Induced FMs effectively restricted MTB survival. Transcriptomic and metabolomic profiling revealed distinct changes in gene and metabolite expression in FMs during MTB infection compared with normal macrophages. Integrated analyses identified significant alterations in the cyclic adenosine monophosphate (cAMP) signaling pathway, indicating that its activation contributes to the FM-mediated restriction of MTB survival. CONCLUSIONS FMs inhibit MTB survival. The cAMP signaling pathway is a key contributor. These findings enhance the understanding of the role of FMs in tuberculosis progression, suggest potential targets for host-directed therapies, and offer new directions for developing diagnostic and therapeutic strategies against tuberculosis.
Mycobacterium tuberculosis/physiology* ; Transcriptome ; Metabolomics ; Foam Cells/microbiology* ; Humans ; Metabolome ; Tuberculosis/microbiology* ; Gene Expression Profiling