The European Society of Cardiology (ESC) released the "2024 ESC guidelines for the management of elevated blood pressure and hypertension" on August 30, 2024. This guideline updates the 2018 "Guidelines for the management of arterial hypertension." One notable update is the introduction of the concept of "elevated blood pressure" (120-139/70-89 mm Hg). Additionally, a new systolic blood pressure target range of 120-129 mm Hg has been proposed for most patients receiving antihypertensive treatment. The guideline also includes numerous additions or revisions in areas such as non-pharmacological interventions and device-based treatments for hypertension. This article interprets the guideline's recommendations on definition and classification of elevated blood pressure and hypertension, and cardiovascular disease risk assessment, diagnosing hypertension and investigating underlying causes, preventing and treating elevated blood pressure and hypertension. We provide a comparison interpretation with the 2018 "Guidelines for the management of arterial hypertension" and the "2017 ACC/AHA guideline on the prevention, detection, evaluation, and management of high blood pressure in adults."

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.

ObjectiveTo evaluate the clinical efficacy of Maxing Loushi decoction in the treatment of acute exacerbation of chronic obstructive pulmonary disease （AECOPD） with phlegm turbidity obstructing lung syndrome， and to investigate its effects on inflammatory factors， immune function， and the programmed death-1（PD-1）/programmed death-ligand 1 （PD-L1） signaling pathway. MethodsA randomized controlled study was conducted， enrolling 90 hospitalized patients with AECOPD and phlegm turbidity obstructing lung syndrome in the Respiratory and Emergency Departments of Dongzhimen Hospital， Beijing University of Chinese Medicine， from April 2024 to December 2024. Patients were randomly assigned to a control group and an observation group using a random number table， with 45 patients in each group. The control group received conventional Western medical treatment， while the observation group received additional Maxing Loushi decoction for 14 days. Clinical efficacy， COPD Assessment Test （CAT） score， modified Medical Research Council Dyspnea Scale （mMRC）， 6-minute walk test （6MWT）， serum inflammatory factors， T lymphocyte subsets， and serum PD-1/PD-L1 levels were compared between the two groups before and after treatment. ResultsThe total clinical effective rate was 78.57% （33/42） in the control group and 95.35% （41/43） in the observation group， with the observation group showing significantly higher efficacy than that of the control group. The difference was statistically significant （χ² = 5.136， P<0.05）. After treatment， both groups showed significant reductions in CAT and mMRC scores （P<0.05， P<0.01） and significant increases in 6MWT compared to baseline （P<0.01）. The observation group demonstrated significantly greater improvements than the control group in this regard. Levels of inflammatory markers including C-reactive protein （CRP）， procalcitonin （PCT）， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， monocyte chemoattractant protein-1（MCP-1）， and macrophage inflammatory protein-1α （MIP-1α） were significantly reduced in both groups （P<0.05， P<0.01）， with greater reductions in the observation group （P<0.05， P<0.01）. CD8⁺ levels were significantly reduced （P<0.01）， while CD3⁺， CD4⁺， and CD4⁺/CD8⁺ levels were significantly increased in both groups after treatment （P<0.05， P<0.01）， with more significant improvements observed in the observation group （P<0.05， P<0.01）. Serum PD-1 levels were reduced （P<0.05， P<0.01）， and PD-L1 levels were increased significantly in both groups after treatment （P<0.05， P<0.01）， with more pronounced changes in the observation group （P<0.05）. ConclusionMaxing Loushi decoction demonstrates definite therapeutic efficacy as an adjunctive treatment for patients with AECOPD and phlegm turbidity obstructing lung syndrome. It contributes to reducing serum inflammatory factors， improving immune function， and regulating the PD-1/PD-L1 signaling pathway.

ObjectiveTo evaluate the clinical efficacy of Maxing Loushi decoction in the treatment of acute exacerbation of chronic obstructive pulmonary disease （AECOPD） with phlegm turbidity obstructing lung syndrome， and to investigate its effects on inflammatory factors， immune function， and the programmed death-1（PD-1）/programmed death-ligand 1 （PD-L1） signaling pathway. MethodsA randomized controlled study was conducted， enrolling 90 hospitalized patients with AECOPD and phlegm turbidity obstructing lung syndrome in the Respiratory and Emergency Departments of Dongzhimen Hospital， Beijing University of Chinese Medicine， from April 2024 to December 2024. Patients were randomly assigned to a control group and an observation group using a random number table， with 45 patients in each group. The control group received conventional Western medical treatment， while the observation group received additional Maxing Loushi decoction for 14 days. Clinical efficacy， COPD Assessment Test （CAT） score， modified Medical Research Council Dyspnea Scale （mMRC）， 6-minute walk test （6MWT）， serum inflammatory factors， T lymphocyte subsets， and serum PD-1/PD-L1 levels were compared between the two groups before and after treatment. ResultsThe total clinical effective rate was 78.57% （33/42） in the control group and 95.35% （41/43） in the observation group， with the observation group showing significantly higher efficacy than that of the control group. The difference was statistically significant （χ² = 5.136， P<0.05）. After treatment， both groups showed significant reductions in CAT and mMRC scores （P<0.05， P<0.01） and significant increases in 6MWT compared to baseline （P<0.01）. The observation group demonstrated significantly greater improvements than the control group in this regard. Levels of inflammatory markers including C-reactive protein （CRP）， procalcitonin （PCT）， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， monocyte chemoattractant protein-1（MCP-1）， and macrophage inflammatory protein-1α （MIP-1α） were significantly reduced in both groups （P<0.05， P<0.01）， with greater reductions in the observation group （P<0.05， P<0.01）. CD8⁺ levels were significantly reduced （P<0.01）， while CD3⁺， CD4⁺， and CD4⁺/CD8⁺ levels were significantly increased in both groups after treatment （P<0.05， P<0.01）， with more significant improvements observed in the observation group （P<0.05， P<0.01）. Serum PD-1 levels were reduced （P<0.05， P<0.01）， and PD-L1 levels were increased significantly in both groups after treatment （P<0.05， P<0.01）， with more pronounced changes in the observation group （P<0.05）. ConclusionMaxing Loushi decoction demonstrates definite therapeutic efficacy as an adjunctive treatment for patients with AECOPD and phlegm turbidity obstructing lung syndrome. It contributes to reducing serum inflammatory factors， improving immune function， and regulating the PD-1/PD-L1 signaling pathway.

This study aimed to investigate the effect of Flos Farfarae (FF) fumigation on cigarette smoke-induced lung injury mice, and analyze the metabolic profile of lung tissue by metabolomics. All animal experiments were conducted under the guidance and approval of the Animal Ethics Review Committee of Shanxi University (Approval number: SXULL2019014). By using HS-GC-MS to analyze volatile components of Flos Farfarae, 23 compounds were identified. The results showed that FF fumigation improved the lung tissue morphology of cigarette smoke-induced lung injury mice, lowered the levels of interleukin 6 (IL-6) and interleukin-1β (IL-1β). The lung tissue samples were applied for metabolomic analysis based on UHPLC-QTOF MS, the results showed that 70 metabolites were changed in the lung tissue of mice after cigarette exposure, and 35 of them could be regulated, including lysophosphatidylcholine (LPC), 12-HETE, adenosine, and xanthine. These metabolites, such as LPC, 12-HETE, adenosine, and xanthine were mainly associated with the body's inflammatory response. It was observed that these metabolites are primarily involved in purine metabolism, arachidonic acid metabolism, phospholipid metabolism, and pyruvate metabolism pathways. These findings suggest that the volatile terpenoids in the FF may regulate the metabolites associated with the inflammatory response in the lung tissue, such as lysophosphatidylcholine, 12-HETE, and adenosine, which could further alleviate lung inflammation induced by cigarette smoke through the metabolic pathways of purine metabolism and others. This study proved the scientific basis of the traditional application of FF fumigation, and provided a theoretical basis for the further product development.

Based on the interaction between supramolecule of traditional Chinese medicine and enterobacteria, the material basis of Rhei Radix et Rhizoma and Coptidis Rhizoma was explored. Scanning electron microscopy (SEM) and dynamic light scattering (DLS) were used to characterize the morphological differences of Rhubarb single decoction, Coptis single decoction and Rhubarb and Coptis co-decoction. An in vitro antibacterial model (E. coli, E. faecium and B. subtilis) was established to evaluate the damage effect of the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma on enterobacteria. Ultra high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to analyze the changes of chemical components of single decoctions and co-decoctions. The co-decoction of Rhei Radix et Rhizoma and Coptidis Rhizoma was turbid after decocting. The spherical particles of 300-400 nm were observed under SEM, and the co-decoction was more uniform and stable than that of single decoction. The interaction between supramolecules formed after the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma and enterobacteria was significantly different from that of single decoction. In the process of interaction between supramolecules and enterobacteria, the spherical state was maintained, and the medicinal ingredients in Coptidis Rhizoma or Rhei Radix et Rhizoma were blocked, which could effectively alleviate the damage to enterobacteria. This study provided a reference for subsequent studies on the regulation of intestinal flora homeostasis by the combination of Rhei Radix et Rhizoma and Coptidis Rhizoma.

Objective To analyze the correlation between the ELL2 gene 1119 T>C polymorphism and the susceptibility to pleomorphic adenoma of the salivary gland.Methods The pedigree of the pleomorphic adenoma family of salivary gland was drawn.The exons of ELL2 gene in 5 members of salivary pleomorphic adenoma family were sequenced.A case-control study was conducted.One hundred and twelve patients with pleomorphic adenoma of the salivary gland who visited the Department of Oral and Maxillofacial Surgery of Shanxi Bethune Hospital from January 2016 to July 2020 were taken as case group,and 176 healthy examinees from January 2019 to January 2020 were taken as control group with age and sex as matching conditions.The 1119 T>C polymorphism of ELL2 genes in the two groups were detected with high resolution melting(HRM)curve.Chi-square test was adopted to analyze the correlation between gene polymorphism and the occurrence of pleomorphic adenoma of the salivary gland,stratified analysis was performed to evaluate the synergistic effect of smoking and genotype,and real time quantitative reverse transcription polymerase chain reaction(RT-PCR)was used to detect the expression level of ELL2 in individuals with different genotypes.Results The 1119 T>C polymorphism site existed in the exon 8 of ELL2 gene in a family with pleomorphic adenoma of salivary gland.The results of case-control study showed that the genotype frequency of homozygous CC was significantly higher in patients with pleomorphic adenoma of salivary gland than that in the controls(24.1%vs.11.9%,P=0.002).Homozygous CC was associated with increased risk for developing pleomorphic adenoma of salivary gland(OR=3.059,95%CI 1.494-6.263)in this cohort.Stratification analysis showed that smoking and 1119C allele cooperated to increase the risk of pleomorphic adenoma of salivary gland(OR=3.200,95%CI 1.460-7.014).The expression level of ELL2 mRNA in CC genotype was significantly higher than that in individuals with CT or TT genotype(P<0.05).Conclusion The genetic variation of ELL2 may play an important role in the occurrence of pleomorphic adenoma of salivary gland,and smoking combined with the 1119C allele increased the risk of this disease.

ObjectiveIn recent years, with the intensification of environmental issues and the depletion of ozone layer, incidence of skin tumors has also significantly increased, becoming one of the major threats to people’s lives and health. However, due to factors such as high concealment in the early stage of skin tumors, unclear symptoms, and large human skin area, most cases are detected in the middle to late stage. Early detection plays a crucial role in postoperative survival of skin tumors, which can significantly improve the treatment and survival rates of patients. We proposed a rapid non-invasive electrical impedance detection method for early screening of skin tumors based on bioimpedance spectroscopy (BIS) technology. MethodsFirstly, we have established a complete skin stratification model, including stratum corneum, epidermis, dermis, and subcutaneous tissue. And the numerical analysis method was used to investigate the effect of dehydrated and dry skin stratum corneum on contact impedance in BIS measurement. Secondly, differentiation effect of different diameter skin tumor tissues was studied using a skin model after removing the stratum corneum. Then, in order to demonstrate that BIS technology can be used for detecting the microinvasion stage of skin tumors, we conducted a simulation study on the differentiation effect of skin tumors under different infiltration depths. Finally, in order to verify that the designed BIS detection system can distinguish between tumor microinvasion periods, we conducted tumor invasion experiments using hydrogel treated pig skin tissue. ResultsThe simulation results show that a dry and high impedance stratum corneum will bring about huge contact impedance, which will lead to larger measurement errors and affect the accuracy of measurement results. We extracted the core evaluation parameter of relaxed imaginary impedance (Z_imag-relax) from the simulation results of the skin tumor model. When the tumor radius (R_tumor) and invasion depth (h)>1.5 mm, the designed BIS detection system can distinguish between tumor tissue and normal tissue. At the same time, in order to evaluate the degree of canceration in skin tissue, the degree of tissue lesion (ε_worse) is defined by the relaxed imaginary impedance (Z_imag-relax) of normal and tumor tissue (ε_worse is the percentage change in virtual impedance of tumor tissue relative to that of normal tissue), and we fitted a Depth-Z_imag-relax curve using relaxation imaginary impedance data at different infiltration depths, which can be applied to quickly determine the infiltration depth of skin tumors after being supplemented with a large amount of clinical data in the future. The experimental results proved that when ε_worse=0.492 0, BIS could identify microinvasive tumor tissue, and the fitting curve correction coefficient of determination was 0.946 8, with good fitting effect. The simulation using pig skin tissue correlated the results of real human skin simulation with the experimental results of pig skin tissue, proving the reliability of this study, and laying the foundation for further clinical research in the future. ConclusionOur proposed BIS method has the advantages of fast, real-time, and non-invasive detection, as well as high sensitivity to skin tumors, which can be identified during the stage of tumor microinvasion.

ObjectiveTemporal heterogeneity in lung cancer presents as fluctuations in the biological characteristics, genomic mutations, proliferation rates, and chemotherapeutic responses of tumor cells over time, posing a significant barrier to effective treatment. The complexity of this temporal variance, coupled with the spatial diversity of lung cancer, presents formidable challenges for research. This article will pave the way for new avenues in lung cancer research, aiding in a deeper understanding of the temporal heterogeneity of lung cancer, thereby enhancing the cure rate for lung cancer. MethodsRaman spectroscopy emerges as a powerful tool for real-time surveillance of biomolecular composition changes in lung cancer at the cellular scale, thus shedding light on the disease’s temporal heterogeneity. In our investigation, we harnessed Raman spectroscopic microscopy alongside multivariate statistical analysis to scrutinize the biomolecular alterations in human lung epithelial cells across various timeframes after benzo(a)pyrene exposure. ResultsOur findings indicated a temporal reduction in nucleic acids, lipids, proteins, and carotenoids, coinciding with a rise in glucose concentration. These patterns suggest that benzo(a)pyrene induces structural damage to the genetic material, accelerates lipid peroxidation, disrupts protein metabolism, curtails carotenoid production, and alters glucose metabolic pathways. Employing Raman spectroscopy enabled us to monitor the biomolecular dynamics within lung cancer cells in a real-time, non-invasive, and non-destructive manner, facilitating the elucidation of pivotal molecular features. ConclusionThis research enhances the comprehension of lung cancer progression and supports the development of personalized therapeutic approaches, which may improve the clinical outcomes for patients.

ObjectiveTriple-negative breast cancer (TNBC) is the breast cancer subtype with the worst prognosis, and lacks effective therapeutic targets. Colony stimulating factors (CSFs) are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells, playing an important role in the malignant progression of TNBC. This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes (CRGs), and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy. MethodsWe downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database. Through LASSO Cox regression analysis, we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score (CRRS). We further analyzed the correlation between CRRS and patient prognosis, clinical features, tumor microenvironment (TME) in both high-risk and low-risk groups, and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy. ResultsWe identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model. Kaplan-Meier survival curves, time-dependent receiver operating characteristic curves, and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival, and the predictive ability of CRRS prognostic model was further validated using the GEO dataset. Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients. Moreover, patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil, ipatasertib, and paclitaxel. ConclusionWe have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs, which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment. Moreover, the key genes within this model may represent potential molecular targets for future therapies of TNBC.