ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

Objective To explore the relationship between PANoptosis and hepatic ischemia-reperfusion injury (HIRI), and to screen the key genes of PANoptosis in HIRI. Methods PANoptosis-related differentially expressed genes (PDG) were obtained through the Gene Expression Omnibus database and GeneCards database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the biological pathways related to PDG. A protein-protein interaction network was constructed. Key genes were selected, and their diagnostic value was assessed and validated in the HIRI mice. Immune cell infiltration analysis was performed based on the cell-type identification by estimating relative subsets of RNA transcripts. Results A total of 16 PDG were identified. GO analysis showed that PDG were closely related to cellular metabolism. KEGG analysis indicated that PDG were mainly enriched in cellular death pathways such as apoptosis and immune-related signaling pathways such as the tumor necrosis factor signaling pathway. GSEA results showed that key genes were mainly enriched in immune-related signaling pathways such as the mitogen-activated protein kinase (MAPK) signaling pathway. Two key genes, DFFB and TNFSF10, were identified with high accuracy in diagnosing HIRI, with areas under the curve of 0.964 and 1.000, respectively. Immune infiltration analysis showed that the control group had more infiltration of resting natural killer cells, M2 macrophages, etc., while the HIRI group had more infiltration of M0 macrophages, neutrophils, and naive B cells. Real-time quantitative polymerase chain reaction results showed that compared with the Sham group, the relative expression of DFFB messenger RNA in liver tissue of HIRI group mice increased, and the relative expression of TNFSF10 messenger RNA decreased. Cibersort analysis showed that the infiltration abundance of naive B cells was positively correlated with DFFB expression (r=0.70, P=0.035), and the infiltration abundance of M2 macrophages was positively correlated with TNFSF10 expression (r=0.68, P=0.045). Conclusions PANoptosis-related genes DFFB and TNFSF10 may be potential biomarkers and therapeutic targets for HIRI.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

Bone is a highly calcified and vascularized tissue. The vascular system plays a vital role in supporting bone growth and repair, such as the provision of nutrients, growth factors, and metabolic waste transfer. Moreover, the additional functions of the bone vasculature, such as the secretion of various factors and the regulation of bone-related signaling pathways, are essential for maintaining bone health. In the bone microenvironment, bone tissue cells play a critical role in regulating angiogenesis, including osteoblasts, bone marrow mesenchymal stem cells (BMSCs), and osteoclasts. Osteogenesis and bone angiogenesis are closely linked. The decrease in osteogenesis and bone angiogenesis caused by aging leads to osteoporosis. Long noncoding RNAs (lncRNAs) are involved in various physiological processes, including osteogenesis and angiogenesis. Recent studies have shown that lncRNAs could mediate the crosstalk between angiogenesis and osteogenesis. However, the mechanism by which lncRNAs regulate angiogenesis‒osteogenesis crosstalk remains unclear. In this review, we describe in detail the ways in which lncRNAs regulate the crosstalk between osteogenesis and angiogenesis to promote bone health, aiming to provide new directions for the study of the mechanism by which lncRNAs regulate bone metabolism.
RNA, Long Noncoding/physiology* ; Osteogenesis/physiology* ; Humans ; Neovascularization, Physiologic/genetics* ; Bone and Bones/metabolism* ; Animals ; Mesenchymal Stem Cells ; Signal Transduction ; Osteoblasts ; Osteoclasts ; Angiogenesis

Objective To analyze the changes in optical coherence tomography angiography (OCTA) parameters in patients with essential hypertension，and to explore the effect of blood pressure on OCTA parameters. Methods A total of 164 patients with essential hypertension were selected and divided into controlled blood pressure group (n=92) and uncontrolled blood pressure group (n=72). OCTA examination was performed on the optic disc and macula of all patients, and the right eyes were selected for analysis. Results There were no significant differences in retinal nerve fiber layer (RNFL) thickness, radial peripapillary capillary (RPC) total vascular density, RPC total small vessel density, perifovea superficial capillary plexus (SCP) vascular density, and perifovea deep capillary plexus (DCP) vascular density between the two groups of patients. There were no significant differences in foveal avascular zone (FAZ) area, FAZ diameter, and fovea retinal thickness between the two groups of patients. The density of the parafovea SCP, parafovea DCP, and fractal dimension (FD) in the uncontrolled blood pressure group were significantly lower than those in the controlled blood pressure group (P＜0.05). Multiple linear regression analysis showed that elevation of blood pressure was a independently related factor of reduced parafovea DCP density (P＝0.026), while there was no correlation between the uncontrolled blood pressure and parafovea SCP density and FD level. Conclusions The blood pressure level is correlated with the parafovea DCP density, while has no correlation with other OCTA parameters in hypertension patients.

Atherosclerosis(AS)is an inflammatory cardiovascular disease characterized by plaque accumulation in the arterial wall,leading to increased morbidity and mortality of related cardiovascular disorders.The main pathological mechanisms of AS include lipid deposition,oxidative stress,and chronic inflammation,with disease progression involving endothelial cell dysfunction,macrophage polarization,foam cell formation,and smooth muscle cell proliferation or apoptosis.Mitochondria are essential organelles that provide energy for cellular metabolism,and the mitochondrial quality control(MQC)system is the fundamental mechanism maintaining mitochondrial functional homeostasis.MQC dysfunction can induce vascular phenotype changes through pathways such as oxidative stress,apoptosis,and inflammation,thereby promoting the progression of AS.Therefore,targeting MQC to regulate mitochondrial function may become a new direction for the treatment of AS.This review summarizes the molecular mechanisms of MQC,including mitochondrial biogenesis,mitochondrial dynamics,and mitochondrial autophagy(mitophagy),and further elucidates the role of abnormal MQC in the pathological processes of AS,aiming to provide a scientific basis for identifying potential targets to delay the progression of AS and developing related drugs.

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