With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To investigate the characteristics of imprinted differentially methylated regions (iDMRs) in placentas and their correlation with preeclampsia (PE). Methods A total of 43 healthy pregnant women (control group) and 33 pregnant women with PE (PE group) at Shanghai Putuo Maternity and Infant Hospital and International Peace Maternal and Child Health Hospital, Shanghai Jiao Tong University School of Medicine from September 2021 to September 2023 were selected. A total of 3 362 CpG sites in 62 iDMRs were analyzed in 76 placenta and 5 maternal blood samples using BisCap targeted bisulfite resequencing (BisCap-seq) assays. The CpG sites in the CpG islands of the iDMRs were assessed for their methylation levels and methylation linkage disequilibrium (MLD). Imprinted methylation haplotype blocks (iMHBs) were constructed based on MLD. The methylation levels and variablility of CpG sites and iMHBs were compared among the healthy placenta, PE placenta and blood samples. Results The CpG sites in the CpG islands of the iDMRs exhibited intermediate methylation, with adjacent sites displaying high MLD (methylation levels: 0.35-0.65, D’ ＞ 0.8). A total of 185 iMHBs were constructed using these coupled CpG sites, 60 placenta-specific iMHBs and 38 somatic iMHBs were found to be differentially methylated in the placenta compared with maternal blood (P_adj＜0.05). Twenty-seven iMHBs were identified with differentially variable methylation patterns in the placenta. The iMHBs methylation was unchanged in the PE placentas compared to the healthy placentas. Twenty-seven differentially methylated cytosines (DMCs) were identified outside the iMHBs structure, among which the methylation levels of 19 CpG sites showed statistically significant differences between the PE group and the control group (P_adj＜0.05). The quantitative results of placental compositions of maternal plasma cell-free DNA (cfDNA) using placenta-specific haplotype (PSH) were highly correlated with those estimated by a deconvolution methodology (r＝0.973, P＜0.01). Conclusions The genomic imprinting features in the PE placentas were obvious, and PSH could be a potential marker of the placenta to quantify the placental compositions of maternal plasma cfDNA.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry（UPLC-Q-Orbitrap-MS）， to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba（TPAGH）， and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group， recombinant human epidermal growth factor（rhEGF） group（4 mg·kg^-1）， and low， medium， and high dose groups of TPAGH（3.5， 7， 14 mg·kg^-1）， with 24 mice in each group. A full-thickness skin excision model was constructed， and each administration group was coated with the drug at the wound site， and the model group was treated with an equal volume of normal saline， the treatment was continued for 30 days， during which 8 mice from each group were sacrificed on days 6， 12， and 30. The healing of the wounds in the mice was observed， and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin（HE）， Masson， and Sirius red staining， and enzyme-linked immunosorbent assay（ELISA） was used to dynamically measure the contents of interleukin-6（IL-6）， tumor necrosis factor-α（TNF-α）， vascular endothelial growth factor A（VEGFA）， matrix metalloproteinase（MMP）-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH， and molecular docking of key components and targets was performed. Gene Ontology（GO） biological process analysis and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis were carried out for the related targets， so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH， including 28 phenylpropanoids， 31 tannins， 23 triterpenes， 49 flavonoids， and 15 others， and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that， compared with the model group， the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate（P<0.05）， and the number of new capillaries， number of fibroblasts， number of new skin appendages， epidermal regeneration rate， collagen deposition ratio， and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved（P<0.05， 0.01）， the levels of IL-6， TNF-α， MMP-3 and MMP-9 in the skin tissues were reduced to different degrees， while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets， including tumor protein 53（TP53）， sarcoma receptor coactivator（SRC）， protein kinase B（Akt）1， signal transducer and activator of transcription 3（STAT3）， epidermal growth factor receptor（EGFR） and so on， participating in 75 signaling pathways such as advanced glycation end-products（AGE）-receptor for AGE（AGE/RAGE） signaling pathway， phosphatidylinositol 3-kinase（PI3K）/Akt signaling pathway， mitogen-activated protein kinase（MAPK） signaling pathway. Molecular docking confirmed that the key components genistein， geraniin， and casuariin had good binding ability to TP53， SRC， Akt1， STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction， thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology， the study explores how key components may bind to targets such as TP53， Akt1 and EGFR， exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.

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.

ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.

ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.

Objective:To analyze the clinical characteristics of children with head and neck rhabdomyosarcoma (RMS) and to summarize the mid-long term efficacy of Beijing Children′s Hospital Rhabdomyosarcoma 2006 (BCH-RMS-2006) regimen and China Children′s Cancer Group Rhabdomyosarcoma 2016 (CCCG-RMS-2016) regimen.Methods:A retrospective cohort study. Clinical data of 137 children with newly diagnosed head and neck RMS at Beijing Children′s Hospital, Capital Medical University from March 2013 to December 2021 were collected. Clinical characteristic of patients at disease onset and the therapeutic effects of patients treated with the BCH-RMS-2006 and CCCG-RMS-2016 regimens were compared. The treatments and outcomes of patients with recurrence were also summarized. Survival analysis was performed by Kaplan-Meier method, and Log-Rank test was used for comparison of survival rates between groups.Results:Among 137 patients, there were 80 males (58.4%) and 57 females (41.6%), the age of disease onset was 59 (34, 97) months. The primary site in the orbital, non-orbital non-parameningeal, and parameningeal area were 10 (7.3%), 47 (34.3%), and 80 (58.4%), respectively. Of all patients, 32 cases (23.4%) were treated with the BCH-RMS-2006 regimen and 105 (76.6%) cases were treated with the CCCG-RMS-2016 regimen. The follow-up time for the whole patients was 46 (20, 72) months, and the 5-year progression free survival (PFS) and overall survival (OS) rates for the whole children were (60.4±4.4)% and (69.3±4.0)%, respectively. The 5-year OS rate was higher in the CCCG-RMS-2016 group than in BCH-RMS-2006 group ((73.0±4.5)% vs. (56.6±4.4)%, χ2=4.57, P=0.029). For the parameningeal group, the 5-year OS rate was higher in the CCCG-RMS-2016 group (61 cases) than in BCH-RMS-2006 group (19 cases) ((57.3±7.6)% vs. (32.7±11.8)%, χ2=4.64, P=0.031). For the group with meningeal invasion risk factors, the 5-year OS rate was higher in the CCCG-RMS-2016 group (54 cases) than in BCH-RMS-2006 group (15 cases) ((57.7±7.7)% vs. (30.0±12.3)%, χ2=4.76, P=0.029). Among the 10 cases of orbital RMS, there was no recurrence. In the non-orbital non-parameningeal RMS group (47 cases), there were 13 (27.6%) recurrences, after re-treatment, 7 cases survived. In the parameningeal RMS group (80 cases), there were 40 (50.0%) recurrences, with only 7 cases surviving after re-treatment. Conclusions:The overall prognosis for patients with orbital and non-orbital non-parameningeal RMS is good. However, children with parameningeal RMS have a high recurrence rate, and the effectiveness of re-treatment after recurrence is poor. Compared with the BCH-RMS-2006 regimen, the CCCG-RMS-2016 regimen can improve the treatment efficacy of RMS in the meningeal region.

Isosteviol is a tetracyclic diterpenoid compound obtained by hydrolysis of natural stevia glycoside under acidic conditions. It has many pharmacological activities, such as anti-tumor, hypoglycemic, anti-inflammatory and antibacterial. Due to its low water solubility, low activity and low bioavailability, isosteviol has poor performance. In order to overcome these shortcomings, scholars have obtained a large number of isosteviol derivatives with novel structures and excellent activity. In this paper, we review the recent progress in the research on the structure modification, biological activity, structure-activity relationship and microbial transformation of isosteviol, in order to provide a reference for the development of new drugs of isosteviol and its derivatives.

ObjectiveTo investigate the role and mechanism of action of paeoniflorin （PF） in protecting HepG2 cells induced by palmitic acid （PA）. MethodsHepG2 cells were stimulated with PA at a concentration of 250 μmol/L to establish a NAFLD model. Compound C at a concentration of 10 μmol/L was used as an inhibitor， and PF at a concentration of 25 μmol/L was used for intervention. The experiment was divided into normal group （CON group） treated with complete culture medium， model group （MOD group） treated with PA， PF treatment group （MOD+PF group） treated with PA and PF， model+inhibitor group （MOD+COM group） treated with PA and Compound C， and model+inhibitor+PF group （MOD+COM+PF group） treated with PA， Compound C， and PF. Kits were used to measure lipid deposition indicators， liver function parameters， oxidative stress indicators， and inflammation indicators； oil red O staining was used to observe lipid deposition； Western Blot was used to measure the protein expression levels of AMPK， SIRT1， PGC-1α， mTOR， Beclin-1， LC3， and P62 in cells. The one-way analysis of variance was used for comparison of quantitative data between groups， while the Tukey’s test was used for comparison between two groups. ResultsCompared with the MOD group， PF improved the levels of TC and TG （P<0.05）， reduced the levels of ALT， AST， CRP， TNF-α， IL-1β， and IL-6 （P<0.05）， increased the activity of SOD and CAT and the level of GSH， and reduced the level of MDA in cells （all P<0.05）. Oil red O staining showed that PF alleviated lipid deposition in cells. Western blot results showed that compared with the MOD group， PF increased the protein expression levels of p-AMPK， SIRT1， PGC-1α， LC3Ⅱ/LC3Ⅰ， and Beclin-1 and reduced the protein expression levels of p-mTOR and P62 （all P<0.05）. ConclusionPF can inhibit PA-induced oxidative stress and inflammatory response in HepG2 cells， improve lipid deposition， and promote autophagy via the AMPK/SIRT1/PGC-1α/mTOR signaling pathway.