Lung cancer has the highest morbidity and mortality rate among all cancers. Because of the complex pathogenesis， there are limitations in the common Western medicine treatment methods. Clinical and experimental studies have proved that traditional Chinese medicine （TCM） can not only effectively treat lung cancer and alleviate the clinical symptoms of cancer patients but also reduce the adverse reactions and complications caused by surgery， chemotherapy， and radiotherapy to improve the quality of life of the patients. The biological behaviors of lung cancer cells， such as proliferation， invasion， and metastasis， are closely related to their metabolic reprogramming. Metabolic reprogramming in lung cancer involves a series of metabolic changes such as increased glucose uptake and consumption， enhanced glycolysis， increased amino acid uptake and catabolism， and enhanced lipid and protein synthesis. Studies have reported that TCM active components， extracts， and compound prescriptions can effectively inhibit the biological behaviors of lung cancer by regulating metabolic reprogramming. Therefore， this paper reviews the pharmacological mechanisms of TCM active components， extracts， and compound prescriptions in regulating metabolic reprogramming of lung cancer， with the aim of providing a new way of thinking for the treatment of lung cancer by TCM regulation of metabolic reprogramming of lung cancer cells. The available studies suggest that TCM mainly inhibits the extracellular signal-regulated protein kinase （ERK）/c-Myc， phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR）， and hypoxia-inducible factor-α （HIF-1α） pathways. Furthermore， the expression of monocarboxylate transporter 4 （MCT4）， glucose transporter 1 （GLUT1）， pyruvate dehydrogenase （PDH）， phosphofructokinase 1 （PFK1）， pyruvate dehydrogenase kinase 1 （PDK1）， pyruvate kinase M2 （PKM2）， hexokinase （HK）， lactate dehydrogenase （LDH）， and lactate dehydrogenase A （LDHA） are inhibited. In this way， TCM inhibits the glucose uptake by lung cancer cells and glycolysis in lung cancer cells to reduce the energy metabolism of tumor cells， ultimately achieving the therapeutic effect on lung cancer.

This study aimed to explore the molecular mechanism of rubioncolin C(RuC) in inhibiting gastric cancer(GC). AGS and MGC803 cell lines were selected as cellular models. After treating the cells with RuC at different concentrations, the effects of RuC on the proliferation ability of GC cells were assessed using the CCK-8 method, real-time cellular analysis(RTCA), and colony formation assays. Transmission electron microscopy was used to observe subcellular structural changes. Immunofluorescence was applied to detect LC3 fluorescent foci. Acridine orange staining was used to evaluate the state of intracellular lysosomes. Western blot was employed to detect the expression of autophagy-related proteins LC3Ⅱ, P62, and lysosomal cathepsin D(CTSD). The SuperPred online tool was used to predict the target proteins that bound to RuC, and molecular docking analysis was conducted to identify the interaction sites between RuC and CTSD. The drug affinity responsive target stability(DARTS) assay was performed to detect the direct binding interaction between RuC and CTSD. The results showed that RuC significantly inhibited the proliferation and colony formation of GC cells at low concentrations, with 24-hour half-maximal inhibitory concentrations(IC_(50)) of 3.422 and 2.697 μmol·L~(-1) for AGS and MGC803 cells, respectively. After 24 hours of treatment with RuC at concentrations of 1, 2, and 3 μmol·L~(-1), the colony formation rates for AGS cells were 61.0%±1.5%, 28.0%±0.5%, and 18.2%±0.5%, respectively, while the rates for MGC803 cells were 56.0%±0.5%, 23.3%±1.0%, and 11.8%±1.0%, all of which were significantly reduced. Transmission electron microscopy revealed that RuC promoted an increase in autophagosome formation in GC cells. Immunofluorescence detection showed that LC3 fluorescent foci of GC cells increased with the increase in RuC dose. RuC up-regulated the expression of autophagy-related proteins LC3Ⅱ and P62 in GC cells. Acridine orange staining indicated that RuC altered the acidic environment of lysosomes. SuperPred online prediction identified CTSD as a potential target protein of RuC. Western blot analysis revealed that RuC induced the up-regulation of the inactive precursor of CTSD in GC cells. CTSD activity assays indicated that RuC reduced the activity of CTSD. Molecular docking simulations found that RuC bound to the substrate-binding region of CTSD, forming hydrogen bonds with the Tyr205 and Asp231 residues. Microscale thermophoresis and DARTS assays further confirmed that RuC directly bound to CTSD. In summary, RuC inhibits lysosomal activity by targeting and down-regulating the expression of CTSD, thereby inducing autophagosome accumulation in GC cells.
Humans ; Stomach Neoplasms/enzymology* ; Cathepsin D/chemistry* ; Cell Line, Tumor ; Molecular Docking Simulation ; Cell Proliferation/drug effects* ; Autophagosomes/metabolism* ; Autophagy/drug effects*

Based on the interleukin-17(IL-17) signaling pathway, this study explores the effect and mechanism of Bufei Decoction on Klebsiella pneumoniae pneumonia in rats. SD rats were randomly divided into the control group, model group, Bufei Decoction low-dose group(6.68 g·kg~(-1)·d~(-1)), Bufei Decoction high-dose group(13.36 g·kg~(-1)·d~(-1)), and dexamethasone group(1.04 mg·kg~(-1)·d~(-1)), with 10 rats in each group. A pneumonia model was established by tracheal drip injection of K. pneumoniae. After successful model establishment, the improvement in lung tissue damage was observed following drug administration. Core targets and signaling pathways were screened using transcriptomics techniques. Real-time fluorescence quantitative polymerase chain reaction was used to detect the mRNA expression of core targets interleukin-6(IL-6), interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and chemokine CXC ligand 6(CXCL6). Western blot was used to assess key proteins in the IL-17 signaling pathway, including interleukin-17A(IL-17A), nuclear transcription factor-κB activator 1(Act1), tumor necrosis factor receptor-associated factor 6(TRAF6), and downstream phosphorylated p38 mitogen-activated protein kinase(p-p38 MAPK), and phosphorylated nuclear factor-κB p65(p-NF-κB p65). Apoptosis of lung tissue cells was detected by terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling(TUNEL). The results showed that, compared with the control group, the model group exhibited significant pathological damage in lung tissue. The mRNA expression of IL-6, IL-1β, TNF-α, and CXCL6, as well as the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly increased, and the number of apoptotic cells was notably higher, indicating successful model establishment. Compared with the model group, both low-and high-dose groups of Bufei Decoction showed reduced pathological damage in lung tissue. The mRNA expression levels of IL-6, IL-1β, TNF-α, and CXCL6, and the protein levels of IL-17A, Act1, TRAF6, p-p38 MAPK/p38 MAPK, and p-NF-κB p65/NF-κB p65, were significantly decreased, with a significant reduction in apoptotic cells in the high-dose group. In conclusion, Bufei Decoction can effectively improve lung tissue damage and reduce inflammation in rats with K. pneumoniae. The mechanism may involve the regulation of the IL-17 signaling pathway and the reduction of apoptosis.
Animals ; Interleukin-17/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Rats ; Male ; Klebsiella pneumoniae/physiology* ; Klebsiella Infections/immunology* ; Humans ; Lung/drug effects*

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

The AP2/ERF transcription factor family is a class of transcription factors widely present in plants, playing a crucial role in regulating flowering, flower development, flower opening, and flower senescence. Based on transcriptome data from flower, leaf, and stem samples of two Lonicera macranthoides varieties, 117 L. macranthoides AP2/ERF family members were identified, including 14 AP2 subfamily members, 61 ERF subfamily members, 40 DREB subfamily members, and 2 RAV subfamily members. Bioinformatics and differential gene expression analyses were performed using NCBI, ExPASy, SOMPA, and other platforms, and the expression patterns of L. macranthoides AP2/ERF transcription factors were validated via qRT-PCR. The results indicated that the 117 LmAP2/ERF members exhibited both similarities and variations in protein physicochemical properties, AP2 domains, family evolution, and protein functions. Differential gene expression analysis revealed that AP2/ERF transcription factors were primarily differentially expressed in the flowers of the two L. macranthoides varieties, with the differentially expressed genes mainly belonging to the ERF and DREB subfamilies. Further analysis identified three AP2 subfamily genes and two ERF subfamily genes as potential regulators of flower development, two ERF subfamily genes involved in flower opening, and two ERF subfamily genes along with one DREB subfamily gene involved in flower senescence. Based on family evolution and expression analyses, it is speculated that AP2/ERF transcription factors can regulate flower development, opening, and senescence in L. macranthoides, with ERF subfamily genes potentially serving as key regulators of flowering duration. These findings provide a theoretical foundation for further research into the specific functions of the AP2/ERF transcription factor family in L. macranthoides and offer important theoretical insights into the molecular mechanisms underlying floral phenotypic differences among its varieties.
Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Transcription Factors/chemistry* ; Lonicera/classification* ; Flowers/metabolism* ; Phylogeny ; Gene Expression Profiling ; Multigene Family

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

OBJECTIVE: To investigate the metabolic characteristics of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) in myeloid leukemia by in vitro culture of myeloid leukemia cells and construction of tumor-bearing nude mouse model. METHODS: U937, THP-1, HL60 and K562 cells were cultured in vitro. The cells in logarithmic growth phase (l×10 ⁵ cells/well) were added with ¹⁸F-FDG, and the uptake rate of ¹⁸F-FDG was measured at 15, 30, 60 and 120 min after addation, respectively. The four kinds of cells were inoculated subcutaneously into the hind limbs of nude mice to establish a tumor-bearing nude mouse model. When the tumor size was about 500 mm³, ¹⁸F-FDG was injected through the tail vein of the mice, and positron emission tomography/computed tomography was performed at 60 min after injection. The morphology of tumor-bearing cells was observed by hematoxylin-eosin (HE) staining in serial pathological sections. RESULTS: After co-incubation with ¹⁸F-FDG, the ¹⁸F-FDG uptake rates of U937 cells were significantly higher than THP-1, HL60 and K562 cells at 4 time points (all P <0.05), and THP-1 cells were higher than K562 cells (all P <0.05). The uptake rate of ¹⁸F-FDG by leukemia cells was rapid in the first 60 min, then tended to be stable. Pathological analysis showed that subcutaneous inoculation of U937, THP-1, HL60 and K562 cells could successfully establish tumor-bearing nude mouse models of myeloid leukemia. The ¹⁸F-FDG uptake value in U937 tumor-bearing nude mice was significantly higher than THP-1, HL60 and K562 tumor-bearing nude mice (all P <0.01). The ¹⁸F-FDG uptake values in THP-1 and HL60 tumor-bearing nude mice were significantly higher than that in K562 tumor-bearing nude mice (both P <0.01). CONCLUSION The tumor-bearing nude mouse model of myeloid leukemia can be successfully constructed by subcutaneous inoculation. The ¹⁸F-FDG uptake rate of acute myeloid leukemia (AML) cells is higher in cells cultured in vitro and tumor-bearing nude mouse model. ¹⁸F-FDG may have better clinical application value for AML.
Animals ; Fluorodeoxyglucose F18/metabolism* ; Mice, Nude ; Mice ; Humans ; Leukemia, Myeloid/diagnostic imaging* ; HL-60 Cells ; K562 Cells ; Cell Line, Tumor ; U937 Cells

Objective:To analyze the change in human resources within China′s Centers for Disease Control and Prevention (CDC) from 2010 to 2020.Methods:The self-reported information from provincial, prefectural (city), and county (district) levels of China′s CDC, covering employee counts, staff composition, professional qualifications, educational backgrounds, technical titles, and tenure, were extracted from the China Disease Prevention and Control Information System. The demographic context was provided by the annual population figures from the China Statistical Yearbook (2010-2020). The profile of CDC personnel was described, and the average annual percentage rate change (AAPC), average annual percentage rate change (APC), human resource agglomeration degree (HRAD) and the difference between HRAD and population agglomeration degree (PAD) were calculated. The Joinpoint regression model was used to analyze the time trend.Results:The decade under review witnessed a net increase of 17 300 active and 18 300 enrolled personnel in the CDC, surpassing the national population growth rate with AAPCs of 0.93% and 1.03%, respectively. This upward trajectory was statistically significant ( P<0.05). The ratio of disease control personnel per 10 000 population escalated from 1.14 to 1.21. An initial decline in active CDC workforce density (from 1.31 to 1.27 per 10 000 population between 2010 and 2017) was followed by an increase (from 1.28 to 1.37 between 2018 and 2020), with APCs of -0.40% and 3.73%, respectively. The proportion of professional and technical staff in 2019 was highest in the eastern region (86.01%), followed by the western (83.75%) and central regions (79.54%). The period also saw an enhancement in the average academic degree (from 1.91 to 2.43 points) and professional title scores (from 1.39 to 1.53 points) of CDC personnel. While the average tenure in the eastern and western regions showed a slight decline, the central region experienced an increase, with HRAD values indicating a higher concentration in the eastern and central regions compared to the western region. The HRAD-PAD discrepancy revealed a negative value in the eastern region, nearing zero in the central and western regions. Conclusion:Between 2010 and 2020, China′s CDC experienced notable growth in human resources and underwent structural optimization, albeit with significant regional disparities in concentration.

Objective To propose a method for classifying small bowel capsule endoscopy images by combining the Swin Transformer network with an improved Adapt-RandAugment data augmentation approach,aiming to enhance the accuracy and efficiency of small bowel lesion classification and recognition.Methods An Adapt-RandAugment data augmentation approach was formulated based on the RandAugment data enhancement sub-strategy and the principles of no feature loss and no distortion when enhancing small bowel capsule endoscopy images.In the publicly available Kvasir-Capsule dataset of small bowel capsule endoscopic images,the Adapt-RandAugment data augmentation approach was trained based on the Swin Transformer network,and the convolutional neural networks ResNet152 and DenseNet161 were used as the benchmarks to validate the combined Swin Transformer network and Adapt-RandAugment data augmentation approach for small bowel capsule endoscopy image classification.Results The proposed algorithm gained advantages over ResNet152 and DenseNet161 networks in the indicators,which had the macro average precision(MAC-PRE),macro average recall(MAC-REC),macro average F1 score(MAC-Fi-S)being 0.383 2,0.314 8 and 0.290 5 respectively,the micro average precision(MIC-PRE),micro average recall(MIC-REC)and micro average F1 score(MIC-Fi-S)all being 0.755 3,and the Matthews correlation coe-fficient(MCC)being 0.452 3.Conclusion The proposed small bowel capsule endoscopy image classification method based on Swin Transformer network and Adapt-RandAugment data augmentation approach behaves well in classified recognition efficiency and accuracy.[Chinese Medical Equipment Journal,2024,45(6):9-16]

Objective To present the initial practice of a novel procedure for the surgical treatment of inguinal hernia-"lateral approach single-incision laparoscopic totally extraperitoneal(L-SILTEP)repair"in certain specific situations.Methods The clinical data of 110 inguinal hernia patients who underwent L-SILTEP in the First Affiliated Hospital of Ningbo University,Shanghai General Hospital affiliated to Shanghai Jiao Tong University School of Medicine,and Shanghai East Hospital affiliated to Tongji University from June 2021 to March 2024 were collected retrospectively.Patients' demographics,surgical details,length of hospital stay,and postoperative outcomes were analyzed respectively.Results All surgeries were completed successfully and there was no conversion.The median surgical time was 55(41.25,70)mins and the intraoperative blood loss was 5(2,10)mL.In surgery,inferior epigastric artery injury occurred in 5 cases(4.5%)and spermatic cord injury occurred in 1 case(0.9%).The mean visual analog scale(VAS)scores pain assessment at 6,24,and 48 h after surgery were 3.0±0.8,1.9±0.7 and 1.1±0.4,respectively.The duration of hospital stay was(3.3±0.7)days.The most common postoperative complication was seroma,which occurred in 9 cases(8.2%).Additionally,extraperitoneal hematoma occurred in 1 case(0.9%)and scrotum effusion in 1 case(0.9%).Conclusions Generally,L-SILTEP is safe,feasible and effective.However,due to its advanced technique-demand,the application of L-SILTEP should be patient-specific and surgeon-specific.The successful implementation of this surgical procedure necessitates extensive training and meticulous attention to the surgical details.