The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Molecular Structure ; Asteraceae/chemistry* ; Chromatography, High Pressure Liquid ; Magnetic Resonance Spectroscopy

In this study, lipopolysaccharide(LPS), ovalbumin(OVA), and compound 48/80(C48/80) were administered to establish non-infectious pneumonia models under simulated clinical conditions, and the correlation between their pathological characteristics and traditional Chinese medicine(TCM) syndromes was compared, providing the basis for the selection of appropriate animal models for TCM efficacy evaluation. An acute pneumonia model was established by nasal instillation of LPS combined with intraperitoneal injection for intensive stimulation. Three doses of OVA mixed with aluminum hydroxide adjuvant were injected intraperitoneally on days one, three, and five and OVA was administered via endotracheal drip for excitation on days 14-18 to establish an OVA-induced allergic pneumonia model. A single intravenous injection of three doses of C48/80 was adopted to establish a C48/80-induced pneumonia model. By detecting the changes in peripheral blood leukocyte classification, lung tissue and plasma cytokines, immunoglobulins(Ig), histamine levels, and arachidonic acid metabolites, the multi-dimensional analysis was carried out based on pathological evaluation. The results showed that the three models could cause pulmonary edema, increased wet weight in the lung, and obvious exudative inflammation in lung tissue pathology, especially for LPS. A number of pyrogenic cytokines, inclading interleukin(IL)-6, interferon(IFN)-γ, IL-1β, and IL-4 were significantly elevated in the LPS pneumonia model. Significantly increased levels of prostacyclin analogs such as prostaglandin E2(PGE2) and PGD2, which cause increased vascular permeability, and neutrophils in peripheral blood were significantly elevated. The model could partly reflect the clinical characteristics of phlegm heat accumulating in the lung or dampness toxin obstructing the lung. The OVA model showed that the sensitization mediators IgE and leukotriene E4(LTE4) were increased, and the anti-inflammatory prostacyclin 6-keto-PGF2α was decreased. Immune cells(lymphocytes and monocytes) were decreased, and inflammatory cells(neutrophils and basophils) were increased, reflecting the characteristics of "deficiency", "phlegm", or "dampness". Lymphocytes, monocytes, and basophils were significantly increased in the C48/80 model. The phenotype of the model was that the content of histamine, a large number of prostacyclins(6-keto-PGE1, PGF2α, 15-keto-PGF2α, 6-keto-PGF1α, 13,14-D-15-keto-PGE2, PGD2, PGE2, and PGH2), LTE4, and 5-hydroxyeicosatetraenoic acid(5S-HETE) was significantly increased, and these indicators were associated with vascular expansion and increased vascular permeability. The pyrogenic inflammatory cytokines were not increased. The C48/80 model reflected the characteristics of cold and damp accumulation. In the study, three non-infectious pneumonia models were constructed. The LPS model exhibited neutrophil infiltration and elevated inflammatory factors, which was suitable for the efficacy study of TCM for clearing heat, detoxifying, removing dampness, and eliminating phlegm. The OVA model, which took allergic inflammation as an index, was suitable for the efficacy study of Yiqi Gubiao formulas. The C48/80 model exhibited increased vasoactive substances(histamine, PGs, and LTE4), which was suitable for the efficacy study and evaluation of TCM for warming the lung, dispersing cold, drying dampness, and resolving phlegm. The study provides a theoretical basis for model selection for the efficacy evaluation of TCM in the treatment of pneumonia.
Animals ; Disease Models, Animal ; Mice ; Pneumonia/genetics* ; Medicine, Chinese Traditional ; Male ; Humans ; Cytokines/immunology* ; Female ; Lipopolysaccharides/adverse effects* ; Lung/drug effects* ; Drugs, Chinese Herbal ; Ovalbumin ; Mice, Inbred BALB C

OBJECTIVES: To summarize the clinical characteristics, diagnosis, and treatment outcomes of neonatal venous thrombosis. METHODS: A retrospective analysis was conducted on the clinical data of 11 neonates with venous thrombosis admitted to the Department of Neonatology of Anhui Children's Hospital from January 2019 to September 2024. The clinical characteristics, diagnostic approaches, treatments, and outcomes were analyzed. RESULTS: Among the 11 neonates diagnosed with venous thrombosis, 5 were male, and 6 were preterm infants, with a median gestational age of 35⁺⁶ weeks, birth weight of (2 322±1 069) g, and admission temperature of (36.6±0.4)°C. The median age at symptom onset was 6 days. Of the 11 cases, 8 limb venous thromboses and 1 portal vein thrombosis were confirmed by vascular ultrasound, and 2 cases of intracranial venous sinus thrombosis were confirmed by magnetic resonance imaging. Ten cases received low molecular weight heparin for anticoagulation, with a treatment duration of (24±15) days; 2 cases were treated with urokinase thrombolysis, and 4 cases received fresh frozen plasma transfusion. Thrombosis resolved in 7 cases before discharge. Partial resolution occurred in 2 cases before discharge (1 continued outpatient treatment until resolution and 1 resolved during follow-up). One case was transferred to another hospital after 1 day of treatment and was discharged after thrombosis reduction. No adverse reactions such as bleeding were observed. One neonate with cerebral infarction at admission did not receive heparin anticoagulation and was followed up as an outpatient. CONCLUSIONS Vascular ultrasound is the most commonly used diagnostic method for neonatal venous thrombosis. Heparin anticoagulation is the recommended treatment. The overall prognosis of neonatal venous thrombosis is favorable.
Humans ; Male ; Venous Thrombosis/drug therapy* ; Infant, Newborn ; Female ; Retrospective Studies

BACKGROUND: It is inaccurate to reflect the level of dust exposure through working years. Furthermore, identifying a predictive indicator for lung function decline is significant for coal miners. The study aimed to explored whether club cell secretory protein (CC16) levels can reflect early lung function changes. METHODS: The cumulative respiratory dust exposure (CDE) levels of 1,461 coal miners were retrospectively assessed by constructed a job-exposure matrix to replace working years. Important factors affecting lung function and CC16 were selected by establishing random forest models. Subsequently, the potential of CC16 to reflect lung injury was explored from multiple perspectives. First, restricted cubic spline (RCS) models were used to compare the trends of changes in lung function indicators and plasma CC16 levels after dust exposure. Then mediating analysis was performed to investigate the role of CC16 in the association between dust exposure and lung function decline. Finally, the association between baseline CC16 levels and follow-up lung function was explored. RESULTS: The median CDE were 35.13 mg/m³-years. RCS models revealed a rapid decline in forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), and their percentages of predicted values when CDE exceeded 25 mg/m³-years. The dust exposure level (<5 mg/m³-years) causing significant changes in CC16 was much lower than the level (25 mg/m³-years) that caused changes in lung function indicators. CC16 mediated 11.1% to 26.0% of dust-related lung function decline. Additionally, workers with low baseline CC16 levels experienced greater reductions in lung function in the future. CONCLUSIONS CC16 levels are more sensitive than lung indicators in reflecting early lung function injury and plays mediating role in lung function decline induced by dust exposure. Low baseline CC16 levels predict poor future lung function.
Uteroglobin/blood* ; Humans ; Dust/analysis* ; Occupational Exposure/analysis* ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Lung Injury/chemically induced* ; Coal Mining ; Biomarkers/blood* ; China/epidemiology* ; Air Pollutants, Occupational ; Female

OBJECTIVES: The purinergic receptor P2X2 (P2RX2) encodes an ATP-gated ion channel permeable to Na⁺, K⁺, and especially Ca²⁺. Loss-of-function mutations in P2RX2 are known to cause autosomal dominant nonsyndromic deafness 41 (DFNA41), which manifests as high-frequency hearing loss, accelerated presbycusis, and increased susceptibility to noise-induced damage. Zebrafish, owing to their small size, rapid development, high fecundity, transparent embryos, and high gene conservation with humans, provide an ideal model for studying human diseases and developmental mechanisms. This study aims to generate a p2rx2 knockout zebrafish model using CRISPR/Cas9 gene editing system to investigate the effect of p2rx2 deficiency on the auditory system, providing a basis for understanding P2RX2-related hearing loss and developing gene therapy strategies. METHODS: Two CRISPR targets (sgRNA1 and sgRNA2) spaced 47 bp apart were designed within the zebrafish p2rx2 gene. Synthesized sgRNAs and Cas9 protein were microinjected into single-cell stage Tübingen (TU)-strain zebrafish embryos. PCR and gel electrophoresis verified editing efficiency at 36 hours post-fertilization (hpf). Surviving embryos were raised to adulthood (F0), tail-clipped, genotyped, and screened for positive mosaics. F1 heterozygotes were generated by outcrossing, and F2 homozygous mutants were obtained by intercrossing. Polymerase chain reaction (PCR) combined with sequencing verified mutation type and heritability. At 5 days post-fertilization (dpf), YO-PRO-1 staining was used to examine hair cell morphology and count in lateral line neuromasts and the otolith region. Auditory evoked potential (AEP) thresholds at 600, 800, 1 000, and 2 000 Hz were measured in nine 4-month-old wild type and mutant zebrafish per group. RESULTS: A stable p2rx2 knockout zebrafish line was successfully established. Sequencing revealed a 66 bp insertion at the first target site introducing a premature stop codon (TAA), leading to early termination of protein translation and loss of function. Embryos developed normally with no gross malformations. At 5 dpf, mutants exhibited significantly reduced hair cell density in the otolith region compared with wild type, although lateral line neuromasts were unaffected. AEP testing showed significantly elevated auditory thresholds at all 4 frequencies in homozygous mutants compared with wild type (all P<0.001), indicating reduced hearing sensitivity. CONCLUSIONS We successfully generated a p2rx2 loss-of-function zebrafish model using CRISPR/Cas9 technology. p2rx2 deficiency caused hair cell defects in the otolith region and increased auditory thresholds across frequencies, indicating its key role in maintaining zebrafish auditory hair cell function and hearing perception. The phenotype's restriction to the otolith region suggests tissue-specific roles of p2rx2 in sensory organs. This model provides a valuable tool for elucidating the molecular mechanisms of P2RX2-related hearing loss and for screening otoprotective drugs and developing gene therapies.
Animals ; Zebrafish/genetics* ; Receptors, Purinergic P2X2/deficiency* ; CRISPR-Cas Systems/genetics* ; Gene Knockout Techniques ; Phenotype ; Zebrafish Proteins/genetics* ; Disease Models, Animal

As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

OBJECTIVE: The role of cold spells of different intensities in the economic burden of death is crucial for health adaptation to climate change, especially in a multi-site setting. The objective of the study was to explore the economic burden of mortality attributable to cold spells. METHODS: We performed a two-stage time-series analysis using the Value of Statistical Life (VSL) approach to evaluate the economic impact of mortality related to cold spells of varying lengths and intensities. This analysis employed a case-crossover design, with a distributed lag nonlinear model (DLNM) used for analysis. Analysis was stratified according to age, sex, and region of origin. The results of the assessment show that cold spells have an enormous impact on the economic losses of mortality due to climate change and aging. RESULTS: Totally, 8.3% (95% CI: 0.0%, 16.0%) to 13.8% (95% CI: 1.0%, 24.8%) of VSL were ascribed to cold spells, accounting for economic losses of 4.71 (95% CI: 0.34, 8.47) to 11.45 (95% CI: 0.00, 21.00) billion CNY, in the cold season. The population aged over 65 y and females are particularly vulnerable. Economic impacts in warmer regions, such as the southern and subtropical zones, are more extensive than those in the northern and temperate zones. CONCLUSION Customizing cold spell prevention measures for vulnerable populations or regions is vital to alleviating the socioeconomic burden.
China/epidemiology* ; Humans ; Female ; Male ; Cold Temperature/adverse effects* ; Aged ; Middle Aged ; Adult ; Mortality ; Infant ; Child ; Adolescent ; Child, Preschool ; Young Adult ; Climate Change ; Aged, 80 and over ; Cost of Illness ; Infant, Newborn

Microplastics are widely present in various environments such as water bodies,land,and atmosphere,which pose threats to the ecological environment and human health through transmission and accumulation in the food chain.The existing detection techniques for microplastics face challenges such as complex preparation procedure of samples,low efficiency in processing large batches of samples,and difficulties in handling complex samples.Therefore,there is an urgent need for rapid and efficient detection techniques suitable for complex microplastics samples in the field of environmental monitoring.Raman spectroscopy,known for its advantages such as rapidity,accuracy,high sensitivity,non-destructiveness,and non-contact,demonstrates great application potential in detection of microplastics.Deep learning,an artificial intelligence method known for its large-scale data processing,nonlinear modeling and automatic feature extraction capabilities,is receiving increasing attention in the analysis of Raman spectroscopy signals.The application of deep learning-based Raman spectroscopy has significantly improved performance indicators such as detection efficiency and accuracy.This article introduced the existing Raman enhancement techniques,summarized the deep learning methods applied in Raman spectroscopy signal analysis,reviewed the recent research and application progress of deep learning-based Raman spectroscopy in detection of microplastics,and finally discussed the challenges and future prospects of deep learning-based Raman spectroscopy in detection of microplastics.