ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

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*

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

Hypoxia-inducible factor (HIF-1α), a core transcription factor responding to changes in cellular oxygen levels, is closely associated with a wide range of physiological and pathological conditions. However, its differential impacts on vascular cell types and molecular programs modulating human vascular homeostasis and regeneration remain largely elusive. Here, we applied CRISPR/Cas9-mediated gene editing of human embryonic stem cells and directed differentiation to generate HIF-1α-deficient human vascular cells including vascular endothelial cells, vascular smooth muscle cells, and mesenchymal stem cells (MSCs), as a platform for discovering cell type-specific hypoxia-induced response mechanisms. Through comparative molecular profiling across cell types under normoxic and hypoxic conditions, we provide insight into the indispensable role of HIF-1α in the promotion of ischemic vascular regeneration. We found human MSCs to be the vascular cell type most susceptible to HIF-1α deficiency, and that transcriptional inactivation of ANKZF1, an effector of HIF-1α, impaired pro-angiogenic processes. Altogether, our findings deepen the understanding of HIF-1α in human angiogenesis and support further explorations of novel therapeutic strategies of vascular regeneration against ischemic damage.
Humans ; Vascular Endothelial Growth Factor A/metabolism* ; Endothelial Cells/metabolism* ; Transcription Factors/metabolism* ; Gene Expression Regulation ; Hypoxia/metabolism* ; Cell Hypoxia/physiology*

Objective To evaluate the in vitro effect of combinations of 5 β-lactam antibiotics with different β-lac-tamase inhibitors on the activity of multidrug-resistant Mycobacterium tuberculosis(MDR-TB),and identify the most effective combination of β-lactam antibiotics and β-lactamase inhibitors against MDR-TB.Methods MDR-TB strains collected in Henan Province Antimicrobial Resistance Surveillance Project in 2021 were selected.The mini-mum inhibitory concentrations(MIC)of 5 β-lactam antibiotics or combinations with different β-lactamase inhibitors on clinically isolated MDR-TB strains were measured by MIC detection method,and the blaC mutation of the strains was analyzed by polymerase chain reaction(PCR)and DNA sequencing.Results A total of 105 strains of MDR-TB were included in the analysis.MIC detection results showed that doripenem had the highest antibacterial activity against MDR-TB,with a MIC50 of 16 μg/mL.MIC values of most β-lactam antibiotics decreased significantly after combined with β-lactamase inhibitors.A total of 13.33％(n=14)strains had mutations in blaC gene,mainly 3 nu-cleotide substitution mutations,namely AGT333AGG,AAC638ACC and ATC786ATT.BlaC proteins Ser111 Arg and Asn213Thr enhanced the synergistic effect of clavulanic acid/sulbactam and meropenem on MDR-TB compared with synonymous single-nucleotide mutation.Conclusion The combination of doripenem and sulbactam has the strongest antibacterial activity against MDR-TB.Substitution mutations of BlaC protein Ser111 Arg and Asn213Thr enhances the sensitivity of MDR-TB to meropenem through the synergy with clavulanic acid/sulbactam.

Objective To explore the incidence of long CO VID symptoms in patients infected with Omicron variant of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Methods According to the inclusion and exclu-sion criteria of literatures,relevant studies without language restrictions published up to 2024 were retrieved from both Chinese and English databases.The Chinese databases were China National Knowledge Infrastructure(CNKI),Wanfang Database,and VIP databases,and the foreign databases were PubMed,Embase,and Web of Science.Three-step screening was used to select literatures,and Stata 17.0 software was used for analysis.Results The incidence of at least one sequelae in patients infected with Omicron variant was 29.62％.The most common symptoms included fatigue(19.10％),joint or muscle pain(11.06％),memory loss(9.71％),brain fog(8.80％),cough(8.42％),headache(7.26％),and sore throat(6.68％).Subgroup analysis results showed that with the extension of follow-up(3 months vs 6 months),the incidence of smell or taste changes was significantly re-duced(7.22％vs 0.78％).The higher the proportion of women(＜50％vs 50％-65％vs＞65％),the higher the incidence of joint or muscle pain(1.09％vs 4.62％vs 19.53％);the greater the median age(≥45 years vs＜45 years),the higher the incidence of chest pain or chest distress(0.90％vs 3.86％),all with statistically significant differences(all P＜0.05).Conclusion Incidence of long COVID in Omicron-infected patients is high and can cause various symptoms.Follow-up time,median age and gender proportion have significant impacts on the incidence of some symptoms.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

End-stage patients experience unbearable pain because of refractory symptoms.Palliative sedation is a form of palliative care which relieves patients' agony by lowering their consciousness.Standard palliative sedation can help patients die with dignity.It is distinct from euthanasia and does not alter the survival of patients.Sufficient palliative care is the premise of palliative sedation.Repeated and detailed clinical evaluation,as well as multidisciplinary involvement,is necessary for the standardized implementation of palliative sedation.Here,we proposed the standard process and specifications of palliative sedation in Peking Union Medical College Hospital.Furthermore,we reported a case of palliative sedation for an advanced cancer patient with refractory delirium and living pain to demonstrate its application in clinical practice.
Humans ; Anesthesia ; Pain ; Hospitals ; Palliative Care ; Universities

Objective: To analyze correlation of occupational hydrogen fluoride exposure to low doses of bone metabolism index through occupational epidemiological investigation and benchmark dose calculation. Methods: In May 2021, using cluster sampling method, 237 workers exposed to hydrogen fluoride in a company were selected as the contact group, and 83 workers not exposed to hydrogen fluoride in an electronics production company were selected as the control group. The external exposure dose and urinary fluoride concentration, blood and urine biochemical indicators of the workers was measured.The relationship between external dose and internal dose of hydrogen fluoride was analyzed. The external dose, urinary fluoride was used as exposure biomarkers, while serum osteocalcin (BGP), serum alkaline phosphatase (AKP) and urinary hydroxyproline (HYP) were used as effect biomarkers for bone metabolism of hydrogen fluoride exposure. The benchmark dose calculation software (BMDS1.3.2) was used to calculate benchmark dose (BMD) . Results: Urine fluoride concentration in the contact group was correlated with creatinine-adjusted urine fluoride concentration (r=0.69, P=0.001). There was no significant correlation between the external dose of hydrogen fluoride and urine fluoride in the contact group (r=0.03, P=0.132). The concentrations of urine fluoride in the contact group and the control group were (0.81±0.61) and (0.45±0.14) mg/L, respectively, and the difference between the two groups was statistically significant (t=5.01, P=0.025). Using BGP, AKP and HYP as effect indexes, the urinary BMDL-05 values were 1.28, 1.47 and 1.08 mg/L, respectively. Conclusion: Urinary fluoride can sensitively reflect the changes in the effect indexes of biochemical indexes of bone metabolism. BGP and HYP can be used as early sensitive effect indexes of occupational hydrogen fluoride exposure.
Humans ; Fluorides/adverse effects* ; Hydrofluoric Acid ; Benchmarking ; Biomarkers ; Occupational Exposure/adverse effects*

This study aimed to provide scientific evidence for predicting quality markers(Q-markers) of Elephantopus scaber by establishing UPLC fingerprint of E. scaber from different geographical origins and determining the content of 13 major components, as well as conducting in vitro anti-cancer activity investigation of the main components. The chromatographic column used was Waters CORTECS UPLC C_(18)(2.1 mm×150 mm, 1.6 μm), and the mobile phase consisted of acetonitrile and 0.1% formic acid solution(gradient elution). The column temperature was set at 30 ℃, and the flow rate was 0.2 mL·min~(-1). The injection volume was 1 μL, and the detection wavelength was 240 nm. The UPLC fingerprint of E. scaber was fitted using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(2012 edition) to determine common peaks, evaluate similarity, identify and determine the content of major components. The CCK-8 assay was used to explore the inhibitory effect of the main components on the proliferation of lung cancer cells. The results showed that in the established UPLC fingerprint of E. scaber, 35 common peaks were identified. Thirteen major components, including neochlorogenic acid(peak 1), chlorogenic acid(peak 2), cryptochlorogenic acid(peak 3), caffeic acid(peak 4), schaftoside(peak 6), galuteolin(peak 9), isochlorogenic acid B(peak 10), isochlorogenic acid A(peak 12), isochlorogenic acid C(peak 18), deoxyelephantopin(peak 28), isodeoxyelephantopin(peak 29), isoscabertopin(peak 31), and scabertopin(peak 32) were identified and quantified, and a quantitative analysis method was established. The results of the in vitro anti-cancer activity study showed that deoxyelephantopin, isodeoxyelephantopin, isoscabertopin, and scabertopin in E. scaber exhibited inhibition rates of lung cancer cell proliferation exceeding 80% at a concentration of 10 μmol·L~(-1), higher than the positive drug paclitaxel. These results indicate that the fingerprint of E. scaber is highly characteristic, and the quantitative analysis method is accurate and stable, providing references for the research on quality standards of E. scaber. Four sesquiterpene lactones in E. scaber show significant anti-cancer activity and can serve as Q-markers for E. scaber.
Humans ; Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal/chemistry* ; Asteraceae/chemistry* ; Lung Neoplasms/drug therapy*