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.

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*

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.

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.

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*

Objective: To investigate the association between gestational diabetes mellitus (GDM) and preterm birth subtypes. Methods: Based on the cohort of pregnant women in Anqing Prefectural Hospital, the pregnant women who received prenatal screening in the first or second trimesters were recruited into baseline cohorts; and followed up for them was conducted until delivery, and the information about their pregnancy status and outcomes were obtained through electronic medical record system and questionnaire surveys. The log-binomial regression model was used to explore the association between GDM and preterm birth [iatrogenic preterm birth, spontaneous preterm birth (preterm premature rupture of membranes and preterm labor)]. For multiple confounding factors, the propensity score correction model was used to compute the adjusted association. Results: Among the 2 031 pregnant women with a singleton delivery, the incidence of GDM and preterm birth were 10.0% (204 cases) and 4.4% (90 cases) respectively. The proportions of iatrogenic preterm birth and spontaneous preterm birth in the GDM group (n=204) were 1.5% and 5.9% respectively, while the proportions in non-GDM group (n=1 827) were 0.9% and 3.2% respectively, and the difference in the proportion of spontaneous preterm birth between the two groups was significant (P=0.048). Subtypes of spontaneous preterm were further analyzed, and the results showed that the proportions of preterm premature rupture of membranes and preterm labor in the GDM group were 4.9% and 1.0% respectively, while the proportions in the non-GDM group were 2.1% and 1.1% respectively. It showed that the risk of preterm premature rupture of membranes in GDM pregnant women was 2.34 times (aRR=2.34, 95%CI: 1.16-4.69) higher than that in non-GDM pregnant women. Conclusions: Our results showed that GDM might increase the risk of preterm premature rupture of membranes. No significant increase in the proportion of preterm labor in pregnant women with GDM was found.
Infant, Newborn ; Female ; Pregnancy ; Humans ; Premature Birth ; Diabetes, Gestational ; Obstetric Labor, Premature ; Hospitals ; Iatrogenic Disease

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*

OBJECTIVE: To determine the feasibility of conducting a full-scale randomized controlled trial (RCT) and investigate the basic information and safety of acupuncture for patients with chronic spontaneous urticaria (CSU). METHODS: A total of 80 participants with CSU from July 2018 to July 2019 were randomly assigned to receive active acupuncture (n=41) on a fixed prescription of acupoints or sham acupuncture (n=39) with superficial acupuncture on non-acupuncture points through the completely randomized design. Patients in both groups received 5 sessions per week for 2 weeks, and participants were followed for a further 2 weeks. Feasibility was assessed by recruitment and randomization rates, retention of participants, treatment protocol adherence, and the incidence of adverse events (AEs). The clinical primary outcome was the changes from baseline weekly urticaria activity scores (UAS7) after treatment at 2 weeks. Secondary outcomes included the Visual Analogue Scale (VAS) score of itching intensity, Dermatology Life Quality Index (DLQI), Hamilton Depression Scale (HAMD), and Hamilton Anxiety Scale (HAMA). RESULTS: A total of 80 participants were enrolled. The recruitment rate of 24.02%, randomization rate of 100%, a loss rate of 6.25%, and no obvious AEs were observed in either group. The decrease from baseline in the mean UAS7 total score at week 2 in the active acupuncture group was -8.63 (95%CI, -11.78 to -5.49) and -6.21 (95%CI, -9.43 to -2.98) in the sham acupuncture group for a between-group difference of -2.42 (95% CI, -6.93 to 2.07). The change in the DLQI, VAS of itching intensity, HAMA, and HAMD were a slightly better improvement trend in the active acupuncture group than the sham acupuncture group, but the between-group difference was not significant. CONCLUSIONS Active acupuncture had a better improvement trend in alleviating symptoms, improving quality of life and regulating the mood of anxiety and depression in patients with CSU than sham acupuncture. (Registration Nos. AMCTR-ICR-18000190 and ChiCTR2100054776).