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.

Social behavior is extremely important for the physical and mental health of individuals, their growth and development, and for social development. Social behavioral disorders have become a typical clinical representation of a variety of psychiatric disorders and have serious adverse effects on the development of individuals. The prefrontal cortex, as one of the key areas responsible for social behavior, involves in many advanced brain functions such as social behavior, emotion, and decision-making. The neural activity of prefrontal cortex has a major impact on the performance of social behavior. Numerous studies demonstrate that neurons and glial cells can regulate certain social behaviors by themselves or the interaction which we called neural microcircuits; and the collaboration with other brain regions also regulates different types of social behaviors. The prefrontal cortex (PFC)-thalamus projections mainly influence social dominance and social preference; the PFC-amygdala projections play a key role in fear behavior, emotional behavior, social exploration, and social identification; and the PFC-nucleus accumbens projections mainly involve social preference, social memory, social cognition, and spatial-social associative learning. Based on the above neural mechanism, many studies have focused on applying the non-invasive neurostimulation to social deficit-related symptoms, including transcranial magnetic stimulation (TMS), transcranial electrical stimulation (TES) and focused ultrasound stimulation (FUS). Our previous study also investigated that repetitive transcranial magnetic stimulation can improve the social behavior of mice and low-intensity focused ultrasound ameliorated the social avoidance behavior of mice by enhancing neuronal activity in the prefrontal cortex. In this review, we summarize the relationship between neurons, glial cells, brain projection and social behavior in the prefrontal cortex, and systematically show the role of the prefrontal cortex in the regulation of social behavior. We hope our summarization will provide a reference for the neural mechanism and effective treatment of social disorders.

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.

Aim To investigate the regulatory role and mechanism of resveratrol in inhibiting autophagy and promoting apoptosis in choroidal melanoma cells. Methods Choroidal melanoma cells (MUM2B) were divided into control and experimental groups, and treated with different concentrations of resveratrol (0, 10, 20,40,60,80 μmol ·L

The tannin content of sorghum seeds had a significant impact on the wine's quality during the brewing process.Additionally,when used as a feed ingredient,the tannin content had a major impact on feed consumption.Thus the tannin content of sorghum has a substantial impact on its quality and application.To quickly and nondestructively determine the tannin content of sorghum,near-infrared spectroscopy was combined with chemometrics in this study,which eliminated the need for time-consuming and costly conventional approaches.Following the spectra's preprocessing,anomalous samples were removed by using a combination of Gaussian process regression(GPR)and Monte Carlo cross-validation(MCCV).The sample set was then randomly divided into a modeling set and a prediction set,with feature wavelength selection carried out using the elimination of uninformative variables(UVE)method.Subsequently,a GPR model was developed,and its performance was compared with partial least squares regression(PLSR)and support vector machine regression(SVR)models.The results indicated that the GPR model outperformed the PLSR and SVR models in all aspects.The optimized GPR model,generated following pre-processing process such as Detrending and Savitzky-Golay smoothing,elimination of anomalous samples,and selection of feature wavelengths,demonstrated superior performance,with model set determination coefficient(Rc2),prediction set determination coefficient(RP2),and relative percent deviation(RPD)values of 0.9979,0.9529,and 4.8453,respectively.These findings validated the effectiveness of the GPR regression model,which integrated near-infrared spectroscopy with chemometrics,for the rapid and non-destructive detection of sorghum tannins.

Pulmonary fibrosis(PF)is a chronic progressive end-stage lung disease.However,the mechanisms un-derlying the progression of this disease remain elusive.Presently,clinically employed drugs are scarce for the treatment of PF.Hence,there is an urgent need for developing novel drugs to address such diseases.Our study found for the first time that a natural source of Prismatomeris connata Y.Z.Ruan(Huang Gen,HG)ethyl acetate extract(HG-2)had a significant anti-PF effect by inhibiting the expression of the transforming growth factor beta 1/suppressor of mothers against decapentaplegic(TGF-β1/Smad)pathway.Network pharmacological analysis suggested that HG-2 had effects on tyrosine kinase phosphorylation,cellular response to reactive oxygen species,and extracellular matrix(ECM)disassembly.Moreover,mass spec-trometry imaging(MSI)was used to visualize the heterogeneous distribution of endogenous metabolites in lung tissue and reveal the anti-PF metabolic mechanism of HG-2,which was related to arginine biosyn-thesis and alanine,asparate and glutamate metabolism,the downregulation of arachidonic acid meta-bolism,and the upregulation of glycerophospholipid metabolism.In conclusion,we elaborated on the relationship between metabolite distribution and the progression of PF,constructed the regulatory metabolic network of HG-2,and discovered the multi-target therapeutic effect of HG-2,which might be conducive to the development of new drugs for PF.

Objective To compare the efficacies of retrograde tibial nailing(RTN)versus minimally invasive percutaneous plate osteosynthesis(MIPPO)in the treatment of distal tibial fractures.Methods A retrospective analysis was conducted on the clinical data of 55 patients with distal tibial fractures who underwent surgery in our hospital.Patients were divided into two groups based on the different surgical methods,patients in the RTN group(n=25)were treated with RTN,and patients in the MIPPO group(n=30)were treated with MIPPO.The surgical parameters(operation time,intraoperative blood loss,intraoperative fluoroscopy times,and success rate of closed reduction),fracture healing time,ankle dorsiflexion range of motion and American Orthopaedic Foot and Ankle Society(AOFAS)ankle-hindfoot scores 6 months after operation and at the last follow-up,and the incidence of complications during perioperative period and follow-up were compared between the two groups.Results The operation time,intraoperative blood loss,and intraoperative fluoroscopy times in the RTN group were significantly shorter/less than those in the MIPPO group(P＜0.05).The ankle dorsiflexion range of motion and AOFAS ankle-hindfoot score 6 months after operation in the RTN group were significantly greater/higher than those in the MIPPO group(P＜0.05).There was no statistically significant difference in the fracture healing time,or ankle dorsiflexion range of motion and AOFAS ankle-hindfoot score at the last follow-up between the two groups(P＞0.05).The success rate of closed reduction in the RTN group was 72.00％,which was lower than that of 96.67％in the MIPPO group(P＜0.05).The incidence of soft tissue-related complications in the RTN group was signifi-cantly lower than that in the MIPPO group(P＜0.05),while there was no statistically significant difference in the overall incidence of complica-tions between the two groups(P＞0.05).Conclusion RTN is an effective minimally invasive surgical technique for the treatment of distal tibial fractures,characterized by minimal trauma,low incidence of soft tissue complications,and fast recovery of joint function compared with MIPPO.

Through reviewing the ancient and modern literature， the name， origin， producing area， quality evaluation， harvesting and processing methods of Trichosanthis Fructus（TF） and Trichosanthis Radix（TR） in famous classical formulas were systematically sorted out following the chronological order. The results showed that there were many nicknames of TF and TR， and Gualou and Tianhuafen have become the mainstream names for its fruit and root， respectively. Both of them took Trichosanthes kirilowii as the mainstream base. TF and TR have been used as medicines in the Han dynasty， and since the North and South dynasties， Leigong Paozhilun had been clear that the effects of peels， seeds， stems， roots were different. TF was used as medicine with intact fruits， harvested after maturity from September to October， hung and dried in the shade， and its quality has been summarized in recent times as being best for those who are mature， large， thick and pliable peels， orange-yellow in color， and with sufficient sugary properties. In ancient times， the processing of TR was mostly crushed or shredded with the peels and seeds， or processing for pancakes and creams. TR was used as medicine with the roots， it is harvested from November to December， peeled and dried in the sun， and its quality was best when it was deep in the soil， large， white， powdery， firm and delicate with few muscles and veins， and it was considered to be toxic when it was born in briney land. Processing method of TR was to do powder into the medicine in the Tang dynasty， and gradually evolved into direct slicing use in the Ming and Qing dynasties. Since the modern era， the authentic producing areas of TF and TR were in the vicinity of Lingbao， Henan province， known as Anyang Huafen， and in modern times， there are well-known production areas such as Anguo， which produces Qihuafen， and Jinan， which produces Changqing Gualou. In the Song dynasty， there was a habit of substituting Trichosanthis Semen for the whole herb， which was later corrected by the materia medica in Ming dynasty. Based on the results， It is suggested that T. kirilowii be selected as the basal plant for the development of famous classical formulas involving TR and TF. In Qingjin Huatantang， Trichosanthis Semen is processed by stir-frying method， while TR and TF in other five formulas from the Catalogue of Ancient Famous Classical Formulas（The First Batch） were all used in raw form.

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 derive the Chinese medicine (CM) syndrome classification and subgroup syndrome characteristics of ischemic stroke patients. METHODS: By extracting the CM clinical electronic medical records (EMRs) of 7,170 hospitalized patients with ischemic stroke from 2016 to 2018 at Weifang Hospital of Traditional Chinese Medicine, Shandong Province, China, a patient similarity network (PSN) was constructed based on the symptomatic phenotype of the patients. Thereafter the efficient community detection method BGLL was used to identify subgroups of patients. Finally, subgroups with a large number of cases were selected to analyze the specific manifestations of clinical symptoms and CM syndromes in each subgroup. RESULTS: Seven main subgroups of patients with specific symptom characteristics were identified, including M3, M2, M1, M5, M0, M29 and M4. M3 and M0 subgroups had prominent posterior circulatory symptoms, while M3 was associated with autonomic disorders, and M4 manifested as anxiety; M2 and M4 had motor and motor coordination disorders; M1 had sensory disorders; M5 had more obvious lung infections; M29 had a disorder of consciousness. The specificity of CM syndromes of each subgroup was as follows. M3, M2, M1, M0, M29 and M4 all had the same syndrome as wind phlegm pattern; M3 and M0 both showed hyperactivity of Gan (Liver) yang pattern; M2 and M29 had similar syndromes, which corresponded to intertwined phlegm and blood stasis pattern and phlegm-stasis obstructing meridians pattern, respectively. The manifestations of CM syndromes often appeared in a combination of 2 or more syndrome elements. The most common combination of these 7 subgroups was wind-phlegm. The 7 subgroups of CM syndrome elements were specifically manifested as pathogenic wind, pathogenic phlegm, and deficiency pathogens. CONCLUSIONS There were 7 main symptom similarity-based subgroups in ischemic stroke patients, and their specific characteristics were obvious. The main syndromes were wind phlegm pattern and hyperactivity of Gan yang pattern.
Humans ; Syndrome ; Ischemic Stroke ; Medicine, Chinese Traditional ; Liver ; Phenotype