The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

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.

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.

Oral diseases concern almost every individual and are a serious health risk to the popula-tion.The restorative treatment of tooth and jaw defects is an important means to achieve oral function and support the appearance of the contour.Based on the principle of"learning from the nature",Deng Xu-liang's group of Peking University School and Hospital of Stomatology has proposed a new concept of"microstructural biomimetic design and tissue adaptation of tooth/jaw materials"to address the worldwide problems of difficulty in treating dentine hypersensitivity,poor prognosis of restoration of tooth defects,and vertical bone augmentation of alveolar bone after tooth loss.The group has broken through the bottle-neck of multi-stage biomimetic technology from the design of microscopic features to the enhancement of macroscopic effects,and invented key technologies such as crystalline/amorphous multi-level assembly,ion-transportation blocking,and multi-physical properties of the micro-environment reconstruction,etc.The group also pioneered the cationic-hydrogel desensitizer,digital stump and core integrated restora-tions,and developed new crown and bridge restorative materials,gradient functionalisation guided tissue regeneration membrane,and electrically responsive alveolar bone augmentation restorative membranes,etc.These products have established new clinical strategies for tooth/jaw defect repair and achieved inno-vative results.In conclusion,the research results of our group have strongly supported the theoretical im-provement of stomatology,developed the technical system of oral hard tissue restoration,innovated the clinical treatment strategy,and led the progress of the stomatology industry.

The statement of"qi transformation leading to the removal of pathogenic dampness"was recorded in Wen Bing Tiao Bian(Analysis on Epidemic Febrile Diseases)written by the Qing Dynasty physician WU Ju-Tong.Dampness in the triple energizer is caused by the dysfunction of qi transformation,and the treatment of dampness must be based on the activation of qi movement and focused on the promotion of qi movement and the restoration of the qi transformation in the triple energizer.For the treatment of dampness attack in the upper energizer,therapies of dispersing lung to smooth qi and resolving dampness to relieve the obstruction are recommended.For the treatment of dampness obstruction in the middle energizer,therapy of activating spleen qi by strengthening spleen and moving qi is stressed for helping the removal of dampness and for the eradication of the source of dampness.For the treatment of dampness stagnation in the lower energizer,therapy of draining dampness with sweet-light medicines and activating yang can be used according to the illness status.The three methods of treating dampness,namely dispersing the upper energizer,activating the middle energizer and draining the lower energizer,all embody the mechanism of"qi transformation leading to the removal of pathogenic dampness",and the therapies of dispersing lung with light medicines,inducing perspiration by opening striated layer,eliminating dampness with aromatics and draining dampness with sweet-light medicines should be used in accordance with the syndromes.The elucidation of the academic thoughts of"qi transformation leading to the removal of pathogenic dampness"can provide theoretical reference for the fundamental research of dampness syndrome and clinical application of therapies for resolving dampness in Chinese medicine.

Objective:With the in-depth study of complement dysregulation,glomerulonephritis with dominant C3 has received increasing attention,with a variety of pathologic types and large differences in symptoms and prognosis between pathologic types.This study analyzes the clinical,pathological,and prognostic characteristics of different pathological types of glomerulonephritis with dominant C3,aiming to avoid misdiagnosis and missed diagnoses. Methods:The clinical,pathological,and follow-up data of 52 patients diagnosed as glomerulonephritis with dominant C3 by renal biopsy from June 2013 to October 2022 were retrospectively analyzed.According to the clinical feature and results of pathology,15 patients with post-infectious glomerulonephritis(PIGN)and 37 patients with of non-infectious glomerulonephritis(N-PIGN)were classified.N-PIGN subgroup analysis was performed,and 16 patients were assigned into a C3-alone-deposition group and 21 in a C3-dominant-deposition group,or 27 in a C3 glomerulopathy(C3G)group and 10 in a non-C3 nephropathy(N-C3G)group. Results:The PIGN group had lower creatinine values(84.60 μmol/L vs 179.62 μmol/L,P= 0.001),lower complement C3 values(0.36 g/L vs 0.74 g/L,P<0.001)at biopsy,and less severe pathological chronic lesions compared with the N-PIGN group.In the N-PIGN subgroup analysis,the C3-dominant-deposition group had higher creatinine values(235.30 μmol/L vs 106.70 μmol/L,P=0.004)and higher 24-hour urine protein values(4 025.62 mg vs 1 981.11 mg,P=0.037)than the C3-alone-deposition group.The prognosis of kidney in the PIGN group(P=0.049),the C3-alone-deposition group(P=0.017),and the C3G group(P=0.018)was better than that in the N-PIGN group,the C3-dominant-deposition group,and the N-C3G group,respectively. Conclusion:Glomerulonephritis with dominant C3 covers a variety of pathological types,and PIGN needs to be excluded before diagnosing C3G because of considerable overlap with atypical PIGN and C3G;in addition,the deposition of C1q complement under fluorescence microscope may indicate poor renal prognosis,and relevant diagnosis,treatment,and follow-up should be strengthened.

Platycodonis Radix is the dry root of Platycodon grandiflorum of Campanulaceae, which has a variety of pharmacological effects and is a commonly used bulk Chinese medicine. In this study, the chloroplast genome sequences of six P. grandiflorum from different producing areas has been sequenced with Illumina HiSeq X Ten platform. The specific DNA barcodes were screened, and the germplasm resources and genetic diversity were analyzed according to the specific barcodes. The total length of the chloroplast genome of 6 P. grandiflorum samples was 172 260-172 275 bp, and all chloroplast genomes showed a typical circular tetrad structure and encoded 141 genes. The comparative genomics analysis and results of amplification efficiency demonstrated that trnG-UCC and ndhG_ndhF were the potential specific DNA barcodes for identification the germplasm resources of P. grandiflorum. A total of 305 P. grandiflorum samples were collected from 15 production areas in 9 provinces, for which the fragments of trnG-UCC and ndhG_ndhF were amplificated and the sequences were analyzed. The results showed that trnG-UCC and ndhG_ndhF have 5 and 11 mutation sites, respectively, and 5 and 7 haplotypes were identified, respectively. The combined analysis of the two sequences formed 13 haplotypes (named Hap1-Hap13), and Hap4 is the main genotype, followed by Hap1. The unique haplotypes possessed by the three producing areas can be used as DNA molecular tags in this area to distinguish from the germplasm resources of P. grandiflorum from other areas. The haplotype diversity, nucleotide diversity and genetic distance were 0.94, 4.79×10^-3 and 0.000 0-0.020 3, respectively, suggesting that the genetic diversity was abundant and intraspecific kinship was relatively close. This study laid a foundation for the identification of P. grandiflorum, the protection and utilization of germplasm resources, and molecular breeding.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.

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.

Gadopiclenol was used in adults and pediatric patients 2 years of age and older during magnetic resonance imaging(MRI)to detect and view lesions of the central nervous system(brain,spine,and associated tissues)and body(head and neck,chest,abdomen,pelvis,and musculoskeletal system)with abnormal vascular properties.Gadopiclenol is a new type of macrocyclic gadolinium-based contrast agent(GBCA).In this article,the molecular structure,principle of action,pharmacodynamics,pharmacokinetics,clinical studies,safety and other aspects of Gadopiclenol were reviewed,in order to introduce the current research status and existing achievements of Gadopiclenol.