In recent years, cancer treatment methods and means are becoming more and more diversified, and single treatment methods often have limited efficacy, while the synergistic effect of immunity combined with chemotherapy can inhibit tumor growth more effectively. Based on this, we constructed a sodium alginate hydrogel composite system loaded with chemotherapeutic agents and tumor vaccines (named SA-DOX-NA) with a view to the combined use of chemotherapeutic agents and tumor vaccines. Firstly, the tumor vaccine (named NA) degradable under acidic conditions was constructed by in situ polymerization using chicken ovalbumin (OVA), acrylamide (AAM) and 2-(dimethylamino) ethyl methacrylate (DMAEMA) monomer. Then a hydrogel composite system SA-DOX-NA co-loaded with chemotherapeutic drug doxorubicin (DOX) and NA was prepared using sodium alginate as a matrix. The results showed that SA-DOX-NA had good in situ gel-forming ability and formed a mesh structure that could realize the co-loading of DOX and NA as well as the slow drug release. The electron microscopy results showed that SA-DOX-NA had good in situ gel-forming ability with good internal connectivity, and the three-dimensional mesh structure could realize the co-loading of DOX and NA as well as the slow drug release. The antitumor and immunomodulatory results showed that SA-DOX-NA both effectively inhibited the growth of tumor cells and efficiently promoted the proliferation and activation of DC2.4 dendritic cells without additional adjuvant. In summary, SA-DOX-NA exerts the dual efficacy of chemotherapy and immunotherapy for tumor treatment, and has a good application prospect in local tumor treatment.

Five saponins were isolated from the kernels of Momordica cochinchinensis, by macroporous resin, silica gel, ODS column chromatography, and semi preparative HPLC. Based on MS and NMR analysis, combining with alkaline hydrolysis and acid hydrolysis, their structures were identified as: gypsogenin-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (1), quillaic acid-3-O-{β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonosyl}-28-O-β-D-xylopyranosyl (1→3)-[β-D-xylopyranosyl (1→4)]-α-L-rhamnopyranosyl (1→2)-β-D-fucopyranoside (2), gypsogenin-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (3), quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside sodium (4), 18α-quillaic acid-3-O-β-D-galactopyranosyl (1→2)-[α-L-rhamnopyranosyl (1→3)]-β-D-glucuropyranonoside (5). Compounds 1-5 were new compounds, and named as mubezhisides A, B, C, D, E, respectively. They all could obviously inhibited the growth of Candida albicans, C. parapsilosis, and C. tropicalis.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

ObjectiveTo investigate the antidepressant effects and mechanisms of total flavonoids from Cuscutae Semen （TFCC） in the mouse model of chronic unpredictable mild stress （CUMS）. MethodsFifty male 4-week-old ICR mice were randomized into five groups （n=10 per group）： blank control， model， Cuscutae Semen decoction （10.2 g·kg^-1·d^-1）， paroxetine （2.6 mg·kg^-1·d^-1）， and TFCC （173.2 mg·kg^-1·d^-1）. The other groups except the blank control group underwent chronic unpredictable mild stress （CUMS） for 4 weeks. Behavioral assessments were conducted post-modeling. Then， the model group received distilled water （10 mL·kg^-1·d^-1）， while treatment groups were administrated with respective agents via oral gavage （10 mL·kg^-1） for 4 weeks. Depression-like behaviors were evaluated by the sucrose preference test （SPT）， forced swimming test （FST）， and tail suspension test （TST）. Hippocampal neuronal morphology was observed via hematoxylin-eosin staining， and apoptosis in the brain tissue was assessed via terminal- deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was employed to measure the hippocampal levels of inflammatory cytokines ［interleukin （IL）-1β， IL-6， and TNF-α）］ and neurotransmitters ［5-hydroxytryptamine （5-HT）， dopamine （DA）， and brain-derived neurotrophic factor （BDNF）］， while the reactive oxygen species （ROS） levels were quantified via the DCFH-DA probe. Real-time PCR was performed to measure the mRNA levels of NOD-like receptor protein 3 （NLRP3）， apoptosis-associated Speck-like protein containing a CARD （ASC）， cysteinyl aspartate-specific proteinase-1 （Caspase-1）， IL-1β， and inducible nitric oxide synthase （iNOS）. Western blot was employed to evaluate the protein levels of NLRP3， ASC， Caspase-1， uncoupling protein 2 （UCP2）， and thioredoxin-interacting protein （TXNIP）. ResultsCompared with the blank control group， the model group exhibited weight loss （P<0.01）， reduced sucrose preference （P<0.01）， prolonged immobility time in FST and TST （P<0.01）， neuron disarrangement with nuclear pyknosis in hippocampal CA3 region， increased apoptosis in the brain tissue， elevated levels of IL-1β， IL-6， and TNF-α （P<0.01）， declined levels of 5-HT， DA， and BDNF （P<0.01）， increased ROS accumulation （P<0.01）， upregulated mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， down-regulated protein level of UCP2 （P<0.01）， and up-regulated protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Compared with the model group， the interventions restored sucrose preference （P<0.01）， shortened immobility time （P<0.01）， repaired hippocampal neuronal structure， reduced apoptosis， lowered the levels of inflammatory cytokines （P<0.01）， restored the levels of neurotransmitters （P<0.01）， alleviated ROS accumulation （P<0.01）， downregulated the mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， upregulated the protein level of UCP2 （P<0.01）， and reduced the protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Moreover， TFCC outperformed Cuscutae Semen decoction in ameliorating depressive behaviors. TFCC excelled in neuronal repair， neurotransmitter regulation， anti-inflammatory effects， and modulation of the UCP2/TXNIP/NLRP3 pathway （P<0.05）. ConclusionTFCC modulates the hippocampal UCP2/TXNIP/NLRP3 pathway to inhibit inflammasome activation， reduce oxidative stress， restore neurotransmitters， thus suppressing neuronal apoptosis and promoting the rearrangement and morphology recovery of hippocampal cells. It outperforms Cuscutae Semen decoction in the antidepressant efficacy.

ObjectiveTo investigate the antidepressant effects and mechanisms of total flavonoids from Cuscutae Semen （TFCC） in the mouse model of chronic unpredictable mild stress （CUMS）. MethodsFifty male 4-week-old ICR mice were randomized into five groups （n=10 per group）： blank control， model， Cuscutae Semen decoction （10.2 g·kg^-1·d^-1）， paroxetine （2.6 mg·kg^-1·d^-1）， and TFCC （173.2 mg·kg^-1·d^-1）. The other groups except the blank control group underwent chronic unpredictable mild stress （CUMS） for 4 weeks. Behavioral assessments were conducted post-modeling. Then， the model group received distilled water （10 mL·kg^-1·d^-1）， while treatment groups were administrated with respective agents via oral gavage （10 mL·kg^-1） for 4 weeks. Depression-like behaviors were evaluated by the sucrose preference test （SPT）， forced swimming test （FST）， and tail suspension test （TST）. Hippocampal neuronal morphology was observed via hematoxylin-eosin staining， and apoptosis in the brain tissue was assessed via terminal- deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was employed to measure the hippocampal levels of inflammatory cytokines ［interleukin （IL）-1β， IL-6， and TNF-α）］ and neurotransmitters ［5-hydroxytryptamine （5-HT）， dopamine （DA）， and brain-derived neurotrophic factor （BDNF）］， while the reactive oxygen species （ROS） levels were quantified via the DCFH-DA probe. Real-time PCR was performed to measure the mRNA levels of NOD-like receptor protein 3 （NLRP3）， apoptosis-associated Speck-like protein containing a CARD （ASC）， cysteinyl aspartate-specific proteinase-1 （Caspase-1）， IL-1β， and inducible nitric oxide synthase （iNOS）. Western blot was employed to evaluate the protein levels of NLRP3， ASC， Caspase-1， uncoupling protein 2 （UCP2）， and thioredoxin-interacting protein （TXNIP）. ResultsCompared with the blank control group， the model group exhibited weight loss （P<0.01）， reduced sucrose preference （P<0.01）， prolonged immobility time in FST and TST （P<0.01）， neuron disarrangement with nuclear pyknosis in hippocampal CA3 region， increased apoptosis in the brain tissue， elevated levels of IL-1β， IL-6， and TNF-α （P<0.01）， declined levels of 5-HT， DA， and BDNF （P<0.01）， increased ROS accumulation （P<0.01）， upregulated mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， down-regulated protein level of UCP2 （P<0.01）， and up-regulated protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Compared with the model group， the interventions restored sucrose preference （P<0.01）， shortened immobility time （P<0.01）， repaired hippocampal neuronal structure， reduced apoptosis， lowered the levels of inflammatory cytokines （P<0.01）， restored the levels of neurotransmitters （P<0.01）， alleviated ROS accumulation （P<0.01）， downregulated the mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， upregulated the protein level of UCP2 （P<0.01）， and reduced the protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Moreover， TFCC outperformed Cuscutae Semen decoction in ameliorating depressive behaviors. TFCC excelled in neuronal repair， neurotransmitter regulation， anti-inflammatory effects， and modulation of the UCP2/TXNIP/NLRP3 pathway （P<0.05）. ConclusionTFCC modulates the hippocampal UCP2/TXNIP/NLRP3 pathway to inhibit inflammasome activation， reduce oxidative stress， restore neurotransmitters， thus suppressing neuronal apoptosis and promoting the rearrangement and morphology recovery of hippocampal cells. It outperforms Cuscutae Semen decoction in the antidepressant efficacy.

Objective To analyze the research status and trend of scarlet fever literature in China, and to provide reference for subsequent research. Methods Three major Chinese databases, CNKI, Wanfang, and VIP, as well as Web of Science English database, were used to search for literature related to scarlet fever from 2000 to 2023. Citespace6.2.R2 software was used to statistically analyze the number of publications, authors, institutions and journals, co-cited literature, keyword clustering, and other literature characteristics of the literature. Results From 2000 to 2023, a total of 1 011 Chinese literature were included in the three major Chinese databases. Since 2011, the number of publications had gradually increased, but in recent years, the number of publications had decreased. The organization with the most publications was the Shenyang Center for Disease Control and Prevention. The cluster analysis of key words mainly formed 9 cluster tags, and the high-frequency keywords mainly included epidemic characteristics, epidemiology, incidence rate, etc. A total of 84 English literature were included in the WOS database, with an overall upward trend in publication volume. The institution with the most publications was the China Center for Disease Control and Prevention, and the most frequently cited journal was ^“LANCET INFECT DIS^”.《Resurgence of scarlet fever in China: a 13-year population-based surveillance study》 was the most cited journal. After keyword cluster analysis, 9 cluster labels were mainly formed, and the keywords were mainly outbreak，Hong Kong, and Group A streptococcus. Conclusion Compared with the English literature, which mainly focuses on spatiotemporal aggregation, etiology and strain resistance, Chinese literature focuses more on epidemic surveillance, clinical features and quality nursing.