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.

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.

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: Death burden of stroke is severe with over one-third rural residents in China, but there is still a lack of specific national and high-quality reports on the urban-rural differences in stroke burden, especially for subtypes. We aimed to update the understanding of urban-rural differences in stroke deaths. METHODS: This is a descriptive observational study. Data from the national mortality surveillance system, which covers 323.8 million with 605 disease surveillance points (DSPs) across all 31 provinces, municipalities, and autonomous regions in China. All deaths from stroke as the underlying cause from 2015 to 2020 according to DSPs. Crude mortality rate and age-standardized mortality rate (ASMR) were estimated through DSPs. Average annual percentage change was used to explain the change in mortality rate. RESULTS: From 2015 to 2020, the majority of deaths from all stroke subtypes occurred in rural areas. There were significant differences between the changes of urban and rural ASMRs. On the whole, the changes in urban areas were evidently better, and the ASMR differences were basically expanding. Stroke ASMR in urban China decreased by 15.5%. The rural ASMR of ischemic stroke increased by 12.9%. The rural and urban ASMRs of intracerebral hemorrhage decreased by 24.9% and 27.4%, and those of subarachnoid hemorrhage decreased by 29.5% and 40.4%, respectively. The highest ASMRs of all stroke subtypes and the increasing trend of ischemic stroke ASMR make rural males the focus of stroke management. CONCLUSIONS The death burden of stroke varies greatly between urban and rural China. Rural residents face unique challenges.
Humans ; China/epidemiology* ; Stroke/mortality* ; Rural Population/statistics & numerical data* ; Male ; Female ; Urban Population/statistics & numerical data* ; Middle Aged ; Aged ; Aged, 80 and over ; Adult