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.

Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

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.

Quantum dots (QDs), nanoscale semiconductor crystals, have emerged as a revolutionary class of nanomaterials with unique optical and electrochemical properties, making them highly promising for applications in disease diagnosis and treatment. Their tunable emission spectra, long-term photostability, high quantum yield, and excellent charge carrier mobility enable precise control over light emission and efficient charge utilization, which are critical for biomedical applications. This article provides a comprehensive review of recent advancements in the use of quantum dots for disease diagnosis and therapy, highlighting their potential and the challenges involved in clinical translation. Quantum dots can be classified based on their elemental composition and structural configuration. For instance, IB-IIIA-VIA group quantum dots and core-shell structured quantum dots are among the most widely studied types. These classifications are essential for understanding their diverse functionalities and applications. In disease diagnosis, quantum dots have demonstrated remarkable potential due to their high brightness, photostability, and ability to provide precise biomarker detection. They are extensively used in bioimaging technologies, enabling high-resolution imaging of cells, tissues, and even individual biomolecules. As fluorescent markers, quantum dots facilitate cell tracking, biosensing, and the detection of diseases such as cancer, bacterial and viral infections, and immune-related disorders. Their ability to provide real-time, in vivo tracking of cellular processes has opened new avenues for early and accurate disease detection. In the realm of disease treatment, quantum dots serve as versatile nanocarriers for targeted drug delivery. Their nanoscale size and surface modifiability allow them to transport therapeutic agents to specific sites, improving drug bioavailability and reducing off-target effects. Additionally, quantum dots have shown promise as photosensitizers in photodynamic therapy (PDT). When exposed to specific wavelengths of light, quantum dots interact with oxygen molecules to generate reactive oxygen species (ROS), which can selectively destroy malignant cells, vascular lesions, and microbial infections. This targeted approach minimizes damage to healthy tissues, making PDT a promising strategy for treating complex diseases. Despite these advancements, the translation of quantum dots from research to clinical application faces significant challenges. Issues such as toxicity, stability, and scalability in industrial production remain major obstacles. The potential toxicity of quantum dots, particularly to vital organs, has raised concerns about their long-term safety. Researchers are actively exploring strategies to mitigate these risks, including surface modification, coating, and encapsulation techniques, which can enhance biocompatibility and reduce toxicity. Furthermore, improving the stability of quantum dots under physiological conditions is crucial for their effective use in biomedical applications. Advances in surface engineering and the development of novel encapsulation methods have shown promise in addressing these stability concerns. Industrial production of quantum dots also presents challenges, particularly in achieving consistent quality and scalability. Recent innovations in synthesis techniques and manufacturing processes are paving the way for large-scale production, which is essential for their widespread adoption in clinical settings. This article provides an in-depth analysis of the latest research progress in quantum dot applications, including drug delivery, bioimaging, biosensing, photodynamic therapy, and pathogen detection. It also discusses the multiple barriers hindering their clinical use and explores potential solutions to overcome these challenges. The review concludes with a forward-looking perspective on the future directions of quantum dot research, emphasizing the need for further studies on toxicity mitigation, stability enhancement, and scalable production. By addressing these critical issues, quantum dots can realize their full potential as transformative tools in disease diagnosis and treatment, ultimately improving patient outcomes and advancing biomedical science.

Gap junction(GJ),also known as gap junction,is widely found between neurons and glial cells,and can connect neighboring cells and mediate the transmission of electrical sig-nals between neighboring cells.The GJ channel,which exists between neurons and mediates intercellular electrical signaling,is also known as an electrical synapse.Connexins(Cxs)are the molecular basis of GJ,and are expressed to different degrees in different neurons and glial cells.The presence of GJ mediates different functions among neurons and glial cells,which further influences the establishment of various mature neural circuits,re-flecting the importance of GJ in the maintenance of neural cir-cuits.This review summarizes the relationship between GJ and neural circuits in relation to the effects of GJ and different Cxs on neurons and glial cells,providing new research ideas for the treatment of neuropsychiatric disorders.

Aim To preliminarily evaluate the effects of hypobaric hypoxia on organism damage in rats with post-traumatic stress disorder(PTSD),with a view to laying a foundation for drug research in plateau PTSD.Methods The rats were randomly divided into four groups,namely,the control(Control)group,the sin-gle-prolonged stress(SPS)group,the hypobaric hy-poxia(HH)group and the single-prolonged stress combined with hypobaric hypoxia(SPS+HH)group.The PTSD model was firstly constructed using the SPS method for rats in the SPS and SPS+HH groups.On the second day,rats in the HH group and SPS+HH group were placed in a low-pressure hypoxia chamber at a simulated altitude of 6000 m for 14 days.General condition,behavior,blood tests,and histomorphology were examined in order to evaluate the damage caused by low pressure hypoxia in PTSD rats.Results The body mass of rats in the SPS+HH group was signifi-cantly reduced;the feces were partly hard and lumpy,and some of them were seen to have high viscosity.Anxiety-like and depression-like behaviors were ob-served in all groups except in the control group,in which hypobaric hypoxia aggravated the behavioral ab-normalities in SPS rats.Rats in both the SPS and SPS+HH groups had coagulation dysfunction and abnor-mally increased blood viscosity,which was significantly abnormal in the SPS+HH group;erythrocytes,hemo-globin,and erythrocyte specific volume in whole blood of rats in the SPS+HH group were significantly in-creased compared with those of rats in the SPS group;and serum TP,LDH and GLU levels were abnormal in rats in the SPS+HH group.Dilated and congested blood vessels were seen in hippocampal tissue,conges-ted central veins were seen in hepatic tissue,and dilat-ed and congested liver sinusoids with mild granuloma-tous degeneration of hepatocytes were seen in rats of the SPS+HH group.Conclusion Hypobaric hypoxia exacerbates depression-like and anxiety-like behaviors in PTSD rats,as well as hematological indices and his-tomorphometric abnormalities in PTSD rats.

Aim To investigate the mechanism of py-roptosis mediated by the NLRP3/caspase-1/GSDMD signaling pathway and the intervention effect of Radix Angelica Sinensis and Radix Astragalus ultrafiltration extract(RAS-RA)in radiation-induced pulmonary fi-brosis.Methods Fifty Wistar rats were randomly di-vided into five groups,with ten rats in each group.Ex-cept for the blank control group,all other groups of rats were anesthetized and received a single dose of 40 Gy X-ray local chest radiation to establish a radiation-in-duced pulmonary fibrosis rat model.After radiation,the rats in the RAS-RA intervention groups were orally administered doses of 0.12,0.24 and 0.48 g·kg-1 once a day for 30 days.The average weight and lung index of the rats were observed after 30 days of contin-uous administration.Hydroxyproline(HYP)content in lung tissue was determined by hydrolysis method.The levels of IL-18 and IL-1 β in serum were detected by ELISA.Lung tissue pathological changes were ob-served by HE and Masson staining.Ultrastructural changes in lung tissue were observed by transmission e-lectron microscopy.The expression levels of NLRP3/caspase-1/GSDMD pyroptosis pathway-related proteins and fibrosis-related proteins in lung tissue were detec-ted by Western blot.Results Compared with the blank group,the HYP content in lung tissue and the levels of IL-18 and IL-1 β in serum significantly in-creased in the model group(P＜0.01).HE and Mas-son staining showed inflammatory cell infiltration and collagen fiber deposition.Transmission electron mi-croscopy revealed increased damaged mitochondria,disordered arrangement,irregular morphology,shallow matrix,outer membrane rupture,mostly fractured and shortened cristae,mild expansion,increased electron density of individual mitochondrial matrix,mild sparse structure of lamellar bodies,partial disorder,unclear organelles,and characteristic changes of pyroptosis.Western blot analysis showed increased expression of caspase-1,GSDMD,NLRP3,CoL-Ⅰ,α-SMA,and CoL-Ⅲ proteins(P＜0.01).Compared with the model group,the RAS-RA intervention group showed signifi-cant improvement in body mass index and lung index of rats,decreased levels of IL-18 and IL-1 β inflammatory factors(P＜0.01),improved mitochondrial structure,reduced degree of fibrosis,and decreased expression of caspase-1,GSDMD,NLRP3,COL-Ⅰ,COL-Ⅲ,and α-SMA proteins in lung tissue(P＜0.01).Conclusion RAS-RA has an inhibitory effect on radiation-in-duced pulmonary fibrosis,and its mechanism may be related to the inhibition of pyroptosis through the regu-lation of the NLRP3/caspase-1/GSDMD signaling pathway.

Lassa virus(LASV),a member of Arenaviridae family,is the cause of severe acute hemorrhagic fever,known as Lassa fever,which has an overall fatality rate of 1％,but up to 15％in hospitalized patients.LASV is mainly endemic in West Africa.At present,there is no approved drug or vaccine for LASV,and treatment is limited to ribavirin in the early dis-ease stage.Although some drugs have entered the clinical stage,most have been studied in cellular and animal models.Accord-ing to the Centers for Disease Control and Prevention,LASV is a Class A pathogen due to a high mortality rate and limited treatment options.The World Health Organization has identified Lassa fever as a top priority for research and development.This article reviews recent progress in the development of LASV inhibitors.