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.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

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.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Objective To investigate whether Liuwei Dihuang Pills enhances the antigen cross-presenting ability of dendritic cell(DC)by increasing gap junctional intercellular communication(GJIC),and to explore the mechanisms involved.Methods Western Blot and immunofluorescence were used to observe the effects of Liuwei Dihuang Pills-containing serum on the expression and membrane localisation of gap junction protein connexin43(Cx43)in mouse melanoma cells(B16);Calcein-AM/DiI fluorescence tracer assay was used to observe the effects of Liuwei Dihuang Pills-containing serum on the function of GJIC in B16 cells;flow cytometry was used to observe the role of GJIC in the enhancement of DC antigen presenting ability by Liuwei Dihuang Pills-containing serum;and propidium iodide(PI)/Hoechst staining assay was used to observe the immunocidal effect of CD8+ T-lymphocytes.Results Western Blot and immunofluorescence experiments showed that Liuwei Dihuang Pills-containing serum led to the up-regulation of Cx43 expression;fluorescence tracer experiments proved that the GJIC function of B16 cells was significantly enhanced by Liuwei Dihuang Pills-containing serum;flow cytometry analyses showed that the DC antigen-presenting ability was enhanced by Liuwei Dihuang Pills-containing serum;and the results of PI/Hoechst staining showed that the immuno-killing effect of CD8+T-cells was more significant after the intervention of Liuwei Dihuang Pills-containing serum in B16-OVA.Conclusion Liuwei Dihuang Pills improve the GJIC function by up-regulating the Cx43 expression of melanoma cells,and then enhance the cross-presenting ability of DCs thus activating stronger CD8+ T-cell immunocidal responses.

Objective: To evaluate the incidence, treatment, and survival outcomes of Swyer syndrome with gonadal non-dysgerminoma malignant germ cell tumor (MGCT-NDG). Methods: A retrospective study was performed on Swyer syndrome patients with MGCT-NDG between January 2011 and December 2022 in Peking Union Medical College Hospital to investigate their characteristics and outcomes. Results: A total of 15 patients (4.9%, 15/307) with Swyer syndrome were identified in 307 MGCT-NDG patients. The average age at diagnosis of MGCT-NDG and Swyer syndrome were (16.8±6.7) and (16.7±6.6) years, respectively. Six cases were preoperatively diagnosed as Swyer syndrome, of which 4 cases received bilateral gonadectomy with or without hysterectomy, while the other 2 cases underwent removal of gonadal tumor and unilateral gonadectomy with hysterectomy, respectively. Of the 9 patients postoperatively diagnosed as Swyer syndrome, unilateral gonadectomy, removal of gonadal tumor, and unilateral gonadectomy with hysterectomy were performed in 6 patients, 2 patients, and 1 patient, respectively. Mixed malignant germ cell tumor (MGCT;10 cases), yolk sac tumor (4 cases), and immature teratoma (1 case) were the pathological subtypes, in the descending order. There were International Federation of Gynecology and Obstetrics (FIGO) stage Ⅰ in 6 cases, stage Ⅱ in 3 cases, stage Ⅲ in 5 cases, and stage Ⅳ in 1 case, respectively. Eleven patients received reoperation for residual gonadectomy after a average delay of (7.9±6.2) months, including 8 MGCT-NDG patients and 1 gonadoblastoma patient, no tumor involved was seen in the remaining gonads in the other 2 cases. Ten patients experienced at least one recurrence, with a median event free survival of 9 months (5, 30 months), of which 2 patients received surgery only at the time of initial treatment. All patients with recurrence received surgery and combined with postoperative chemotherapy. After a median follow-up of 25 months (15, 42 months), 10 patients were disease-free, 3 patients died of the tumor, 1 died of side effects of leukemia chemotherapy, and 1 survived with disease. Conclusion: The incidence rate of Swyer syndrome in patients with MGCT-NDG is about 4.9%; timely diagnosis and bilateral gonadectomy should be emphasized to reduce the risk of reoperation and second carcinogenesis in this population.
Female ; Humans ; Retrospective Studies ; Gonadal Dysgenesis, 46,XY/surgery* ; Gonadoblastoma/surgery* ; Neoplasms, Germ Cell and Embryonal/surgery* ; Ovarian Neoplasms/pathology*

Objective To explore the changes of metabonomics in blood of mice after high-voltage electric shock,then screen out the significantly changed differential metabolites and metabolic pathways.Methods The head of C57BL/6J mice was subjected to high-voltage electric shock(electric shock group)or exposed to acoustic and optical stimulation of high-voltage electric(control group),then the whole blood from mice were collected to separate serum.The dual platform combined metabonomic analysis based on gas chromatography-mass spectrometer(GC-MS)and liquid chromatography-mass spectrometer(LC-MS)was performed and orthogonal partial least squares discriminant analysis(OPLS-DA)was used to screen the differential metabolites and related metabolic pathways.Results A total of 415 differential metabolites were screened out in metabonomics in blood of mice after high-voltage electric shock,including 187 up-regulated and 228 down-regulated metabolites.These differentially metabolites were significantly enriched in metabolic pathways including central carbon metabolism in cancer,glucagon signaling pathway,etc.Conclusion By establishing the model of high-voltage electrical injury on experimental mice,this study reveals the significant change of metabolite content and metabolic pathway in blood by high-voltage electrical injury.Which provides a basis for the damage of blood metabolic activity by high-voltage electrical injury,and suggests the potential harm of high-voltage electrical injury to blood metabolic activity in the whole body.

Background::The conversion of adenosine (A) to inosine (I) through deamination is the prevailing form of RNA editing, impacting numerous nuclear and cytoplasmic transcripts across various eukaryotic species. Millions of high-confidence RNA editing sites have been identified and integrated into various RNA databases, providing a convenient platform for the rapid identification of key drivers of cancer and potential therapeutic targets. However, the available database for integration of RNA editing in hematopoietic cells and hematopoietic malignancies is still lacking.Methods::We downloaded RNA sequencing (RNA-seq) data of 29 leukemia patients and 19 healthy donors from National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database, and RNA-seq data of 12 mouse hematopoietic cell populations obtained from our previous research were also used. We performed sequence alignment, identified RNA editing sites, and obtained characteristic editing sites related to normal hematopoietic development and abnormal editing sites associated with hematologic diseases.Results::We established a new database, "REDH", represents RNA editome in hematopoietic differentiation and malignancy. REDH is a curated database of associations between RNA editome and hematopoiesis. REDH integrates 30,796 editing sites from 12 murine adult hematopoietic cell populations and systematically characterizes more than 400,000 edited events in malignant hematopoietic samples from 48 cohorts (human). Through the Differentiation, Disease, Enrichment, and knowledge modules, each A-to-I editing site is systematically integrated, including its distribution throughout the genome, its clinical information (human sample), and functional editing sites under physiological and pathological conditions. Furthermore, REDH compares the similarities and differences of editing sites between different hematologic malignancies and healthy control.Conclusions::REDH is accessible at http://www.redhdatabase.com/. This user-friendly database would aid in understanding the mechanisms of RNA editing in hematopoietic differentiation and malignancies. It provides a set of data related to the maintenance of hematopoietic homeostasis and identifying potential therapeutic targets in malignancies.

AIM To investigate the purification process for esculin,fraxin,esculetin and fraxetin in Fraxini Cortex by macroporous resin.METHODS Static adsorption experiment was applied to screening resin model,single factor test was adopted in the optimization of purification process,UPLC-QTOF-MS/MS was used for identifying main components,after which heatmap was drawn.RESULTS The optimal resin model was ADS-5.The optimal purification process was determined to be 1.1 BV for loading amount,0.75 g/mL for loading concentration,2 BV pure water for washing impurity,and 4 BV 25%ethanol for eluting effective constituents,coumarins demonstrated the total transfer rate,purity and yield of 84.42%,53.28%and 4.79%,respectively.Total 37 constituents were identified,among which coumarins and phenylethanol glycosides were mainly concentrated in 25%ethanol eluent,organic acids,iridoids and flavonoids were mainly concentrated in 95%ethanol eluent.CONCLUSION This stable,feasible and accurate method can characterize the distribution patterns of coumarins in Fraxini Cortex in different eluents of macroporous resin,which provides guidance for further related pharmaceutical research.