In recent years, Edwardsiella tarda has become one of the most deadly pathogens of Japanese fl ounder( Paralichthys olivaceus), causing serious annual losses in commercial production. In contrast to the rapid advances...In recent years, Edwardsiella tarda has become one of the most deadly pathogens of Japanese fl ounder( Paralichthys olivaceus), causing serious annual losses in commercial production. In contrast to the rapid advances in the aquaculture of P. o livaceus, the study of E. tarda resistance-related markers has lagged behind, hindering the development of a disease-resistant strain. Thus, a marker-trait association analysis was initiated, combining bulked segregant analysis(BSA) and quantitative trait loci(QTL) mapping. Based on 180 microsatellite loci across all chromosomes, 106 individuals from the F1333(♀: F0768 ×♂: F0915)(Nomenclature rule: F+year+family number) were used to detect simple sequence repeats(SSRs) and QTLs associated with E. tarda resistance. After a genomic scan, three markers(Scaffold 404-21589, Scaffold 404-21594 and Scaffold 270-13812) from the same linkage group(LG)-1 exhibited a signifi cant difference between DNA, pooled/bulked from the resistant and susceptible groups( P <0.001). Therefore, 106 individuals were genotyped using all the SSR markers in LG1 by single marker analysis. Two different analytical models were then employed to detect SSR markers with different levels of signifi cance in LG1, where 17 and 18 SSR markers were identifi ed, respectively. Each model found three resistance-related QTLs by composite interval mapping(CIM). These six QTLs, designated q E1–6, explained 16.0%–89.5% of the phenotypic variance. Two of the QTLs, q E-2 and q E-4, were located at the 66.7 c M region, which was considered a major candidate region for E. tarda resistance. This study will provide valuable data for further investigations of E. tarda resistance genes and facilitate the selective breeding of disease-resistant Japanese fl ounder in the future.展开更多
Differentiation of oligodendrocyte progenitor cells into mature myelin-forming oligodendrocytes contributes to remyelination.Failure of remyelination due to oligodendrocyte progenitor cell death can result in severe n...Differentiation of oligodendrocyte progenitor cells into mature myelin-forming oligodendrocytes contributes to remyelination.Failure of remyelination due to oligodendrocyte progenitor cell death can result in severe nerve damage.Ferroptosis is an iron-dependent form of regulated cell death caused by membrane rupture induced by lipid peroxidation,and plays an important role in the pathological process of ischemic stroke.However,there are few studies on oligodendrocyte progenitor cell ferroptosis.We analyzed transcriptome sequencing data from GEO databases and identified a role of ferroptosis in oligodendrocyte progenitor cell death and myelin injury after cerebral ischemia.Bioinformatics analysis suggested that perilipin-2(PLIN2)was involved in oligodendrocyte progenitor cell ferroptosis.PLIN2 is a lipid storage protein and a marker of hypoxia-sensitive lipid droplet accumulation.For further investigation,we established a mouse model of cerebral ischemia/reperfusion.We found significant myelin damage after cerebral ischemia,as well as oligodendrocyte progenitor cell death and increased lipid peroxidation levels around the infarct area.The ferroptosis inhibitor,ferrostatin-1,rescued oligodendrocyte progenitor cell death and subsequent myelin injury.We also found increased PLIN2 levels in the peri-infarct area that co-localized with oligodendrocyte progenitor cells.Plin2 knockdown rescued demyelination and improved neurological deficits.Our findings suggest that targeting PLIN2 to regulate oligodendrocyte progenitor cell ferroptosis may be a potential therapeutic strategy for rescuing myelin damage after cerebral ischemia.展开更多
While bulk RNA sequencing and single-cell RNA sequencing have shed light on cellular heterogeneity and potential molecular mechanisms in the musculoskeletal system in both physiological and various pathological states...While bulk RNA sequencing and single-cell RNA sequencing have shed light on cellular heterogeneity and potential molecular mechanisms in the musculoskeletal system in both physiological and various pathological states,the spatial localization of cells and molecules and intercellular interactions within the tissue context require further elucidation.Spatial transcriptomics has revolutionized biological research by simultaneously capturing gene expression profiles and in situ spatial information of tissues,gradually finding applications in musculoskeletal research.This review provides a summary of recent advances in spatial transcriptomics and its application to the musculoskeletal system.The classification and characteristics of data acquisition techniques in spatial transcriptomics are briefly outlined,with an emphasis on widely-adopted representative technologies and the latest technological breakthroughs,accompanied by a concise workflow for incorporating spatial transcriptomics into musculoskeletal system research.The role of spatial transcriptomics in revealing physiological mechanisms of the musculoskeletal system,particularly during developmental processes,is thoroughly summarized.Furthermore,recent discoveries and achievements of this emerging omics tool in addressing inflammatory,traumatic,degenerative,and tumorous diseases of the musculoskeletal system are compiled.Finally,challenges and potential future directions for spatial transcriptomics,both as a field and in its applications in the musculoskeletal system,are discussed.展开更多
Osteoarthritis(OA)is the most common joint disease in elderly patients.Its main pathological change is articular cartilage degeneration,accompanied by synovial inflammation and changes in subchondral bone structure,re...Osteoarthritis(OA)is the most common joint disease in elderly patients.Its main pathological change is articular cartilage degeneration,accompanied by synovial inflammation and changes in subchondral bone structure,resulting in pain and limited mobility.However,previous studies on OA mainly focused on the dysfunction of cartilage and chondrocytes,and the synovium and other joint structures have not received enough attention.展开更多
Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline...Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline system(DLAPS)for diagnosing LLNM in PTC using computed tomography(CT).Methods:A total of 1,266 lateral lymph nodes(LLNs)from 519 PTC patients who underwent CT examinations from January 2019 to November 2022 were included and divided into training and validation set,internal test set,pooled external test set,and prospective test set.The DLAPS consists of an auto-segmentation network based on RefineNet model and a classification network based on ensemble model(ResNet,Xception,and DenseNet).The performance of the DLAPS was compared with that of manually segmented DL models,the clinical model,and Node Reporting and Data System(Node-RADS).The improvement of radiologists’diagnostic performance under the DLAPS-assisted strategy was explored.In addition,bulk RNA-sequencing was conducted based on 12 LLNs to reveal the underlying biological basis of the DLAPS.Results:The DLAPS yielded good performance with area under the receiver operating characteristic curve(AUC)of 0.872,0.910,and 0.822 in the internal,pooled external,and prospective test sets,respectively.The DLAPS significantly outperformed clinical models(AUC 0.731,P<0.001)and Node-RADS(AUC 0.602,P<0.001)in the internal test set.Moreover,the performance of the DLAPS was comparable to that of the manually segmented deep learning(DL)model with AUCs ranging 0.814−0.901 in three test sets.Furthermore,the DLAPSassisted strategy improved the performance of radiologists and enhanced inter-observer consistency.In clinical situations,the rate of unnecessary LLN dissection decreased from 33.33%to 7.32%.Furthermore,the DLAPS was associated with the cell-cell conjunction in the microenvironment.Conclusions:Using CT images from PTC patients,the DLAPS could effectively segment and classify LLNs non-invasively,and this system had a good generalization ability and clinical applicability.展开更多
Seed coat color affects the appearance and commodity quality of mung beans(Vigna radiata L.).The substances that affect mung bean seed coat color are mainly flavonoids,which have important medicinal value.Mapping the ...Seed coat color affects the appearance and commodity quality of mung beans(Vigna radiata L.).The substances that affect mung bean seed coat color are mainly flavonoids,which have important medicinal value.Mapping the seed coat color gene in mung beans would facilitate the development of new varieties and improve their value.In this study,an F2 mapping population consisting of 546 plants was constructed using Jilv9(black seed coat)and BIS9805(green seed coat).Using bulk segregated analysis(BSA)sequencing and kompetitive allele-specific PCR(KASP)markers,the candidate region related to seed coat color was finally narrowed to 0.66 Mb on chromosome(Chr.)4 and included eight candidate genes.Combined transcriptome and metabolome analyses showed that three of the eight candidate genes(LOC106758748,LOC106758747,and LOC106759075)were differentially expressed,which may have caused the differences in flavonoid metabolite content between Jilv9 and BIS9805.These findings can provide a research basis for cloning the genes related to seed coat color and accelerate molecular markerassisted selection breeding in mung beans.展开更多
Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(iCCA)represent the most prevalent primary malignancies of the liver(1,2).Both exhibit significant heterogeneity and complex tumor microenvironments,whic...Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(iCCA)represent the most prevalent primary malignancies of the liver(1,2).Both exhibit significant heterogeneity and complex tumor microenvironments,which contribute to their aggressive nature and poor prognosis.Conventional genomic and transcriptomic methodologies,including bulk sequencing and single-cell RNA sequencing,have identified critical driver mutations and cellular subpopulations.However,these approaches lack the ability to preserve the native spatial architecture of tissues,thereby limiting insights into cellular interactions and functional niches.The emergence of spatial omics technologies addresses this fundamental limitation.By enabling the simultaneous assessment of molecular expression and its precise histological context,these methods provide an unprecedented view of the tumor ecosystem,offering new avenues for understanding hepatobiliary cancer biology and developing targeted therapies.展开更多
Single-cell RNA sequencing(scRNA-seq),introduced in 2009,has rapidly become a cornerstone of biological research,particularly in uncovering cellular heterogeneity,developmental trajectories,and gene regulatory network...Single-cell RNA sequencing(scRNA-seq),introduced in 2009,has rapidly become a cornerstone of biological research,particularly in uncovering cellular heterogeneity,developmental trajectories,and gene regulatory networks.By enabling high-resolution analysis of gene expression at the single-cell level,scRNA-seq overcomes the limitations of traditional bulk RNA sequencing that averages gene expression across cell populations.This transformative technology has provided unprecedented insights into the cellular composition of complex tissues and organs,revealing rare cell types,transient states,and dynamic regulatory interactions that were previously obscured.Its applications span diverse fields,including developmental biology,immunology,and cancer research,where it has become an indispensable tool for dissecting cellular diversity,mapping lineage relationships,and identifying key drivers of disease progression[1].scRNA-seq has become a core research method,driving breakthroughs in our understanding of cellular behavior and tissue organization.展开更多
There are similarities between rheumatoid arthritis(RA)and systemic lupus erythematosus(SLE)in terms of clinical manifestations,immune responses,and therapeutic strategies,1 and thus a joint analysis of the two diseas...There are similarities between rheumatoid arthritis(RA)and systemic lupus erythematosus(SLE)in terms of clinical manifestations,immune responses,and therapeutic strategies,1 and thus a joint analysis of the two diseases could contribute to a deeper understanding of the shared pathogenesis of autoimmune diseases.The subtype analysis of RA and SLE is currently understudied,and the marker genes used for subtype definition in most studies are derived from bulk RNA sequencing data or microarray data,which are underrepresentative of individual immune cell status.2 Therefore,we aimed to identify cell type-specific expressed genes as biomarkers based on single-cell RNA sequencing data and to explore the commonalities and differences between RA and SLE by a combined subtype analysis based on microarray data.Both the representativeness of the markers in terms of immune characteristics and the reproducibility of the results are ensured by the sufficient sample size.Immune infiltration analysis revealed the subtype heterogeneity and significant differences in clinical characteristics between different subtypes of RA patients,which verified the heterogeneity between different subtypes.Finally,we constructed subtype prediction models by machine learning algorithms further validating the heterogeneity among subtypes.Detailed methodology and the overall flowchart(Fig.S1)are provided in the supplementary material.展开更多
Pituitary neuroendocrine tumors(PitNETs)are pathologically characterized by dysregulation of neuroendocrine function and systemic disruption of hormonal homeostasis,yet their regulatory effects on peripheral immune ne...Pituitary neuroendocrine tumors(PitNETs)are pathologically characterized by dysregulation of neuroendocrine function and systemic disruption of hormonal homeostasis,yet their regulatory effects on peripheral immune networks remain poorly characterized.Here,we systematically analyzed bulk RNA sequencing(RNA‑seq)from 883 PitNET tumors,108 PitNET‑associated peripheral blood mononuclear cells(PBMC)samples,and 175 healthy PBMC controls,combined with 69 single‑cell RNA sequencing(scRNA-seq)samples covering tumors,normal pituitaries,as well as tumor‑derived and normal PBMCs.We identified a systemic immune disequilibrium in PitNET patients,characterized by increased circulating lymphocyte proportions,accompanied by upregulated cytokine-receptor interaction signatures.Notably,tumor resection reversed this imbalance,as supported by the normalization of monocyte and neutrophil counts,validated by flow cytometry and routine blood data from 600 samples(200 healthy controls and 200 PitNET patients with paired pre-and post-surgery follow‑up).Trajectory analysis identified terminally differentiated,secretory-specialized cell populations with lineage-specific hormone and cytokine hypersecretion.Ligand-receptor inference suggested these tumor-derived factors potentially engage circulating immune cell receptors.A random‑forest classifier based on PBMC transcriptomes distinguished PitNET subtypes,underscoring the diagnostic potential of peripheral immune signatures.Furthermore,in an estrogen-induced rat model,elevated PRL level coincided with the same peripheral immune skewing.Overall,our work provides a valuable resource and demonstrates PitNETs can be systemic immune modulators,where intrinsic hormone secretory activity and monocyte-lymphocyte imbalance collectively drive peripheral immune dysfunction.展开更多
Single-cell RNA sequencing(scRNA-seq)has emerged as a valuable tool for studying cellular heterogeneity in various fields,particularly in virological research.By studying the viral and cellular transcriptomes,the dyna...Single-cell RNA sequencing(scRNA-seq)has emerged as a valuable tool for studying cellular heterogeneity in various fields,particularly in virological research.By studying the viral and cellular transcriptomes,the dynamics of viral infection can be investigated at a single-cell resolution.However,limited studies have been conducted to investigate whether RNA transcripts from clinical samples contain substantial amounts of viral RNAs,and a specific computational framework for efficiently detecting viral reads based on scRNA-seq data has not been developed.Hence,we introduce DVsc,an open-source framework for precise quantitative analysis of viral infection from single-cell transcriptomics data.When applied to approximately 200 diverse clinical samples that were infected by more than 10 different viruses,DVsc demonstrated high accuracy in systematically detecting viral infection across a wide array of cell types.This innovative bioinformatics pipeline could be crucial for addressing the potential effects of surreptitiously invading viruses on certain illnesses,as well as for designing novel medicines to target viruses in specific host cell subsets and evaluating the efficacy of treatment.DVsc supports the FASTQ format as an input and is compatible with multiple single-cell sequencing platforms.Moreover,it could also be applied to sequences from bulk RNA sequencing data.DVsc is available at http://62.234.32.33:5000/DVsc.展开更多
基金Supported by the National Natural Science Foundation of China(No.31461163005)the Taishan Scholar Project of Shandong Province
文摘In recent years, Edwardsiella tarda has become one of the most deadly pathogens of Japanese fl ounder( Paralichthys olivaceus), causing serious annual losses in commercial production. In contrast to the rapid advances in the aquaculture of P. o livaceus, the study of E. tarda resistance-related markers has lagged behind, hindering the development of a disease-resistant strain. Thus, a marker-trait association analysis was initiated, combining bulked segregant analysis(BSA) and quantitative trait loci(QTL) mapping. Based on 180 microsatellite loci across all chromosomes, 106 individuals from the F1333(♀: F0768 ×♂: F0915)(Nomenclature rule: F+year+family number) were used to detect simple sequence repeats(SSRs) and QTLs associated with E. tarda resistance. After a genomic scan, three markers(Scaffold 404-21589, Scaffold 404-21594 and Scaffold 270-13812) from the same linkage group(LG)-1 exhibited a signifi cant difference between DNA, pooled/bulked from the resistant and susceptible groups( P <0.001). Therefore, 106 individuals were genotyped using all the SSR markers in LG1 by single marker analysis. Two different analytical models were then employed to detect SSR markers with different levels of signifi cance in LG1, where 17 and 18 SSR markers were identifi ed, respectively. Each model found three resistance-related QTLs by composite interval mapping(CIM). These six QTLs, designated q E1–6, explained 16.0%–89.5% of the phenotypic variance. Two of the QTLs, q E-2 and q E-4, were located at the 66.7 c M region, which was considered a major candidate region for E. tarda resistance. This study will provide valuable data for further investigations of E. tarda resistance genes and facilitate the selective breeding of disease-resistant Japanese fl ounder in the future.
基金supported by the National Natural Science Foundation of China,Nos.82071307(to HL),82271362(to HL),82171294(to JW),82371303(to JW),and 82301460(to PX)the Natural Science Foundation of Jiangsu Province,No.BK20211552(to HL)+1 种基金Suzhou Medical Technology Innovation Project-Clinical Frontier,No.SKY2022002(to ZY)the Science and Education Foundation for Health of Suzhou for Youth,No.KJXW2023001(to XL)。
文摘Differentiation of oligodendrocyte progenitor cells into mature myelin-forming oligodendrocytes contributes to remyelination.Failure of remyelination due to oligodendrocyte progenitor cell death can result in severe nerve damage.Ferroptosis is an iron-dependent form of regulated cell death caused by membrane rupture induced by lipid peroxidation,and plays an important role in the pathological process of ischemic stroke.However,there are few studies on oligodendrocyte progenitor cell ferroptosis.We analyzed transcriptome sequencing data from GEO databases and identified a role of ferroptosis in oligodendrocyte progenitor cell death and myelin injury after cerebral ischemia.Bioinformatics analysis suggested that perilipin-2(PLIN2)was involved in oligodendrocyte progenitor cell ferroptosis.PLIN2 is a lipid storage protein and a marker of hypoxia-sensitive lipid droplet accumulation.For further investigation,we established a mouse model of cerebral ischemia/reperfusion.We found significant myelin damage after cerebral ischemia,as well as oligodendrocyte progenitor cell death and increased lipid peroxidation levels around the infarct area.The ferroptosis inhibitor,ferrostatin-1,rescued oligodendrocyte progenitor cell death and subsequent myelin injury.We also found increased PLIN2 levels in the peri-infarct area that co-localized with oligodendrocyte progenitor cells.Plin2 knockdown rescued demyelination and improved neurological deficits.Our findings suggest that targeting PLIN2 to regulate oligodendrocyte progenitor cell ferroptosis may be a potential therapeutic strategy for rescuing myelin damage after cerebral ischemia.
基金supported by The National Natural Science Youth Foundation of China(Grant No.82102584).
文摘While bulk RNA sequencing and single-cell RNA sequencing have shed light on cellular heterogeneity and potential molecular mechanisms in the musculoskeletal system in both physiological and various pathological states,the spatial localization of cells and molecules and intercellular interactions within the tissue context require further elucidation.Spatial transcriptomics has revolutionized biological research by simultaneously capturing gene expression profiles and in situ spatial information of tissues,gradually finding applications in musculoskeletal research.This review provides a summary of recent advances in spatial transcriptomics and its application to the musculoskeletal system.The classification and characteristics of data acquisition techniques in spatial transcriptomics are briefly outlined,with an emphasis on widely-adopted representative technologies and the latest technological breakthroughs,accompanied by a concise workflow for incorporating spatial transcriptomics into musculoskeletal system research.The role of spatial transcriptomics in revealing physiological mechanisms of the musculoskeletal system,particularly during developmental processes,is thoroughly summarized.Furthermore,recent discoveries and achievements of this emerging omics tool in addressing inflammatory,traumatic,degenerative,and tumorous diseases of the musculoskeletal system are compiled.Finally,challenges and potential future directions for spatial transcriptomics,both as a field and in its applications in the musculoskeletal system,are discussed.
文摘Osteoarthritis(OA)is the most common joint disease in elderly patients.Its main pathological change is articular cartilage degeneration,accompanied by synovial inflammation and changes in subchondral bone structure,resulting in pain and limited mobility.However,previous studies on OA mainly focused on the dysfunction of cartilage and chondrocytes,and the synovium and other joint structures have not received enough attention.
基金supported by the Taishan Scholar Project(No.ts20190991,No.tsqn202211378)the Key R&D Project of Shandong Province(No.2022CXPT023)+1 种基金the General Program of National Natural Science Foundation of China(No.82371933)the Medical and Health Technology Project of Shandong Province(No.202307010677)。
文摘Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline system(DLAPS)for diagnosing LLNM in PTC using computed tomography(CT).Methods:A total of 1,266 lateral lymph nodes(LLNs)from 519 PTC patients who underwent CT examinations from January 2019 to November 2022 were included and divided into training and validation set,internal test set,pooled external test set,and prospective test set.The DLAPS consists of an auto-segmentation network based on RefineNet model and a classification network based on ensemble model(ResNet,Xception,and DenseNet).The performance of the DLAPS was compared with that of manually segmented DL models,the clinical model,and Node Reporting and Data System(Node-RADS).The improvement of radiologists’diagnostic performance under the DLAPS-assisted strategy was explored.In addition,bulk RNA-sequencing was conducted based on 12 LLNs to reveal the underlying biological basis of the DLAPS.Results:The DLAPS yielded good performance with area under the receiver operating characteristic curve(AUC)of 0.872,0.910,and 0.822 in the internal,pooled external,and prospective test sets,respectively.The DLAPS significantly outperformed clinical models(AUC 0.731,P<0.001)and Node-RADS(AUC 0.602,P<0.001)in the internal test set.Moreover,the performance of the DLAPS was comparable to that of the manually segmented deep learning(DL)model with AUCs ranging 0.814−0.901 in three test sets.Furthermore,the DLAPSassisted strategy improved the performance of radiologists and enhanced inter-observer consistency.In clinical situations,the rate of unnecessary LLN dissection decreased from 33.33%to 7.32%.Furthermore,the DLAPS was associated with the cell-cell conjunction in the microenvironment.Conclusions:Using CT images from PTC patients,the DLAPS could effectively segment and classify LLNs non-invasively,and this system had a good generalization ability and clinical applicability.
基金supported by the National Natural Science Foundation of China(32301928)the Basic Research Program of Shanxi Province,China(20210302124504)+3 种基金the China Agriculture Research System of MOF and MARA-Food Legumes(CARS08-G10)the National Laboratory Project of Coarse Grain Germplasm Resources Innovation and Molecular Breeding,China(K462202040-01)the Ph D of Shanxi Agricultural University Scientific Research Start-up Project,China(2021BQ43)the Scientific Research Project of Shanxi Agricultural University,China(YZGC098)。
文摘Seed coat color affects the appearance and commodity quality of mung beans(Vigna radiata L.).The substances that affect mung bean seed coat color are mainly flavonoids,which have important medicinal value.Mapping the seed coat color gene in mung beans would facilitate the development of new varieties and improve their value.In this study,an F2 mapping population consisting of 546 plants was constructed using Jilv9(black seed coat)and BIS9805(green seed coat).Using bulk segregated analysis(BSA)sequencing and kompetitive allele-specific PCR(KASP)markers,the candidate region related to seed coat color was finally narrowed to 0.66 Mb on chromosome(Chr.)4 and included eight candidate genes.Combined transcriptome and metabolome analyses showed that three of the eight candidate genes(LOC106758748,LOC106758747,and LOC106759075)were differentially expressed,which may have caused the differences in flavonoid metabolite content between Jilv9 and BIS9805.These findings can provide a research basis for cloning the genes related to seed coat color and accelerate molecular markerassisted selection breeding in mung beans.
基金supported by the Beijing-Tianjin-Hebei Basic Research Cooperation Special Project(grant number 22JCZXJC00200)National High Level Hospital Clinical Research Funding(2025-PUMCH-C-030).
文摘Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(iCCA)represent the most prevalent primary malignancies of the liver(1,2).Both exhibit significant heterogeneity and complex tumor microenvironments,which contribute to their aggressive nature and poor prognosis.Conventional genomic and transcriptomic methodologies,including bulk sequencing and single-cell RNA sequencing,have identified critical driver mutations and cellular subpopulations.However,these approaches lack the ability to preserve the native spatial architecture of tissues,thereby limiting insights into cellular interactions and functional niches.The emergence of spatial omics technologies addresses this fundamental limitation.By enabling the simultaneous assessment of molecular expression and its precise histological context,these methods provide an unprecedented view of the tumor ecosystem,offering new avenues for understanding hepatobiliary cancer biology and developing targeted therapies.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2024IAIS-QN020)the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(Grant No.22lglj08),China.
文摘Single-cell RNA sequencing(scRNA-seq),introduced in 2009,has rapidly become a cornerstone of biological research,particularly in uncovering cellular heterogeneity,developmental trajectories,and gene regulatory networks.By enabling high-resolution analysis of gene expression at the single-cell level,scRNA-seq overcomes the limitations of traditional bulk RNA sequencing that averages gene expression across cell populations.This transformative technology has provided unprecedented insights into the cellular composition of complex tissues and organs,revealing rare cell types,transient states,and dynamic regulatory interactions that were previously obscured.Its applications span diverse fields,including developmental biology,immunology,and cancer research,where it has become an indispensable tool for dissecting cellular diversity,mapping lineage relationships,and identifying key drivers of disease progression[1].scRNA-seq has become a core research method,driving breakthroughs in our understanding of cellular behavior and tissue organization.
基金supported by the Fundamental Research Funds for the Provincial Universities in Heilongjiang Province,China(2024,to Wenhua Lv)College Student Innovation Training Project of Heilongjiang Province,China(S202410226008).
文摘There are similarities between rheumatoid arthritis(RA)and systemic lupus erythematosus(SLE)in terms of clinical manifestations,immune responses,and therapeutic strategies,1 and thus a joint analysis of the two diseases could contribute to a deeper understanding of the shared pathogenesis of autoimmune diseases.The subtype analysis of RA and SLE is currently understudied,and the marker genes used for subtype definition in most studies are derived from bulk RNA sequencing data or microarray data,which are underrepresentative of individual immune cell status.2 Therefore,we aimed to identify cell type-specific expressed genes as biomarkers based on single-cell RNA sequencing data and to explore the commonalities and differences between RA and SLE by a combined subtype analysis based on microarray data.Both the representativeness of the markers in terms of immune characteristics and the reproducibility of the results are ensured by the sufficient sample size.Immune infiltration analysis revealed the subtype heterogeneity and significant differences in clinical characteristics between different subtypes of RA patients,which verified the heterogeneity between different subtypes.Finally,we constructed subtype prediction models by machine learning algorithms further validating the heterogeneity among subtypes.Detailed methodology and the overall flowchart(Fig.S1)are provided in the supplementary material.
基金supported by the National Research Center for Translational Medicine under grant number NRCTM(SH)2023-15(to Z-B.W.)Fundamental Research Funds for the Central Universities(No.YG2023ZD06 to Z-B.W.)+3 种基金National Natural Science Foundation of China(82472640 to Z-B.W.,82373131 and 82573142 to S-J.L.,82200153 to Y-T.D.,82500265 to S-S.Y.)Health care leader of Shanghai Municipal Health Commission(No.2022LJ006 to Z-B.W.)the Natural Science Foundation of Shanghai,China(25ZR1402349 to S-S.Y.)the Innovative Research Team of HighLevel Local Universities in Shanghai.
文摘Pituitary neuroendocrine tumors(PitNETs)are pathologically characterized by dysregulation of neuroendocrine function and systemic disruption of hormonal homeostasis,yet their regulatory effects on peripheral immune networks remain poorly characterized.Here,we systematically analyzed bulk RNA sequencing(RNA‑seq)from 883 PitNET tumors,108 PitNET‑associated peripheral blood mononuclear cells(PBMC)samples,and 175 healthy PBMC controls,combined with 69 single‑cell RNA sequencing(scRNA-seq)samples covering tumors,normal pituitaries,as well as tumor‑derived and normal PBMCs.We identified a systemic immune disequilibrium in PitNET patients,characterized by increased circulating lymphocyte proportions,accompanied by upregulated cytokine-receptor interaction signatures.Notably,tumor resection reversed this imbalance,as supported by the normalization of monocyte and neutrophil counts,validated by flow cytometry and routine blood data from 600 samples(200 healthy controls and 200 PitNET patients with paired pre-and post-surgery follow‑up).Trajectory analysis identified terminally differentiated,secretory-specialized cell populations with lineage-specific hormone and cytokine hypersecretion.Ligand-receptor inference suggested these tumor-derived factors potentially engage circulating immune cell receptors.A random‑forest classifier based on PBMC transcriptomes distinguished PitNET subtypes,underscoring the diagnostic potential of peripheral immune signatures.Furthermore,in an estrogen-induced rat model,elevated PRL level coincided with the same peripheral immune skewing.Overall,our work provides a valuable resource and demonstrates PitNETs can be systemic immune modulators,where intrinsic hormone secretory activity and monocyte-lymphocyte imbalance collectively drive peripheral immune dysfunction.
基金supported by grants from the National Natural Science Foundation of China(Grant Nos.31830054 and 32293204)the Beijing Municipal Health Commission,China(JingYiYan2019-8Grant No.XTCX20180503).
文摘Single-cell RNA sequencing(scRNA-seq)has emerged as a valuable tool for studying cellular heterogeneity in various fields,particularly in virological research.By studying the viral and cellular transcriptomes,the dynamics of viral infection can be investigated at a single-cell resolution.However,limited studies have been conducted to investigate whether RNA transcripts from clinical samples contain substantial amounts of viral RNAs,and a specific computational framework for efficiently detecting viral reads based on scRNA-seq data has not been developed.Hence,we introduce DVsc,an open-source framework for precise quantitative analysis of viral infection from single-cell transcriptomics data.When applied to approximately 200 diverse clinical samples that were infected by more than 10 different viruses,DVsc demonstrated high accuracy in systematically detecting viral infection across a wide array of cell types.This innovative bioinformatics pipeline could be crucial for addressing the potential effects of surreptitiously invading viruses on certain illnesses,as well as for designing novel medicines to target viruses in specific host cell subsets and evaluating the efficacy of treatment.DVsc supports the FASTQ format as an input and is compatible with multiple single-cell sequencing platforms.Moreover,it could also be applied to sequences from bulk RNA sequencing data.DVsc is available at http://62.234.32.33:5000/DVsc.
