Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been s...Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.展开更多
Deepfake-generated fake faces,commonly utilized in identity-related activities such as political propaganda,celebrity impersonations,evidence forgery,and familiar fraud,pose new societal threats.Although current deepf...Deepfake-generated fake faces,commonly utilized in identity-related activities such as political propaganda,celebrity impersonations,evidence forgery,and familiar fraud,pose new societal threats.Although current deepfake generators strive for high realism in visual effects,they do not replicate biometric signals indicative of cardiac activity.Addressing this gap,many researchers have developed detection methods focusing on biometric characteristics.These methods utilize classification networks to analyze both temporal and spectral domain features of the remote photoplethysmography(rPPG)signal,resulting in high detection accuracy.However,in the spectral analysis,existing approaches often only consider the power spectral density and neglect the amplitude spectrum—both crucial for assessing cardiac activity.We introduce a novel method that extracts rPPG signals from multiple regions of interest through remote photoplethysmography and processes them using Fast Fourier Transform(FFT).The resultant time-frequency domain signal samples are organized into matrices to create Matrix Visualization Heatmaps(MVHM),which are then utilized to train an image classification network.Additionally,we explored various combinations of time-frequency domain representations of rPPG signals and the impact of attention mechanisms.Our experimental results show that our algorithm achieves a remarkable detection accuracy of 99.22%in identifying fake videos,significantly outperforming mainstream algorithms and demonstrating the effectiveness of Fourier Transform and attention mechanisms in detecting fake faces.展开更多
Background: Mucosal-associated invariant T(MAIT) cells are systemically depleted in human immunodeficiency virus type 1(HIV-1) infected patients and are not replenished even after successful combined antiretroviral th...Background: Mucosal-associated invariant T(MAIT) cells are systemically depleted in human immunodeficiency virus type 1(HIV-1) infected patients and are not replenished even after successful combined antiretroviral therapy(cART).This study aimed to identify the mechanism underlying MAIT cell depletion.Methods: In the present study, we applied flow cytometry, single-cell RNA sequencing and immunohistochemical staining to evaluate the characteristics of pyroptotic MAIT cells in a total of 127 HIV-1 infected individuals, including 69 treatment-naive patients, 28 complete responders, 15 immunological non-responders, and 15 elite controllers, at the Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.Results: Single-cell transcriptomic profiles revealed that circulating MAIT cells from HIV-1 infected subjects were highly activated, with upregulation of pyroptosis-related genes. Further analysis revealed that increased frequencies of pyroptotic MAIT cells correlated with markers of systemic T-cell activation, microbial translocation, and intestinal damage in cART-naive patients and poor CD4+ T-cell recovery in long-term cART patients. Immunohistochemical staining revealed that MAIT cells in the gut mucosa of HIV-1 infected patients exhibited a strong active gasdermin-D(GSDMD, marker of pyroptosis) signal near the cavity side, suggesting that these MAIT cells underwent active pyroptosis in the colorectal mucosa. Increased levels of the proinflammatory cytokines interleukin-12(IL-12) and IL-18 were observed in HIV-1 infected patients. In addition, activated MAIT cells exhibited an increased pyroptotic phenotype after being triggered by HIV-1 virions, T-cell receptor signals, IL-12 plus IL-18, and combinations of these factors, in vitro.Conclusions: Activation-induced MAIT cell pyroptosis contributes to the loss of MAIT cells in HIV-1 infected patients,which could potentiate disease progression and poor immune reconstitution.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.32200590 to K.L.,81972358 to Q.W.,91959113 to Q.W.,and 82372897 to Q.W.)the Natural Science Foundation of Jiangsu Province(Grant No.BK20210530 to K.L.).
文摘Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.
基金supported by the National Nature Science Foundation of China(Grant Number:61962010).
文摘Deepfake-generated fake faces,commonly utilized in identity-related activities such as political propaganda,celebrity impersonations,evidence forgery,and familiar fraud,pose new societal threats.Although current deepfake generators strive for high realism in visual effects,they do not replicate biometric signals indicative of cardiac activity.Addressing this gap,many researchers have developed detection methods focusing on biometric characteristics.These methods utilize classification networks to analyze both temporal and spectral domain features of the remote photoplethysmography(rPPG)signal,resulting in high detection accuracy.However,in the spectral analysis,existing approaches often only consider the power spectral density and neglect the amplitude spectrum—both crucial for assessing cardiac activity.We introduce a novel method that extracts rPPG signals from multiple regions of interest through remote photoplethysmography and processes them using Fast Fourier Transform(FFT).The resultant time-frequency domain signal samples are organized into matrices to create Matrix Visualization Heatmaps(MVHM),which are then utilized to train an image classification network.Additionally,we explored various combinations of time-frequency domain representations of rPPG signals and the impact of attention mechanisms.Our experimental results show that our algorithm achieves a remarkable detection accuracy of 99.22%in identifying fake videos,significantly outperforming mainstream algorithms and demonstrating the effectiveness of Fourier Transform and attention mechanisms in detecting fake faces.
基金supported by the Peking University Clinical Scientist Program Special(BMU2019LCKXJ013)the National Natural Science Foundation Innovation Research Group Project(81721002)+2 种基金the Sanming Project of Medicine Project in Shenzhen(SZSM201612014)the Yunnan Applied Basic Research Projects-Union Foundation by Yunnan Provincial Department of Science and Technology and Kunming Medical University(202001AY070001-154)the Scientific Research Fund of Education Department of Yunnan Province(2021J0297)。
文摘Background: Mucosal-associated invariant T(MAIT) cells are systemically depleted in human immunodeficiency virus type 1(HIV-1) infected patients and are not replenished even after successful combined antiretroviral therapy(cART).This study aimed to identify the mechanism underlying MAIT cell depletion.Methods: In the present study, we applied flow cytometry, single-cell RNA sequencing and immunohistochemical staining to evaluate the characteristics of pyroptotic MAIT cells in a total of 127 HIV-1 infected individuals, including 69 treatment-naive patients, 28 complete responders, 15 immunological non-responders, and 15 elite controllers, at the Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.Results: Single-cell transcriptomic profiles revealed that circulating MAIT cells from HIV-1 infected subjects were highly activated, with upregulation of pyroptosis-related genes. Further analysis revealed that increased frequencies of pyroptotic MAIT cells correlated with markers of systemic T-cell activation, microbial translocation, and intestinal damage in cART-naive patients and poor CD4+ T-cell recovery in long-term cART patients. Immunohistochemical staining revealed that MAIT cells in the gut mucosa of HIV-1 infected patients exhibited a strong active gasdermin-D(GSDMD, marker of pyroptosis) signal near the cavity side, suggesting that these MAIT cells underwent active pyroptosis in the colorectal mucosa. Increased levels of the proinflammatory cytokines interleukin-12(IL-12) and IL-18 were observed in HIV-1 infected patients. In addition, activated MAIT cells exhibited an increased pyroptotic phenotype after being triggered by HIV-1 virions, T-cell receptor signals, IL-12 plus IL-18, and combinations of these factors, in vitro.Conclusions: Activation-induced MAIT cell pyroptosis contributes to the loss of MAIT cells in HIV-1 infected patients,which could potentiate disease progression and poor immune reconstitution.
