AIM:To investigate the role of genetic polymorphisms in the progression of hepatic fibrosis in hereditary haemochromatosis.METHODS:A cohort of 245 well-characterised C282Y homozygous patients with haemochromatosis was...AIM:To investigate the role of genetic polymorphisms in the progression of hepatic fibrosis in hereditary haemochromatosis.METHODS:A cohort of 245 well-characterised C282Y homozygous patients with haemochromatosis was studied,with all subjects having liver biopsy data and DNA available for testing.This study assessed the association of eight single nucleotide polymorphisms(SNPs)in a total of six genes including toll-like receptor 4(TLR4),transforming growth factor-beta(TGF-β),oxoguanine DNA glycosylase,monocyte chemoattractant protein 1,chemokine C-C motif receptor 2 and interleukin-10 with liver disease severity.Genotyping was performed using high resolution melt analysis and sequencing.The results were analysed in relation to the stage of hepatic fibrosis in multivariate analysis incorporating other cofactors including alcohol consumption and hepatic iron concentration.RESULTS:There were significant associations between the cofactors of male gender(P=0.0001),increasing age(P=0.006),alcohol consumption(P=0.0001),steatosis(P=0.03),hepatic iron concentration(P<0.0001)and the presence of hepatic fibrosis.Of the candidate gene polymorphisms studied,none showed a significant association with hepatic fibrosis in univariate or multivariate analysis incorporating cofactors.We also specifically studied patients with hepatic iron loading above threshold levels for cirrhosis and compared the genetic polymorphisms between those with no fibrosis vs cirrhosis however there was no significant effect from any of the candidate genes studied.Importantly,in this large,well characterised cohort of patients there was no association between SNPs for TGF-βor TLR4and the presence of fibrosis,cirrhosis or increasing fibrosis stage in multivariate analysis.CONCLUSION:In our large,well characterised group of haemochromatosis subjects we did not demonstrate any relationship between candidate gene polymorphisms and hepatic fibrosis or cirrhosis.展开更多
In-situ observations on α/γ phase transformation were made to study the effects of grain boundary microstructures on the formation of a new phase and the migration of α/γ interphase boundary in an iron4. 2%Cr allo...In-situ observations on α/γ phase transformation were made to study the effects of grain boundary microstructures on the formation of a new phase and the migration of α/γ interphase boundary in an iron4. 2%Cr alloy. It was found that triple junctions with more random boundaries could be the primary nucleation sites for a new phase, while triple junctions with low angle or low ∑ coincidence boundaries did not play any role as preferential sites. The migration of α/γ interphase boundary during heating over the transformation temperature range showed the two stage behaviour characterized by a stage with a migration velocity of 0. 33-0. 75 mm/s and secondly by a stage with 3. 7-7. 6 mm/s. It was also found that abnormal grain growth and a high density of ∑3 coincidence boundaries could occur in a phase with bcc structure after cycling of α/γ phase transformation. A new mechanism of nucleation and growth of a new phase in α/γ phase transformation is proposed on the basis of roles of plane-matching interphase boundaries, as previously discussed on the origin of anisotropy of grain growth due to the migration of {110} plane-matching boundaries in Fe-3z%Si alloy. The most recent theoretical work on the distribution of plane-matching boundaries in solids with different crystal structures was found to be useful for the understanding of nucleation and growth during α/γ phase transformation.展开更多
critical for guiding treatment and improving patient outcomes.Traditional molecular subtyping via immuno-histochemistry(IHC)test is invasive,time-consuming,and may not fully represent tumor heterogeneity.This study pr...critical for guiding treatment and improving patient outcomes.Traditional molecular subtyping via immuno-histochemistry(IHC)test is invasive,time-consuming,and may not fully represent tumor heterogeneity.This study proposes a non-invasive approach using digital mammography images and deep learning algorithm for classifying breast cancer molecular subtypes.Four pretrained models,including two Convolutional Neural Networks(MobileNet_V3_Large and VGG-16)and two Vision Transformers(ViT_B_16 and ViT_Base_Patch16_Clip_224)were fine-tuned to classify images into HER2-enriched,Luminal,Normal-like,and Triple Negative subtypes.Hyperparameter tuning,including learning rate adjustment and layer freezing strategies,was applied to optimize performance.Among the evaluated models,ViT_Base_Patch16_Clip_224 achieved the highest test accuracy(94.44%),with equally high precision,recall,and F1-score of 0.94,demonstrating excellent generalization.MobileNet_V3_Large achieved the same accuracy but showed less training stability.In contrast,VGG-16 recorded the lowest performance,indicating a limitation in its generalizability for this classification task.The study also highlighted the superior performance of the Vision Transformer models over CNNs,particularly due to their ability to capture global contextual features and the benefit of CLIP-based pretraining in ViT_Base_Patch16_Clip_224.To enhance clinical applicability,a graphical user interface(GUI)named“BCMS Dx”was developed for streamlined subtype prediction.Deep learning applied to mammography has proven effective for accurate and non-invasive molecular subtyping.The proposed Vision Transformer-based model and supporting GUI offer a promising direction for augmenting diagnostic workflows,minimizing the need for invasive procedures,and advancing personalized breast cancer management.展开更多
We reported in this manuscript that TGF-beta1 induces apoptosis in AML12 murine hepatocytes, which is associated with the activation of p38 MAPK signaling pathway. SB202190, a specific inhibitor of p38 MAPK, strongly ...We reported in this manuscript that TGF-beta1 induces apoptosis in AML12 murine hepatocytes, which is associated with the activation of p38 MAPK signaling pathway. SB202190, a specific inhibitor of p38 MAPK, strongly inhibited the TGF-beta1-induced apoptosis and PAI-1 promoter activity. Treatment of cells with TGF-beta1 activates p38. Furthermore, over-expression of dominant negative mutant p38 also reduced the TGF-beta1-induced apoptosis. The data indicate that the activation of p38 is involved in TGF-beta1-mediated gene expression and apoptosis.展开更多
Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds tha...Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.展开更多
Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the b...Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the burden on medical staff and provides quantitative information,existing methodologies and recent models still struggle to accurately capture and classify the fine boundaries and diverse morphologies of tumors.In order to address these challenges and maximize the performance of brain tumor segmentation,this research introduces a novel SwinUNETR-based model by integrating a new decoder block,the Hierarchical Channel-wise Attention Decoder(HCAD),into a powerful SwinUNETR encoder.The HCAD decoder block utilizes hierarchical features and channelspecific attention mechanisms to further fuse information at different scales transmitted from the encoder and preserve spatial details throughout the reconstruction phase.Rigorous evaluations on the recent BraTS GLI datasets demonstrate that the proposed SwinHCAD model achieved superior and improved segmentation accuracy on both the Dice score and HD95 metrics across all tumor subregions(WT,TC,and ET)compared to baseline models.In particular,the rationale and contribution of the model design were clarified through ablation studies to verify the effectiveness of the proposed HCAD decoder block.The results of this study are expected to greatly contribute to enhancing the efficiency of clinical diagnosis and treatment planning by increasing the precision of automated brain tumor segmentation.展开更多
With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contex...With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contextual understanding,sequential dependencies,and/or data imbalance.This makes distinction between genuine and fabricated news a challenging task.To address this problem,we propose a novel hybrid architecture,T5-SA-LSTM,which synergistically integrates the T5 Transformer for semantically rich contextual embedding with the Self-Attentionenhanced(SA)Long Short-Term Memory(LSTM).The LSTM is trained using the Adam optimizer,which provides faster and more stable convergence compared to the Stochastic Gradient Descend(SGD)and Root Mean Square Propagation(RMSProp).The WELFake and FakeNewsPrediction datasets are used,which consist of labeled news articles having fake and real news samples.Tokenization and Synthetic Minority Over-sampling Technique(SMOTE)methods are used for data preprocessing to ensure linguistic normalization and class imbalance.The incorporation of the Self-Attention(SA)mechanism enables the model to highlight critical words and phrases,thereby enhancing predictive accuracy.The proposed model is evaluated using accuracy,precision,recall(sensitivity),and F1-score as performance metrics.The model achieved 99%accuracy on the WELFake dataset and 96.5%accuracy on the FakeNewsPrediction dataset.It outperformed the competitive schemes such as T5-SA-LSTM(RMSProp),T5-SA-LSTM(SGD)and some other models.展开更多
Image registration is an indispensable component in multi-source remote sensing image processing. In this paper, we put forward a remote sensing image registration method by including an improved multi-scale and multi...Image registration is an indispensable component in multi-source remote sensing image processing. In this paper, we put forward a remote sensing image registration method by including an improved multi-scale and multi-direction Harris algorithm and a novel compound feature. Multi-scale circle Gaussian combined invariant moments and multi-direction gray level co-occurrence matrix are extracted as features for image matching. The proposed algorithm is evaluated on numerous multi-source remote sensor images with noise and illumination changes. Extensive experimental studies prove that our proposed method is capable of receiving stable and even distribution of key points as well as obtaining robust and accurate correspondence matches. It is a promising scheme in multi-source remote sensing image registration.展开更多
基金Supported by NHMRC Medical Postgraduate Scholarship and the Royal Brisbane and Women’s Hospital Research Foundation to Wood MJthe National Health and Medical Research Council(NHMRC)to Ramm GA and Powell LW+1 种基金the recipient of an NHMRC Senior Research Fellowship,1024672 to Subramaniam VNan NHMRC Senior Research Fellowship,No.552409 to Ramm GA
文摘AIM:To investigate the role of genetic polymorphisms in the progression of hepatic fibrosis in hereditary haemochromatosis.METHODS:A cohort of 245 well-characterised C282Y homozygous patients with haemochromatosis was studied,with all subjects having liver biopsy data and DNA available for testing.This study assessed the association of eight single nucleotide polymorphisms(SNPs)in a total of six genes including toll-like receptor 4(TLR4),transforming growth factor-beta(TGF-β),oxoguanine DNA glycosylase,monocyte chemoattractant protein 1,chemokine C-C motif receptor 2 and interleukin-10 with liver disease severity.Genotyping was performed using high resolution melt analysis and sequencing.The results were analysed in relation to the stage of hepatic fibrosis in multivariate analysis incorporating other cofactors including alcohol consumption and hepatic iron concentration.RESULTS:There were significant associations between the cofactors of male gender(P=0.0001),increasing age(P=0.006),alcohol consumption(P=0.0001),steatosis(P=0.03),hepatic iron concentration(P<0.0001)and the presence of hepatic fibrosis.Of the candidate gene polymorphisms studied,none showed a significant association with hepatic fibrosis in univariate or multivariate analysis incorporating cofactors.We also specifically studied patients with hepatic iron loading above threshold levels for cirrhosis and compared the genetic polymorphisms between those with no fibrosis vs cirrhosis however there was no significant effect from any of the candidate genes studied.Importantly,in this large,well characterised cohort of patients there was no association between SNPs for TGF-βor TLR4and the presence of fibrosis,cirrhosis or increasing fibrosis stage in multivariate analysis.CONCLUSION:In our large,well characterised group of haemochromatosis subjects we did not demonstrate any relationship between candidate gene polymorphisms and hepatic fibrosis or cirrhosis.
文摘In-situ observations on α/γ phase transformation were made to study the effects of grain boundary microstructures on the formation of a new phase and the migration of α/γ interphase boundary in an iron4. 2%Cr alloy. It was found that triple junctions with more random boundaries could be the primary nucleation sites for a new phase, while triple junctions with low angle or low ∑ coincidence boundaries did not play any role as preferential sites. The migration of α/γ interphase boundary during heating over the transformation temperature range showed the two stage behaviour characterized by a stage with a migration velocity of 0. 33-0. 75 mm/s and secondly by a stage with 3. 7-7. 6 mm/s. It was also found that abnormal grain growth and a high density of ∑3 coincidence boundaries could occur in a phase with bcc structure after cycling of α/γ phase transformation. A new mechanism of nucleation and growth of a new phase in α/γ phase transformation is proposed on the basis of roles of plane-matching interphase boundaries, as previously discussed on the origin of anisotropy of grain growth due to the migration of {110} plane-matching boundaries in Fe-3z%Si alloy. The most recent theoretical work on the distribution of plane-matching boundaries in solids with different crystal structures was found to be useful for the understanding of nucleation and growth during α/γ phase transformation.
基金funded by the Ministry of Higher Education(MoHE)Malaysia through the Fundamental Research Grant Scheme—Early Career Researcher(FRGS-EC),grant number FRGSEC/1/2024/ICT02/UNIMAP/02/8.
文摘critical for guiding treatment and improving patient outcomes.Traditional molecular subtyping via immuno-histochemistry(IHC)test is invasive,time-consuming,and may not fully represent tumor heterogeneity.This study proposes a non-invasive approach using digital mammography images and deep learning algorithm for classifying breast cancer molecular subtypes.Four pretrained models,including two Convolutional Neural Networks(MobileNet_V3_Large and VGG-16)and two Vision Transformers(ViT_B_16 and ViT_Base_Patch16_Clip_224)were fine-tuned to classify images into HER2-enriched,Luminal,Normal-like,and Triple Negative subtypes.Hyperparameter tuning,including learning rate adjustment and layer freezing strategies,was applied to optimize performance.Among the evaluated models,ViT_Base_Patch16_Clip_224 achieved the highest test accuracy(94.44%),with equally high precision,recall,and F1-score of 0.94,demonstrating excellent generalization.MobileNet_V3_Large achieved the same accuracy but showed less training stability.In contrast,VGG-16 recorded the lowest performance,indicating a limitation in its generalizability for this classification task.The study also highlighted the superior performance of the Vision Transformer models over CNNs,particularly due to their ability to capture global contextual features and the benefit of CLIP-based pretraining in ViT_Base_Patch16_Clip_224.To enhance clinical applicability,a graphical user interface(GUI)named“BCMS Dx”was developed for streamlined subtype prediction.Deep learning applied to mammography has proven effective for accurate and non-invasive molecular subtyping.The proposed Vision Transformer-based model and supporting GUI offer a promising direction for augmenting diagnostic workflows,minimizing the need for invasive procedures,and advancing personalized breast cancer management.
基金grants fromthe Chinese Academy of Sciences (No. KJ951-BI608), the National Natural Sciences FOundation ofChina (No. 39625007 and
文摘We reported in this manuscript that TGF-beta1 induces apoptosis in AML12 murine hepatocytes, which is associated with the activation of p38 MAPK signaling pathway. SB202190, a specific inhibitor of p38 MAPK, strongly inhibited the TGF-beta1-induced apoptosis and PAI-1 promoter activity. Treatment of cells with TGF-beta1 activates p38. Furthermore, over-expression of dominant negative mutant p38 also reduced the TGF-beta1-induced apoptosis. The data indicate that the activation of p38 is involved in TGF-beta1-mediated gene expression and apoptosis.
文摘Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.
基金supported by Institute of Information&Communications Technology Planning&Evaluation(IITP)under the Metaverse Support Program to Nurture the Best Talents(IITP-2024-RS-2023-00254529)grant funded by the Korea government(MSIT).
文摘Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics.While MRI-based automatic brain tumor segmentation technology reduces the burden on medical staff and provides quantitative information,existing methodologies and recent models still struggle to accurately capture and classify the fine boundaries and diverse morphologies of tumors.In order to address these challenges and maximize the performance of brain tumor segmentation,this research introduces a novel SwinUNETR-based model by integrating a new decoder block,the Hierarchical Channel-wise Attention Decoder(HCAD),into a powerful SwinUNETR encoder.The HCAD decoder block utilizes hierarchical features and channelspecific attention mechanisms to further fuse information at different scales transmitted from the encoder and preserve spatial details throughout the reconstruction phase.Rigorous evaluations on the recent BraTS GLI datasets demonstrate that the proposed SwinHCAD model achieved superior and improved segmentation accuracy on both the Dice score and HD95 metrics across all tumor subregions(WT,TC,and ET)compared to baseline models.In particular,the rationale and contribution of the model design were clarified through ablation studies to verify the effectiveness of the proposed HCAD decoder block.The results of this study are expected to greatly contribute to enhancing the efficiency of clinical diagnosis and treatment planning by increasing the precision of automated brain tumor segmentation.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R195)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contextual understanding,sequential dependencies,and/or data imbalance.This makes distinction between genuine and fabricated news a challenging task.To address this problem,we propose a novel hybrid architecture,T5-SA-LSTM,which synergistically integrates the T5 Transformer for semantically rich contextual embedding with the Self-Attentionenhanced(SA)Long Short-Term Memory(LSTM).The LSTM is trained using the Adam optimizer,which provides faster and more stable convergence compared to the Stochastic Gradient Descend(SGD)and Root Mean Square Propagation(RMSProp).The WELFake and FakeNewsPrediction datasets are used,which consist of labeled news articles having fake and real news samples.Tokenization and Synthetic Minority Over-sampling Technique(SMOTE)methods are used for data preprocessing to ensure linguistic normalization and class imbalance.The incorporation of the Self-Attention(SA)mechanism enables the model to highlight critical words and phrases,thereby enhancing predictive accuracy.The proposed model is evaluated using accuracy,precision,recall(sensitivity),and F1-score as performance metrics.The model achieved 99%accuracy on the WELFake dataset and 96.5%accuracy on the FakeNewsPrediction dataset.It outperformed the competitive schemes such as T5-SA-LSTM(RMSProp),T5-SA-LSTM(SGD)and some other models.
基金supported by National Nature Science Foundation of China (Nos. 61462046 and 61762052)Natural Science Foundation of Jiangxi Province (Nos. 20161BAB202049 and 20161BAB204172)+2 种基金the Bidding Project of the Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASG (Nos. WE2016003, WE2016013 and WE2016015)the Science and Technology Research Projects of Jiangxi Province Education Department (Nos. GJJ160741, GJJ170632 and GJJ170633)the Art Planning Project of Jiangxi Province (Nos. YG2016250 and YG2017381)
文摘Image registration is an indispensable component in multi-source remote sensing image processing. In this paper, we put forward a remote sensing image registration method by including an improved multi-scale and multi-direction Harris algorithm and a novel compound feature. Multi-scale circle Gaussian combined invariant moments and multi-direction gray level co-occurrence matrix are extracted as features for image matching. The proposed algorithm is evaluated on numerous multi-source remote sensor images with noise and illumination changes. Extensive experimental studies prove that our proposed method is capable of receiving stable and even distribution of key points as well as obtaining robust and accurate correspondence matches. It is a promising scheme in multi-source remote sensing image registration.
