The accurate segmentation of deep gray matter nuclei is critical for neuropathological research,disease diagnosis and treatment.Existing methods employ the supervised learning training approach,which requires large la...The accurate segmentation of deep gray matter nuclei is critical for neuropathological research,disease diagnosis and treatment.Existing methods employ the supervised learning training approach,which requires large labeled datasets.It is challenging and time-consuming to obtain such datasets for medical image analysis.In addition,these methods based on convolutional neural networks(CNNs)only achieve suboptimal performance due to the locality of convolutional operations.Vision Transformers(ViTs)efficiently model long-range dependencies and thus have the potentiality to outperform these methods in segmentation tasks.To address these issues,we propose a novel hybrid network based on self-supervised pre-training for deep gray matter nuclei segmentation.Specifically,we present a CNN-Transformer hybrid network(CTNet),whose encoder consists of 3D CNN and ViT to learn local spatial-detailed features and global semantic information.A self-supervised learning(SSL)approach that integrates rotation prediction and masked feature reconstruction is proposed to pre-train the CTNet,enabling the model to learn valuable visual representations from unlabeled data.We evaluate the effectiveness of our method on 3T and 7T human brain MRI datasets.The results demonstrate that our CTNet achieves better performance than other comparison models and our pre-training strategy outperforms other advanced self-supervised methods.When the training set has only one sample,our pre-trained CTNet enhances segmentation performance,showing an 8.4%improvement in Dice similarity coefficient(DSC)compared to the randomly initialized CTNet.展开更多
Background:Submarine personnel often experience insomnia and reduced psychological resilience due to extended deployments in confined,high-stress environments.Effective non-pharmacological interventions are needed to ...Background:Submarine personnel often experience insomnia and reduced psychological resilience due to extended deployments in confined,high-stress environments.Effective non-pharmacological interventions are needed to improve sleep quality and resilience in this population.This study aimed to investigate the effect of virtual reality(VR)combined with forest therapy interventions on psychological resilience and sleep quality among submarine personnel with insomnia symptoms.Methods:Using convenience sampling,92 submarine personnel with insomnia symptoms undergoing recuperation at a PLA sanatorium between July 2023 and May 2025 were randomly allocated to experimental and control groups(n=46 each).The control group received forest therapy intervention,while the intervention group received combined VR and forest therapy interventions.Pre-and post-intervention assessments were conducted using the Pittsburgh Sleep Quality Index(PSQI)and Connor-Davidson Resilience Scale(CD-RISC).Results:There is no significant differences between two groups before the intervention on sleep or psychological resilience.Both groups showed significant pre-to post-intervention improvements in sleep and resilience;however,mixed-ANOVA results showed that the intervention(VR+forest therapy)group achieved significantly better outcomes than the control group at post-intervention after Bonferroni correction,including lower PSQI total and key component scores(subjective sleep quality,sleep efficiency,daytime dysfunction)and higher CD-RISC resilience scores.Conclusions:The integration of virtual reality and forest therapy effectively improved sleep quality and psychological resilience among submarine personnel with insomnia symptoms.This combined intervention shows promise as a non-pharmacological approach in military healthcare settings;however,further studies are needed to validate and generalize these findings.展开更多
The geogenic enrichment of arsenic(As)extensively occurred in the riverine systems from the Qinghai-Tibetan Plateau under active geothermal discharge and chemical weathering conditions,while little is known about how ...The geogenic enrichment of arsenic(As)extensively occurred in the riverine systems from the Qinghai-Tibetan Plateau under active geothermal discharge and chemical weathering conditions,while little is known about how dissolved organic matter(DOM)transformation regulates the aquatic As concentrations.The present study revealed that the DOM components from the Singe Tsangpo River(STR)basin primarily consisted of protein-like components(81.30%±6.48%),with the microbially-endogenous production being a predominant source under the control of temperature and glacier-runoff recharge along the river flow path.Notably,the chemical weathering processes have significantly facilitated the enhancement of humic-like components in the river water.Besides,the groundwater DOM characteristics were predominantly influenced by the mobilization of sedimentary organic matter and the introduction of allochthonous DOM resulting from surface-water recharge.Interestingly,humic-like components facilitated As enrichment through complexation and competitive adsorption effects in both surface water and groundwater under oxidizing conditions,whichwas supported by the significant positive correlations between As and humiclike component(R^(2)=0.31/0.65,P<0.05/0.01)and the concurrent mobilization of As and humic-like components from sediment incubation experiments.Moreover,the Structural Equation Modeling analysis revealed a stronger contribution of humic-like components to the As enrichment in the groundwater compared with surface water,possibly due to the relatively strongermicrobial activity and enhanced mobilization of humic-like components in alluvial aquifers.The present study thus provided new insights into the transformation of DOM and its important role in facilitating As enrichment in the aquatic environment from alpine river basins.展开更多
In this study,we utilized gene knockout and overexpression techniques to generate brewer's yeast strains with either a deletion or overexpression of the fatty acyl-CoA oxidase(POX1)gene.The strains studied include...In this study,we utilized gene knockout and overexpression techniques to generate brewer's yeast strains with either a deletion or overexpression of the fatty acyl-CoA oxidase(POX1)gene.The strains studied included the parental strain,the POX1 deletion strain,and the POX1 overexpression strain.These strains were exposed to iso-αacid from hops at a concentration of 300 mg/L,leading to the induction of a viable but nonculturable(VBNC)state.Our results indicated that the silencing of the POX1 gene rendered brewer's yeast cells unable to withstand the high concentration of iso-αacid stress,ultimately leading to cell death.Conversely,the overexpression of POX1 accelerated the transition of yeast cells into the VBNC state compared to the parental strain.Furthermore,we evaluated the levels of reactive oxygen species(ROS),catalase(CAT)activity,superoxide dismutase(SOD)activity,glutathione reductase(GR)activity,and the m RNA expression of genes that regulate these enzymes(the stress-inducible yeast Mpv17(SYM1)gene,CTA1,SOD1,and glutathione reductase(GLR1)gene)in brewer's yeast cells at three distinct stages:normal,short-term stress,and VBNC states.Based on these findings,it can be inferred that the formation of the VBNC state in brewer's yeast is associated with the response to oxidative stress.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 62071405the National Natural Science Foundation of China under Grant 12175189.
文摘The accurate segmentation of deep gray matter nuclei is critical for neuropathological research,disease diagnosis and treatment.Existing methods employ the supervised learning training approach,which requires large labeled datasets.It is challenging and time-consuming to obtain such datasets for medical image analysis.In addition,these methods based on convolutional neural networks(CNNs)only achieve suboptimal performance due to the locality of convolutional operations.Vision Transformers(ViTs)efficiently model long-range dependencies and thus have the potentiality to outperform these methods in segmentation tasks.To address these issues,we propose a novel hybrid network based on self-supervised pre-training for deep gray matter nuclei segmentation.Specifically,we present a CNN-Transformer hybrid network(CTNet),whose encoder consists of 3D CNN and ViT to learn local spatial-detailed features and global semantic information.A self-supervised learning(SSL)approach that integrates rotation prediction and masked feature reconstruction is proposed to pre-train the CTNet,enabling the model to learn valuable visual representations from unlabeled data.We evaluate the effectiveness of our method on 3T and 7T human brain MRI datasets.The results demonstrate that our CTNet achieves better performance than other comparison models and our pre-training strategy outperforms other advanced self-supervised methods.When the training set has only one sample,our pre-trained CTNet enhances segmentation performance,showing an 8.4%improvement in Dice similarity coefficient(DSC)compared to the randomly initialized CTNet.
文摘Background:Submarine personnel often experience insomnia and reduced psychological resilience due to extended deployments in confined,high-stress environments.Effective non-pharmacological interventions are needed to improve sleep quality and resilience in this population.This study aimed to investigate the effect of virtual reality(VR)combined with forest therapy interventions on psychological resilience and sleep quality among submarine personnel with insomnia symptoms.Methods:Using convenience sampling,92 submarine personnel with insomnia symptoms undergoing recuperation at a PLA sanatorium between July 2023 and May 2025 were randomly allocated to experimental and control groups(n=46 each).The control group received forest therapy intervention,while the intervention group received combined VR and forest therapy interventions.Pre-and post-intervention assessments were conducted using the Pittsburgh Sleep Quality Index(PSQI)and Connor-Davidson Resilience Scale(CD-RISC).Results:There is no significant differences between two groups before the intervention on sleep or psychological resilience.Both groups showed significant pre-to post-intervention improvements in sleep and resilience;however,mixed-ANOVA results showed that the intervention(VR+forest therapy)group achieved significantly better outcomes than the control group at post-intervention after Bonferroni correction,including lower PSQI total and key component scores(subjective sleep quality,sleep efficiency,daytime dysfunction)and higher CD-RISC resilience scores.Conclusions:The integration of virtual reality and forest therapy effectively improved sleep quality and psychological resilience among submarine personnel with insomnia symptoms.This combined intervention shows promise as a non-pharmacological approach in military healthcare settings;however,further studies are needed to validate and generalize these findings.
基金supported by the National Natural Science Foundation of China(No.42107094)Sichuan Science and Technology Program(No.2023NSFSC0806)the Geology Bureau project of Xinjiang Uygur Autonomous Region(Nos.XGMB202356 and XGMB202358).
文摘The geogenic enrichment of arsenic(As)extensively occurred in the riverine systems from the Qinghai-Tibetan Plateau under active geothermal discharge and chemical weathering conditions,while little is known about how dissolved organic matter(DOM)transformation regulates the aquatic As concentrations.The present study revealed that the DOM components from the Singe Tsangpo River(STR)basin primarily consisted of protein-like components(81.30%±6.48%),with the microbially-endogenous production being a predominant source under the control of temperature and glacier-runoff recharge along the river flow path.Notably,the chemical weathering processes have significantly facilitated the enhancement of humic-like components in the river water.Besides,the groundwater DOM characteristics were predominantly influenced by the mobilization of sedimentary organic matter and the introduction of allochthonous DOM resulting from surface-water recharge.Interestingly,humic-like components facilitated As enrichment through complexation and competitive adsorption effects in both surface water and groundwater under oxidizing conditions,whichwas supported by the significant positive correlations between As and humiclike component(R^(2)=0.31/0.65,P<0.05/0.01)and the concurrent mobilization of As and humic-like components from sediment incubation experiments.Moreover,the Structural Equation Modeling analysis revealed a stronger contribution of humic-like components to the As enrichment in the groundwater compared with surface water,possibly due to the relatively strongermicrobial activity and enhanced mobilization of humic-like components in alluvial aquifers.The present study thus provided new insights into the transformation of DOM and its important role in facilitating As enrichment in the aquatic environment from alpine river basins.
基金funded by National Natural Science Foundation of China(32272279)the Key R&D project of Shandong Province(2023CXPT007)the Key R&D project of Qingdao Science and Technology Plan(22-3-3-hygg-29-hy)。
文摘In this study,we utilized gene knockout and overexpression techniques to generate brewer's yeast strains with either a deletion or overexpression of the fatty acyl-CoA oxidase(POX1)gene.The strains studied included the parental strain,the POX1 deletion strain,and the POX1 overexpression strain.These strains were exposed to iso-αacid from hops at a concentration of 300 mg/L,leading to the induction of a viable but nonculturable(VBNC)state.Our results indicated that the silencing of the POX1 gene rendered brewer's yeast cells unable to withstand the high concentration of iso-αacid stress,ultimately leading to cell death.Conversely,the overexpression of POX1 accelerated the transition of yeast cells into the VBNC state compared to the parental strain.Furthermore,we evaluated the levels of reactive oxygen species(ROS),catalase(CAT)activity,superoxide dismutase(SOD)activity,glutathione reductase(GR)activity,and the m RNA expression of genes that regulate these enzymes(the stress-inducible yeast Mpv17(SYM1)gene,CTA1,SOD1,and glutathione reductase(GLR1)gene)in brewer's yeast cells at three distinct stages:normal,short-term stress,and VBNC states.Based on these findings,it can be inferred that the formation of the VBNC state in brewer's yeast is associated with the response to oxidative stress.
