Fos-related antigen 1(Fra-1)is a nuclear transcription factor that regulates cell growth,differentiation,and apoptosis.It is involved in the proliferation,invasion,apoptosis and epithelial mesenchymal transformation o...Fos-related antigen 1(Fra-1)is a nuclear transcription factor that regulates cell growth,differentiation,and apoptosis.It is involved in the proliferation,invasion,apoptosis and epithelial mesenchymal transformation of malignant tumor cells.Fra-1 is highly expressed in gastric cancer(GC),affects the cycle distribution and apoptosis of GC cells,and participates in GC occurrence and development.However,the detailed mechanism of Fra-1 in GC is unclear,such as the identification of Fra-1-interacting proteins and their role in GC pathogenesis.In this study,we identified tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein eta(YWHAH)as a Fra-1-interacting protein in GC cells using co-immunoprecipitation combined with liquid chromatography-tandem mass spectrometry.Experiments showed that YWHAH positively regulated Fra-1 mRNA and protein expression,and affected GC cell proliferation.Whole proteome analysis showed that Fra-1 affected the activity of the high mobility group AT-hook 1(HMGA1)/phosphatidylinositol-4,5-bisphosphate 3-kinase(PI3K)/protein kinase B(AKT)/mechanistic target of rapamycin(mTOR)signaling pathway in GC cells.Western blotting and flow cytometry confirmed that YWHAH activated HMGA1/PI3K/AKT/mTOR signaling pathway by positively regulating Fra-1 to affect GC cell proliferation.These results will help to discover new molecular targets for the early diagnosis,treatment,and prognosis prediction of GC.展开更多
Since the early nineteen seventies, the gold price has been dramatically changed. The price of an ounce of gold was only about 30 dollars in the early nineteen seventies. Yet, at the beginning of the 80＇s, the price ...Since the early nineteen seventies, the gold price has been dramatically changed. The price of an ounce of gold was only about 30 dollars in the early nineteen seventies. Yet, at the beginning of the 80＇s, the price rose to nearly S700 per ounce. And at the beginning of this century, the price lowered down to S270 per ounce. Again, it reached a highest price in 30 years in September,展开更多
Communication between group 3 innate lymphoid cells(ILC3)and other immune cells,as well as intestinal epithelial cells,is pivotal in regulating intestinal inflammation.This study,for the first time,underscores the imp...Communication between group 3 innate lymphoid cells(ILC3)and other immune cells,as well as intestinal epithelial cells,is pivotal in regulating intestinal inflammation.This study,for the first time,underscores the importance of crosstalk between intestinal endothelial cells(ECs)and ILC3.Our single-cell transcriptome analysis combined with protein expression detection revealed that ECs significantly increased the population of interleukin(IL)-22+ILC3 through interactions mediated by endothelin-1(ET-1)and its receptor endothelin A receptor(EDNRA).Genetic deficiency of EDNRA reduces the proportion of NKp46+ILC3 and impairs IL-22 production in a T-cell-independent,cell-intrinsic manner,leading to increased intestinal inflammation.Mechanistically,the ET-1-EDNRA axis modulates hypoxia-inducible factor 1 alpha(HIF-1α)through protein kinase B(AKT)signaling,supporting metabolic adaptation toward glycolysis and providing protection against colitis.Moreover,restoring HIF-1αexpression or providing exogenous lactate can alleviate colitis associated with EDNRA deficiency and ILC3 glycolytic dysfunction.These findings underscore the importance of communication between intestinal ECs and ILC3 via the ET-1-EDNRA axis in metabolic adaptation processes within ILC3 and maintaining intestinal homeostasis.展开更多
This study mapped the areal extent,identified the species composition,and analyzed the changes of salt marshes in the intertidal zone of China during the period 1985–2019.With the aid of the cloud platform of the Goo...This study mapped the areal extent,identified the species composition,and analyzed the changes of salt marshes in the intertidal zone of China during the period 1985–2019.With the aid of the cloud platform of the Google Earth Engine,we selected Landsat 5/8 and Sentinel-2 images and used the support vector machine classification method to extract salt marsh information for the years of 1985,1990,1995,2000,2005,2010,2015,and 2019.Seven major species of salt marshes:Phragmites australis,Suaeda spp.,Spartina alterniflora,Scirpus mariqueter,Tamarix chinensis,Cyperus malaccensis,and Sesuvium portulacastrum were identified.Our results showed that salt marshes are mainly distributed in Liaoning,Shandong,Jiangsu,Shanghai,and Zhejiang,with varying patterns of shrinking,expansion,or wavering in different places.The distribution of salt marshes has declined considerably from 151,324 ha in 1985 to 115,397 ha in 2019,a drop of 23.7%.During the same period,the area of native species has dropped 95.4%from 77,741 ha to 3,563 ha for Suaeda spp.and 45.1%from 60,511 ha to 33,193 ha for P.australis;on the contrary,the area of exotic species,S.alterniflora,has exhibited a sharp rise from just 99 ha to 67,527 ha.For the past 35 years,the driving factors causing salt marsh changes are mainly land reclamation,variations in water and sand fluxes,and interspecific competition and succession of salt marsh vegetation.These results provide fundamental reference information and could form the scientific basis for formulating policies for the conservation and utilization of salt marsh resources in China.展开更多
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevent...Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevention and control strategies. In this study, we utilized historical incidence data of SFTS (2013–2020) in Shandong Province, China to establish three univariate prediction models based on two time-series forecasting algorithms Autoregressive Integrated Moving Average (ARIMA) and Prophet, as well as a special type of recurrent neural network Long Short-Term Memory (LSTM) algorithm. We then evaluated and compared the performance of these models. All three models demonstrated good predictive capabilities for SFTS cases, with the predicted results closely aligning with the actual cases. Among the models, the LSTM model exhibited the best fitting and prediction performance. It achieved the lowest values for mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). The number of SFTS cases in the subsequent 5 years in this area were also generated using this model. The LSTM model, being simple and practical, provides valuable information and data for assessing the potential risk of SFTS in advance. This information is crucial for the development of early warning systems and the formulation of effective prevention and control measures for SFTS.展开更多
The algal community structure is vital for aquatic management.However,the complicated environmental and biological processes make modeling challenging.To cope with this difficulty,we investigated using random forests(...The algal community structure is vital for aquatic management.However,the complicated environmental and biological processes make modeling challenging.To cope with this difficulty,we investigated using random forests(RF)to predict phytoplankton community shifting based on multi-source environmental factors(including physicochemical,hydrological,and meteorological variables).The RF models robustly predicted the algal communities composed by 13 major classes(Bray-Curtis dissimilarity=9.2±7.0%,validation NRMSE mostly<10%),with accurate simulations to the total biomass(validation R^(2)>0.74)in Norway's largest lake,Lake Mjosa.The importance analysis showed that the hydro-meteorological variables(Standardized MSE and Node Purity mostly>0.5)were the most influential factors in regulating the phytoplankton.Furthermore,an in-depth ecological interpretation uncovered the interactive stress-response effect on the algal community learned by the RF models.The interpretation results disclosed that the environmental drivers(i.e.,temperature,lake inflow,and nutrients)can jointly pose strong influence on the algal community shifts.This study highlighted the power of machine learning in predicting complex algal community structures and provided insights into the model interpretability.展开更多
基金This work was supported by the Hunan Provincial Natural Science Foundation(2021JJ30915).
文摘Fos-related antigen 1(Fra-1)is a nuclear transcription factor that regulates cell growth,differentiation,and apoptosis.It is involved in the proliferation,invasion,apoptosis and epithelial mesenchymal transformation of malignant tumor cells.Fra-1 is highly expressed in gastric cancer(GC),affects the cycle distribution and apoptosis of GC cells,and participates in GC occurrence and development.However,the detailed mechanism of Fra-1 in GC is unclear,such as the identification of Fra-1-interacting proteins and their role in GC pathogenesis.In this study,we identified tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein eta(YWHAH)as a Fra-1-interacting protein in GC cells using co-immunoprecipitation combined with liquid chromatography-tandem mass spectrometry.Experiments showed that YWHAH positively regulated Fra-1 mRNA and protein expression,and affected GC cell proliferation.Whole proteome analysis showed that Fra-1 affected the activity of the high mobility group AT-hook 1(HMGA1)/phosphatidylinositol-4,5-bisphosphate 3-kinase(PI3K)/protein kinase B(AKT)/mechanistic target of rapamycin(mTOR)signaling pathway in GC cells.Western blotting and flow cytometry confirmed that YWHAH activated HMGA1/PI3K/AKT/mTOR signaling pathway by positively regulating Fra-1 to affect GC cell proliferation.These results will help to discover new molecular targets for the early diagnosis,treatment,and prognosis prediction of GC.
文摘Since the early nineteen seventies, the gold price has been dramatically changed. The price of an ounce of gold was only about 30 dollars in the early nineteen seventies. Yet, at the beginning of the 80＇s, the price rose to nearly S700 per ounce. And at the beginning of this century, the price lowered down to S270 per ounce. Again, it reached a highest price in 30 years in September,
基金supported by grants from the National Natural Science Foundation of China(Nos.82171706 and 82471736 to YMH)the Guangdong Basic and Applied Basic Research Foundation(Nos.2022A1515140172 and 2024A1515012897 to YMH)the Open Fund Project of Guangdong Academy of Medical Sciences(No.YKY-KF202209 to YMH).
文摘Communication between group 3 innate lymphoid cells(ILC3)and other immune cells,as well as intestinal epithelial cells,is pivotal in regulating intestinal inflammation.This study,for the first time,underscores the importance of crosstalk between intestinal endothelial cells(ECs)and ILC3.Our single-cell transcriptome analysis combined with protein expression detection revealed that ECs significantly increased the population of interleukin(IL)-22+ILC3 through interactions mediated by endothelin-1(ET-1)and its receptor endothelin A receptor(EDNRA).Genetic deficiency of EDNRA reduces the proportion of NKp46+ILC3 and impairs IL-22 production in a T-cell-independent,cell-intrinsic manner,leading to increased intestinal inflammation.Mechanistically,the ET-1-EDNRA axis modulates hypoxia-inducible factor 1 alpha(HIF-1α)through protein kinase B(AKT)signaling,supporting metabolic adaptation toward glycolysis and providing protection against colitis.Moreover,restoring HIF-1αexpression or providing exogenous lactate can alleviate colitis associated with EDNRA deficiency and ILC3 glycolytic dysfunction.These findings underscore the importance of communication between intestinal ECs and ILC3 via the ET-1-EDNRA axis in metabolic adaptation processes within ILC3 and maintaining intestinal homeostasis.
基金This study was supported in part by the Ministry of Natural Resources(Blue Carbon Initiative and Policy)the Department of Science and Technology,Zhejiang Province(2016C04004)the Fundamental Research Funds for the Zhejiang Provincial Universities(2021XZZX012).
文摘This study mapped the areal extent,identified the species composition,and analyzed the changes of salt marshes in the intertidal zone of China during the period 1985–2019.With the aid of the cloud platform of the Google Earth Engine,we selected Landsat 5/8 and Sentinel-2 images and used the support vector machine classification method to extract salt marsh information for the years of 1985,1990,1995,2000,2005,2010,2015,and 2019.Seven major species of salt marshes:Phragmites australis,Suaeda spp.,Spartina alterniflora,Scirpus mariqueter,Tamarix chinensis,Cyperus malaccensis,and Sesuvium portulacastrum were identified.Our results showed that salt marshes are mainly distributed in Liaoning,Shandong,Jiangsu,Shanghai,and Zhejiang,with varying patterns of shrinking,expansion,or wavering in different places.The distribution of salt marshes has declined considerably from 151,324 ha in 1985 to 115,397 ha in 2019,a drop of 23.7%.During the same period,the area of native species has dropped 95.4%from 77,741 ha to 3,563 ha for Suaeda spp.and 45.1%from 60,511 ha to 33,193 ha for P.australis;on the contrary,the area of exotic species,S.alterniflora,has exhibited a sharp rise from just 99 ha to 67,527 ha.For the past 35 years,the driving factors causing salt marsh changes are mainly land reclamation,variations in water and sand fluxes,and interspecific competition and succession of salt marsh vegetation.These results provide fundamental reference information and could form the scientific basis for formulating policies for the conservation and utilization of salt marsh resources in China.
基金funded by Medical Science and Technology Projects,China(JK2023GK002,JK2023GK003,and JK2023GK004).
文摘Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevention and control strategies. In this study, we utilized historical incidence data of SFTS (2013–2020) in Shandong Province, China to establish three univariate prediction models based on two time-series forecasting algorithms Autoregressive Integrated Moving Average (ARIMA) and Prophet, as well as a special type of recurrent neural network Long Short-Term Memory (LSTM) algorithm. We then evaluated and compared the performance of these models. All three models demonstrated good predictive capabilities for SFTS cases, with the predicted results closely aligning with the actual cases. Among the models, the LSTM model exhibited the best fitting and prediction performance. It achieved the lowest values for mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). The number of SFTS cases in the subsequent 5 years in this area were also generated using this model. The LSTM model, being simple and practical, provides valuable information and data for assessing the potential risk of SFTS in advance. This information is crucial for the development of early warning systems and the formulation of effective prevention and control measures for SFTS.
基金supported by the National Natural Science Foundation of China(21876148)the Zhejiang Provincial Natural Science Foundation/Funds for Distinguished Young Scientists(LR22D06003)+3 种基金the Key Laboratory of Marine Ecological Monitoring and Restoration Technologies of the Ministry of Natural Resources of China(MEMRT202102)Science Foundation of Donghai Laboratory(DH-2022KF01021)Fundamental Research Funds for the Central Universities(226-2022-00119)Funding for ZJU Tang Scholar to X.X.The authors acknowledge the data sharing from the Norwegian Institute for Water Research(NIVA).
文摘The algal community structure is vital for aquatic management.However,the complicated environmental and biological processes make modeling challenging.To cope with this difficulty,we investigated using random forests(RF)to predict phytoplankton community shifting based on multi-source environmental factors(including physicochemical,hydrological,and meteorological variables).The RF models robustly predicted the algal communities composed by 13 major classes(Bray-Curtis dissimilarity=9.2±7.0%,validation NRMSE mostly<10%),with accurate simulations to the total biomass(validation R^(2)>0.74)in Norway's largest lake,Lake Mjosa.The importance analysis showed that the hydro-meteorological variables(Standardized MSE and Node Purity mostly>0.5)were the most influential factors in regulating the phytoplankton.Furthermore,an in-depth ecological interpretation uncovered the interactive stress-response effect on the algal community learned by the RF models.The interpretation results disclosed that the environmental drivers(i.e.,temperature,lake inflow,and nutrients)can jointly pose strong influence on the algal community shifts.This study highlighted the power of machine learning in predicting complex algal community structures and provided insights into the model interpretability.
