Pulmonary embolism(PE)can range from minor,asymptomatic blood clots to life-threatening emboli capable of obstructing pulmonary arteries,potentially leading to cardiac arrest and fatal outcomes.Due to this significant...Pulmonary embolism(PE)can range from minor,asymptomatic blood clots to life-threatening emboli capable of obstructing pulmonary arteries,potentially leading to cardiac arrest and fatal outcomes.Due to this significant mortality risk,risk stratification is essential following PE diagnosis to guide appropriate therapeutic intervention.This study proposes a machine learning-based methodology for PE risk stratification,utilizing clinical data from a cohort of 139 patients.The predictive framework integrates an enhanced binary Honey Badger Algorithm(BCCHBA)with the K-Nearest Neighbor(KNN)classifier.To comprehensively evaluate the performance of the core optimization algorithm(CCHBA),a series of benchmark function tests were conducted.Furthermore,diagnostic validation tests were performed using real-world PE patient data collected from medical facilities,demonstrating the clinical significance and practical utility of the BCCHBA-KNN system.Analysis revealed the critical importance of specific indicators,including neutrophil percentage(NEUT%),systolic blood pressure(SBP),oxygen saturation(SaO2%),white blood cell count(WBC),and syncope.The classification results demonstrated exceptional performance,with the prediction model achieving 100%sensitivity and 99.09%accuracy.This approach holds promise as a novel and accurate method for assessing PE severity.展开更多
Epithelial-mesenchymal transition(EMT)is a critical cellular process in embryonic development and is also the basis for wound repair,tissue regeneration,and cancer metastasis(Zhao et al.,2015).During cancer migration ...Epithelial-mesenchymal transition(EMT)is a critical cellular process in embryonic development and is also the basis for wound repair,tissue regeneration,and cancer metastasis(Zhao et al.,2015).During cancer migration and invasion,EMT involved comprehensive reprogramming processes related to cytoskeletal remodeling,cell differentiation,epigenetic regulation and metabolism(Plikus et al.,2015).In fact,the understanding of EMT in cancer development is still limited.In 2015.展开更多
Pancreatic cancer （PC） occurs when malignant cells develop in the part of the pancreas, a glandular organ behind the stomach. For 2015, there are about 40,560 people dead of pancreatic cancer （20,710 men and 19,850...Pancreatic cancer （PC） occurs when malignant cells develop in the part of the pancreas, a glandular organ behind the stomach. For 2015, there are about 40,560 people dead of pancreatic cancer （20,710 men and 19,850 women） in the US （Siegel et al., 2015）. Though PC accounts for about 3% of all cancers in the US, it can cause about 7% of cancer deaths. This is mainly because that the early stages of this cancer do not usually produce symptoms, and thus the cancer is almost always fatal when it is diagnosed.展开更多
During oncogenesis,the hyper-activation of proto-oncogenes and defection of tumor suppressor genes（Zhao et al.,2012,2016a）can regulate cell proliferation,differentiation,apoptosis,and cell-to-cell communication（Bal...During oncogenesis,the hyper-activation of proto-oncogenes and defection of tumor suppressor genes（Zhao et al.,2012,2016a）can regulate cell proliferation,differentiation,apoptosis,and cell-to-cell communication（Balmain et al.,2003;Haber and Settleman,2007）.Recent evidence has shown that non-coding RNAs, such as microRNAs （miRNAs） （Chen, 2005）, and long non- coding RNAs （lncRNAs）, can also act as oncogenes to initiate and promote cancer progression.展开更多
Cancer metastasis is the end product of cancer evolution,contributing to the massive mortality of cancer patients（Chaffer and Weinberg,2011）.Different primary cancers have distinct spreading routes via the blood or ...Cancer metastasis is the end product of cancer evolution,contributing to the massive mortality of cancer patients（Chaffer and Weinberg,2011）.Different primary cancers have distinct spreading routes via the blood or the lymphatics or through both routes,which presents challenge for effective cancer treatment（Qian et aL,2017）.展开更多
Myocardial infarction (MI), the most serious of the ischemic heart diseases, is accompanied by myocardial metabolic disorders and the loss of cardiomyocytes. Increasing evidence has shown that long noncoding RNAs (lnc...Myocardial infarction (MI), the most serious of the ischemic heart diseases, is accompanied by myocardial metabolic disorders and the loss of cardiomyocytes. Increasing evidence has shown that long noncoding RNAs (lncRNAs) are involved in various pathological conditions such as cancer and cardiovascular diseases (CVDs), and are emerging as a novel biomarker for these disorders. This study aims to investigate the regulatory role and mechanisms of lncRNAs in myocardial remodeling in the setting of MI. We find that post-infarcted hearts exhibit a reduction of adenosine triphosphate (ATP) and an alteration of the glucose and lipid metabolism genes cluster of differentiation 36 (CD36), hexokinase 1 (HK1), and clucose transporter 4 (GLUT4), accompanied by cardiomyocyte pyroptosis. We then identify a previously unknown conserved lncRNA, AK009126 (cardiomyocyte pyroptosis-associated lncRNA, CPAL), which is remarkably upregulated in the myocardial border zone of MI mice. Importantly, the adeno-associated virus 9 (AAV9)-mediated silencing of endogenous CPAL by its short hairpin RNA (shRNA) partially abrogates myocardial metabolic alterations and cardiomyocyte pyroptosis during MI in mice. Mechanistically, CPAL is shown to bind directly to nuclear factor kappa B (NFκB) and to act as an activator of NFκB to induce NFκB phosphorylation in cardiomyocytes. We also find that CPAL upregulates caspase-1 expression at the transcriptional level and consequently promotes the release of interleukin (IL)-18 and IL-1β from cardiomyocytes. Collectively, our findings reveal the conserved lncRNA CPAL as a new regulator of cardiac metabolic abnormalities and cardiomyocyte pyroptosis in the setting of MI and suggest CPAL as a new therapeutic target to protect cardiomyocytes against ischemic injury in infarcted hearts.展开更多
Background:Cardiomyocytes derived from human embryonic stem cells(hESCs)are regulated by complex and stringent gene networks during differentiation.Long non-coding RNAs(lncRNAs)exert critical epigenetic regulatory fun...Background:Cardiomyocytes derived from human embryonic stem cells(hESCs)are regulated by complex and stringent gene networks during differentiation.Long non-coding RNAs(lncRNAs)exert critical epigenetic regulatory functions in multiple differentiation processes.However,the involvement of lncRNAs in the differentiation of hESCs into cardiomyocytes has not yet been fully elucidated.Here,we identified the key roles of ZFAS1(lncRNA zinc finger antisense 1)in the differentiation of cardiomyocytes from hESCs.Methods:A model of cardiomyocyte differentiation from stem cells was established using the monolayer differentiation method,and the number of beating hESCs-derived cardiomyocytes was calculated.Gene expression was analyzed by quantitative real-time PCR(qRTPCR).Immunofluorescence assays were performed to assess the expression of cardiac troponin T(cTnT)andα-actinin protein in cardiomyocytes.Results:qRT-PCR showed that ZFAS1 expression in the mesoderm was significantly higher than that in embryonic stem cells,cardiac progenitor cells,and cardiomyocytes.Knockdown of ZFAS1 inhibited cardiomyocyte differentiation from hESCs,which was characterized by reduced expression of the cardiac-specific markers cTnT,α-actinin,myosin heavy chain 6(MYH6),and myosin heavy chain 7(MYH7).In contrast,ZFAS1 overexpression remarkably increased the percentage of spontaneously beating cardiomyocytes.In terms of the mechanism,we found that ZFAS1 is an antisense lncRNA at the 5′end of the protein-coding gene ZNFX1.Knockdown of ZFAS1 could increase the mRNA expression level of ZNFX1.Furthermore,qRT-PCR demonstrated that the silencing of ZNFX1 led to an increase in cardiac-specific markers that predicted the promotion of cardiomyocyte differentiation.Conclusion:Altogether,these data suggest that lncRNA-ZFAS1 is required for cardiac differentiation by functionally inhibiting the expression of ZNFX1,which may provide a reference for the treatment of heart disease to a certain extent.展开更多
In order to achieve high-speed, real-time and accurate, an image acquisition method based on digital signal processor (DSP) TMS320DM642 is proposed for the paper currency image acquisition [1]. System will be high spe...In order to achieve high-speed, real-time and accurate, an image acquisition method based on digital signal processor (DSP) TMS320DM642 is proposed for the paper currency image acquisition [1]. System will be high speed digital signal processing (DSP) technology and complex programmable logic device (CPLD) and CIS acquisition module combination, the structure of acquisition system is given and the time series analysis, during the process of collecting this kind of design has the advantages of simple implementation, high recognition rate [2].展开更多
Comprehensive Summary.Accurate prediction for chemical reaction performance offers optimal direction for synthetic development. To this end, we present a novel multi-modal model called MMHRP-GCL to achieve the predict...Comprehensive Summary.Accurate prediction for chemical reaction performance offers optimal direction for synthetic development. To this end, we present a novel multi-modal model called MMHRP-GCL to achieve the prediction of homogeneous chemical reaction yield, enantioselectivity, and activation energy by fusing the information from the text and graph modalities, requiring only 8 simple descriptors and Reaction SMILES obtained without high-cost DFT computation, and capable of managing reactions involving a fluctuating number of molecules. Experimental results on 4 datasets show that MMHRP-GCL outperforms at least 7 generalized SOTA methods. Ablation study confirms the critical roles of the complementation of graph and text modalities, as well as the significance of modality alignment and atomic features in prediction. Albeit there is still room for improvement in the interpretation of atomic relationships, the model has a remarkable ability to identify important atoms. A statistically interpretable study of the feature importance and a test on challenging dataset further demonstrates the utility and potential of the model. As a high-accuracy, low-cost, interpretable, and general multi-modal model, MMHRP-GCL provides valuable guidance on the design of forward predictors for homogeneous catalytic reactions.展开更多
Data aggregation has been widely researched to address the privacy concern when data is published,meanwhile,data aggregation only obtains the sum or average in an area.In reality,more fine-grained data brings more val...Data aggregation has been widely researched to address the privacy concern when data is published,meanwhile,data aggregation only obtains the sum or average in an area.In reality,more fine-grained data brings more value for data consumers,such as more accurate management,dynamic price-adjusting in the grid system,etc.In this paper,a multi-subset data aggregation scheme for the smart grid is proposed without a trusted third party,in which the control center collects the number of users in different subsets,and obtains the sum of electricity consumption in each subset,meantime individual user’s data privacy is still preserved.In addition,the dynamic and flexible user management mechanism is guaranteed with the secret key negotiation process among users.The analysis shows MSDA not only protects users’privacy to resist various attacks but also achieves more functionality such as multi-subset aggregation,no reliance on any trusted third party,dynamicity.And performance evaluation demonstrates that MSDA is efficient and practical in terms of communication and computation overhead.展开更多
Current global energy and environmental crisis have spurred efforts towards developing sustainable biotechnological solutions,such as utilizing CO_(2) and its derivatives as raw materials.Formate is an attractive onec...Current global energy and environmental crisis have spurred efforts towards developing sustainable biotechnological solutions,such as utilizing CO_(2) and its derivatives as raw materials.Formate is an attractive onecarbon source due to its high solubility and low reduction potential.However,the regulatory mechanism of formate metabolism in yeast remains largely unexplored.This study employed adaptive laboratory evolution(ALE)to improve formate tolerance in Saccharomyces cerevisiae and characterized the underlying molecular mechanisms.The evolved strain was applied to produce free fatty acids(FFAs)under high concentration of formate with glucose addition.The results showed that the evolved strain achieved a FFAs titer of 250 mg/L.Overall,this study sheds light on the regulatory mechanism of formate tolerance and provides a platform for future studies under high concentrations of formate.展开更多
Metal-organic frameworks(MOFs)and their derivatives received more and more attention due to the diverse morphologies,rich porous structures,and tunable metal active sites,which have been widely used in energy-related ...Metal-organic frameworks(MOFs)and their derivatives received more and more attention due to the diverse morphologies,rich porous structures,and tunable metal active sites,which have been widely used in energy-related electrocatalytic reactions.Surfactants,a class of compounds with hydrophilic and hydrophobic portions in the molecular structure,are able to modulate the properties of liquid and solid surfaces.Surfactants play a crucial role in controlling the shape and size of MOFs,which helps optimize electrocatalytic performance,especially in improving the exposure and accessibility of catalytic active sites.In this review,we first outline the types and applications of surfactants.Second,we describe the interface modulation and reaction mechanism of different surfactants during the forming of MOFs and their derivatives.Finally,we discuss the current applications of surfactant-modified MOFs and their derivatives in electrocatalysis.This review provides a better understanding of surfactantassistant structure regulation and electrocatalytic activity study of MOFs and their derivatives.展开更多
Background:The causal relationship between visceral adipose tissue(VAT)and gout is still unclear.We aimed to examine the potential association between them using observational and Mendelian randomization(MR)analyses.M...Background:The causal relationship between visceral adipose tissue(VAT)and gout is still unclear.We aimed to examine the potential association between them using observational and Mendelian randomization(MR)analyses.Methods:In the observational analyses,a total of 11,967 participants(aged 39.5±11.5 years)were included from the National Health and Nutrition Examination Survey.Logistic regression models were used to investigate the association between VAT mass and the risk of gout.In two-sample MR analyses,211 VAT mass-related independent genetic variants(derived from genome-wide association studies in 325,153 UK biobank participants)were used as instrumental variables.The random-effects inverse-variance weighted(IVW)method was used as the primary analysis.Additional sensitivity analyses were also performed to validate our results.Results:Observational analyses found that an increase in VAT mass(per standard deviation)was associated with a higher risk of gout after controlling for confounding factors(odds ratio[OR]=1.27,95%confidence intervals[CI]=1.11-1.45).The two-sample MR analyses demonstrated a causal relationship between increased VAT mass and the risk of gout in primary analyses(OR=1.78,95%CI=1.57-2.03).Sensitivity analyses also showed similar findings,including MR-Egger,weighted median,simple mode,weighted mode,and leave-one-out analyses.Conclusions:Observational analyses showed a robust association of VAT mass with the risk of gout.Meanwhile,MR analyses also provided evidence of a causal relationship between them.In summary,our findings suggested that targeted interventions for VAT mass may be beneficial to prevent gout.展开更多
With the prevalence of Internet of Things(loT)devices,data collection has the potential to improve people's lives and create a significant value.However,it also exposes sensitive information,which leads to privacy...With the prevalence of Internet of Things(loT)devices,data collection has the potential to improve people's lives and create a significant value.However,it also exposes sensitive information,which leads to privacy risks.An approach called N-source anonymity has been used for privacy preservation in raw data collection,but most of the existing schemes do not have a balanced efficiency and robustness.In this work,a lightweight and efficient raw data collection scheme is proposed.The proposed scheme can not only collect data from the original users but also protect their privacy.Besides,the proposed scheme can resist user poisoning attacks,and the use of the reward method can motivate users to actively provide data.Analysis and simulation indicate that the proposed scheme is safe against poison attacks.Additionally,the proposed scheme has better performance in terms of computation and communication overhead compared to existing methods.High efficiency and appropriate incentive mechanisms indicate that the scheme is practical for IoT systems.展开更多
Sensors are widely applied in the collection of voice data.Since many attributes of voice data are sensitive such as user emotions,identity,raw voice collection may lead serious privacy threat.In the past,traditional ...Sensors are widely applied in the collection of voice data.Since many attributes of voice data are sensitive such as user emotions,identity,raw voice collection may lead serious privacy threat.In the past,traditional feature extraction obtains and encrypts voice features that are then transmitted to upstream servers.In order to avoid sensitive attribute disclosure,it is necessary to separate the sensitive attributes from non-sensitive attributes of voice data.Motivated by this,user-optional privacy transmission framework for voice data(called:Voice Fence Wall)is proposed.Firstly,we provide user-optional,which means users can choose the attributes(sensitive attributes)they want to be protected.Secondly,Voice Fence Wall utilizes minimum mutual information(MI)to reduce the correlation between sensitive and non-sensitive attributes,thereby separating these attributes.Finally,only the separated non-sensitive attributes are transmitted to the upstream server,the quality of voice services is satisfied without leaking sensitive attributes.To verify the reliability and practicability,three voice datasets are used to evaluate the model,the experiments demonstrate that Voice Fence Wall not only effectively separates attributes to resist attribute inference attacks,but also outperforms related work in terms of classification performance.Specifically,our framework achieves 89.84%accuracy in sentiment recognition and 6.01%equal error rate in voice authentication.展开更多
With the growing proportion of older adults globally,aging has emerged as a leading risk factor for a range of chronic diseases and mortality[1].This process is characterized by progressive degeneration and loss of fu...With the growing proportion of older adults globally,aging has emerged as a leading risk factor for a range of chronic diseases and mortality[1].This process is characterized by progressive degeneration and loss of function across multiple physiological systems[2].While chronological age is the most straightforward indicator of aging,the variability in aging across different organ systems[3]results in a wide variation in aging characteristics among individuals of the same chronological age[4,5].Recently,several promising DNA methylation(DNAm)-based algorithms(e,g.,HorvathAge,GrimAge,GrimAge2)have been developed to assess biological age by analyzing age-associated changes in DNAm patterns[6].These algorithms are now widely used in biological age assessment.Some of them have demonstrated robust predictive power for mortality and various age-related conditions[1].However,due to differences in objectives,meth-odologies,and tissue types used across these algorithms[6],it remains uncertain which tool best captures the true state of bio-logical aging.展开更多
文摘Pulmonary embolism(PE)can range from minor,asymptomatic blood clots to life-threatening emboli capable of obstructing pulmonary arteries,potentially leading to cardiac arrest and fatal outcomes.Due to this significant mortality risk,risk stratification is essential following PE diagnosis to guide appropriate therapeutic intervention.This study proposes a machine learning-based methodology for PE risk stratification,utilizing clinical data from a cohort of 139 patients.The predictive framework integrates an enhanced binary Honey Badger Algorithm(BCCHBA)with the K-Nearest Neighbor(KNN)classifier.To comprehensively evaluate the performance of the core optimization algorithm(CCHBA),a series of benchmark function tests were conducted.Furthermore,diagnostic validation tests were performed using real-world PE patient data collected from medical facilities,demonstrating the clinical significance and practical utility of the BCCHBA-KNN system.Analysis revealed the critical importance of specific indicators,including neutrophil percentage(NEUT%),systolic blood pressure(SBP),oxygen saturation(SaO2%),white blood cell count(WBC),and syncope.The classification results demonstrated exceptional performance,with the prediction model achieving 100%sensitivity and 99.09%accuracy.This approach holds promise as a novel and accurate method for assessing PE severity.
基金supported by the National Natural Science Foundation of China(Nos.31671375,31871339 and 31801120)the National Key Research and Development Program of China(No.2017YFC1201200)the research start-up fellowship of University of the Sunshine Coast to MZ.
文摘Epithelial-mesenchymal transition(EMT)is a critical cellular process in embryonic development and is also the basis for wound repair,tissue regeneration,and cancer metastasis(Zhao et al.,2015).During cancer migration and invasion,EMT involved comprehensive reprogramming processes related to cytoskeletal remodeling,cell differentiation,epigenetic regulation and metabolism(Plikus et al.,2015).In fact,the understanding of EMT in cancer development is still limited.In 2015.
文摘Pancreatic cancer （PC） occurs when malignant cells develop in the part of the pancreas, a glandular organ behind the stomach. For 2015, there are about 40,560 people dead of pancreatic cancer （20,710 men and 19,850 women） in the US （Siegel et al., 2015）. Though PC accounts for about 3% of all cancers in the US, it can cause about 7% of cancer deaths. This is mainly because that the early stages of this cancer do not usually produce symptoms, and thus the cancer is almost always fatal when it is diagnosed.
文摘During oncogenesis,the hyper-activation of proto-oncogenes and defection of tumor suppressor genes（Zhao et al.,2012,2016a）can regulate cell proliferation,differentiation,apoptosis,and cell-to-cell communication（Balmain et al.,2003;Haber and Settleman,2007）.Recent evidence has shown that non-coding RNAs, such as microRNAs （miRNAs） （Chen, 2005）, and long non- coding RNAs （lncRNAs）, can also act as oncogenes to initiate and promote cancer progression.
基金supported by the National Natural Science Foundation of China(Nos.31171270 and 31671375)the research start-up fellowship of University of the Sunshine Coast to M.Z
文摘Cancer metastasis is the end product of cancer evolution,contributing to the massive mortality of cancer patients（Chaffer and Weinberg,2011）.Different primary cancers have distinct spreading routes via the blood or the lymphatics or through both routes,which presents challenge for effective cancer treatment（Qian et aL,2017）.
文摘Myocardial infarction (MI), the most serious of the ischemic heart diseases, is accompanied by myocardial metabolic disorders and the loss of cardiomyocytes. Increasing evidence has shown that long noncoding RNAs (lncRNAs) are involved in various pathological conditions such as cancer and cardiovascular diseases (CVDs), and are emerging as a novel biomarker for these disorders. This study aims to investigate the regulatory role and mechanisms of lncRNAs in myocardial remodeling in the setting of MI. We find that post-infarcted hearts exhibit a reduction of adenosine triphosphate (ATP) and an alteration of the glucose and lipid metabolism genes cluster of differentiation 36 (CD36), hexokinase 1 (HK1), and clucose transporter 4 (GLUT4), accompanied by cardiomyocyte pyroptosis. We then identify a previously unknown conserved lncRNA, AK009126 (cardiomyocyte pyroptosis-associated lncRNA, CPAL), which is remarkably upregulated in the myocardial border zone of MI mice. Importantly, the adeno-associated virus 9 (AAV9)-mediated silencing of endogenous CPAL by its short hairpin RNA (shRNA) partially abrogates myocardial metabolic alterations and cardiomyocyte pyroptosis during MI in mice. Mechanistically, CPAL is shown to bind directly to nuclear factor kappa B (NFκB) and to act as an activator of NFκB to induce NFκB phosphorylation in cardiomyocytes. We also find that CPAL upregulates caspase-1 expression at the transcriptional level and consequently promotes the release of interleukin (IL)-18 and IL-1β from cardiomyocytes. Collectively, our findings reveal the conserved lncRNA CPAL as a new regulator of cardiac metabolic abnormalities and cardiomyocyte pyroptosis in the setting of MI and suggest CPAL as a new therapeutic target to protect cardiomyocytes against ischemic injury in infarcted hearts.
基金the National Natural Science Foundation of China[81573434 to BZC]Heilongjiang Touyan Innovation Team Program[BZC],HMU Marshal Initiative Funding(HMUMIF-21018 to BZC)National Nature Science Youth Foudation of China[82000226 to XFG].
文摘Background:Cardiomyocytes derived from human embryonic stem cells(hESCs)are regulated by complex and stringent gene networks during differentiation.Long non-coding RNAs(lncRNAs)exert critical epigenetic regulatory functions in multiple differentiation processes.However,the involvement of lncRNAs in the differentiation of hESCs into cardiomyocytes has not yet been fully elucidated.Here,we identified the key roles of ZFAS1(lncRNA zinc finger antisense 1)in the differentiation of cardiomyocytes from hESCs.Methods:A model of cardiomyocyte differentiation from stem cells was established using the monolayer differentiation method,and the number of beating hESCs-derived cardiomyocytes was calculated.Gene expression was analyzed by quantitative real-time PCR(qRTPCR).Immunofluorescence assays were performed to assess the expression of cardiac troponin T(cTnT)andα-actinin protein in cardiomyocytes.Results:qRT-PCR showed that ZFAS1 expression in the mesoderm was significantly higher than that in embryonic stem cells,cardiac progenitor cells,and cardiomyocytes.Knockdown of ZFAS1 inhibited cardiomyocyte differentiation from hESCs,which was characterized by reduced expression of the cardiac-specific markers cTnT,α-actinin,myosin heavy chain 6(MYH6),and myosin heavy chain 7(MYH7).In contrast,ZFAS1 overexpression remarkably increased the percentage of spontaneously beating cardiomyocytes.In terms of the mechanism,we found that ZFAS1 is an antisense lncRNA at the 5′end of the protein-coding gene ZNFX1.Knockdown of ZFAS1 could increase the mRNA expression level of ZNFX1.Furthermore,qRT-PCR demonstrated that the silencing of ZNFX1 led to an increase in cardiac-specific markers that predicted the promotion of cardiomyocyte differentiation.Conclusion:Altogether,these data suggest that lncRNA-ZFAS1 is required for cardiac differentiation by functionally inhibiting the expression of ZNFX1,which may provide a reference for the treatment of heart disease to a certain extent.
文摘In order to achieve high-speed, real-time and accurate, an image acquisition method based on digital signal processor (DSP) TMS320DM642 is proposed for the paper currency image acquisition [1]. System will be high speed digital signal processing (DSP) technology and complex programmable logic device (CPLD) and CIS acquisition module combination, the structure of acquisition system is given and the time series analysis, during the process of collecting this kind of design has the advantages of simple implementation, high recognition rate [2].
基金supported by the National Science Foundation of China(21903010)the Fundamental Research Funds for the Central Universities(DUT24BK047).
文摘Comprehensive Summary.Accurate prediction for chemical reaction performance offers optimal direction for synthetic development. To this end, we present a novel multi-modal model called MMHRP-GCL to achieve the prediction of homogeneous chemical reaction yield, enantioselectivity, and activation energy by fusing the information from the text and graph modalities, requiring only 8 simple descriptors and Reaction SMILES obtained without high-cost DFT computation, and capable of managing reactions involving a fluctuating number of molecules. Experimental results on 4 datasets show that MMHRP-GCL outperforms at least 7 generalized SOTA methods. Ablation study confirms the critical roles of the complementation of graph and text modalities, as well as the significance of modality alignment and atomic features in prediction. Albeit there is still room for improvement in the interpretation of atomic relationships, the model has a remarkable ability to identify important atoms. A statistically interpretable study of the feature importance and a test on challenging dataset further demonstrates the utility and potential of the model. As a high-accuracy, low-cost, interpretable, and general multi-modal model, MMHRP-GCL provides valuable guidance on the design of forward predictors for homogeneous catalytic reactions.
基金This work was supported partly by the National Natural Science Foundation of China(Grant Nos.61162016,62072133,U1811264,U1711263,61966009)the Natural Science Foundation of Guangxi Province(2018GXNSFDA281040,2018GXNSFDA281045)the Innovation Project of Guangxi Graduate Education(YCBZ2020062).
文摘Data aggregation has been widely researched to address the privacy concern when data is published,meanwhile,data aggregation only obtains the sum or average in an area.In reality,more fine-grained data brings more value for data consumers,such as more accurate management,dynamic price-adjusting in the grid system,etc.In this paper,a multi-subset data aggregation scheme for the smart grid is proposed without a trusted third party,in which the control center collects the number of users in different subsets,and obtains the sum of electricity consumption in each subset,meantime individual user’s data privacy is still preserved.In addition,the dynamic and flexible user management mechanism is guaranteed with the secret key negotiation process among users.The analysis shows MSDA not only protects users’privacy to resist various attacks but also achieves more functionality such as multi-subset aggregation,no reliance on any trusted third party,dynamicity.And performance evaluation demonstrates that MSDA is efficient and practical in terms of communication and computation overhead.
基金the National Key R&D Program of China[2021YFC2103500]Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project[TSBICIP-KJGG-009]+1 种基金National Natural Science Foundation of China[22211530047]Beijing Advanced Innovation Center for Soft Matter Science and Engineering,Beijing University of Chemical Technology。
文摘Current global energy and environmental crisis have spurred efforts towards developing sustainable biotechnological solutions,such as utilizing CO_(2) and its derivatives as raw materials.Formate is an attractive onecarbon source due to its high solubility and low reduction potential.However,the regulatory mechanism of formate metabolism in yeast remains largely unexplored.This study employed adaptive laboratory evolution(ALE)to improve formate tolerance in Saccharomyces cerevisiae and characterized the underlying molecular mechanisms.The evolved strain was applied to produce free fatty acids(FFAs)under high concentration of formate with glucose addition.The results showed that the evolved strain achieved a FFAs titer of 250 mg/L.Overall,this study sheds light on the regulatory mechanism of formate tolerance and provides a platform for future studies under high concentrations of formate.
基金supported by the National Natural Science Foundation of China(22178213,22375120,21975148,21601118)the Innovation Capability Support Program of Shaanxi(2023KJXX-018)+5 种基金the Fundamental Research Funds for the Central Universities(GK202207007,GK202309002,GK202103042)the Natural Science Basic Research Program of Shaanxi(2022JC-05)the Natural Science Foundation of Shaanxi Province of China(2022JM-069)the Starting Research Funds of Shaanxi Normal Universitythe 111 Project(B14041)the International Joint Research Center on Advanced Characterizations of Xi'an City。
文摘Metal-organic frameworks(MOFs)and their derivatives received more and more attention due to the diverse morphologies,rich porous structures,and tunable metal active sites,which have been widely used in energy-related electrocatalytic reactions.Surfactants,a class of compounds with hydrophilic and hydrophobic portions in the molecular structure,are able to modulate the properties of liquid and solid surfaces.Surfactants play a crucial role in controlling the shape and size of MOFs,which helps optimize electrocatalytic performance,especially in improving the exposure and accessibility of catalytic active sites.In this review,we first outline the types and applications of surfactants.Second,we describe the interface modulation and reaction mechanism of different surfactants during the forming of MOFs and their derivatives.Finally,we discuss the current applications of surfactant-modified MOFs and their derivatives in electrocatalysis.This review provides a better understanding of surfactantassistant structure regulation and electrocatalytic activity study of MOFs and their derivatives.
基金supported by grants from the Natural Science Foundation of China(Nos.82102199 and 82301768)the Pudong New Area Clinical Plateau Discipline Project(No.PWYgy2021-03)the general program of Shanghai Municipal Commission of Health and Family Planning(No.202040479).
文摘Background:The causal relationship between visceral adipose tissue(VAT)and gout is still unclear.We aimed to examine the potential association between them using observational and Mendelian randomization(MR)analyses.Methods:In the observational analyses,a total of 11,967 participants(aged 39.5±11.5 years)were included from the National Health and Nutrition Examination Survey.Logistic regression models were used to investigate the association between VAT mass and the risk of gout.In two-sample MR analyses,211 VAT mass-related independent genetic variants(derived from genome-wide association studies in 325,153 UK biobank participants)were used as instrumental variables.The random-effects inverse-variance weighted(IVW)method was used as the primary analysis.Additional sensitivity analyses were also performed to validate our results.Results:Observational analyses found that an increase in VAT mass(per standard deviation)was associated with a higher risk of gout after controlling for confounding factors(odds ratio[OR]=1.27,95%confidence intervals[CI]=1.11-1.45).The two-sample MR analyses demonstrated a causal relationship between increased VAT mass and the risk of gout in primary analyses(OR=1.78,95%CI=1.57-2.03).Sensitivity analyses also showed similar findings,including MR-Egger,weighted median,simple mode,weighted mode,and leave-one-out analyses.Conclusions:Observational analyses showed a robust association of VAT mass with the risk of gout.Meanwhile,MR analyses also provided evidence of a causal relationship between them.In summary,our findings suggested that targeted interventions for VAT mass may be beneficial to prevent gout.
基金supported in part by the National Natural Science Foundation of China(62072133)the Innovation Project of Guangxi Graduate Education(YCSW2022279)Wenzhou Science and Technology Plan(2023ZW0013).
文摘With the prevalence of Internet of Things(loT)devices,data collection has the potential to improve people's lives and create a significant value.However,it also exposes sensitive information,which leads to privacy risks.An approach called N-source anonymity has been used for privacy preservation in raw data collection,but most of the existing schemes do not have a balanced efficiency and robustness.In this work,a lightweight and efficient raw data collection scheme is proposed.The proposed scheme can not only collect data from the original users but also protect their privacy.Besides,the proposed scheme can resist user poisoning attacks,and the use of the reward method can motivate users to actively provide data.Analysis and simulation indicate that the proposed scheme is safe against poison attacks.Additionally,the proposed scheme has better performance in terms of computation and communication overhead compared to existing methods.High efficiency and appropriate incentive mechanisms indicate that the scheme is practical for IoT systems.
基金supported by National Natural Science Foundation of China(62072133)the Innovation Project of Guangxi Graduate Education(YCSW2023330)。
文摘Sensors are widely applied in the collection of voice data.Since many attributes of voice data are sensitive such as user emotions,identity,raw voice collection may lead serious privacy threat.In the past,traditional feature extraction obtains and encrypts voice features that are then transmitted to upstream servers.In order to avoid sensitive attribute disclosure,it is necessary to separate the sensitive attributes from non-sensitive attributes of voice data.Motivated by this,user-optional privacy transmission framework for voice data(called:Voice Fence Wall)is proposed.Firstly,we provide user-optional,which means users can choose the attributes(sensitive attributes)they want to be protected.Secondly,Voice Fence Wall utilizes minimum mutual information(MI)to reduce the correlation between sensitive and non-sensitive attributes,thereby separating these attributes.Finally,only the separated non-sensitive attributes are transmitted to the upstream server,the quality of voice services is satisfied without leaking sensitive attributes.To verify the reliability and practicability,three voice datasets are used to evaluate the model,the experiments demonstrate that Voice Fence Wall not only effectively separates attributes to resist attribute inference attacks,but also outperforms related work in terms of classification performance.Specifically,our framework achieves 89.84%accuracy in sentiment recognition and 6.01%equal error rate in voice authentication.
基金supported by grants from the National Natural Science Foundation of China (grant number 82301768 to H.Z.)the International Joint Laboratory on Tropical Diseases Control in Greater Mekong Subregion (grant number 21410750200 to X.L.)
文摘With the growing proportion of older adults globally,aging has emerged as a leading risk factor for a range of chronic diseases and mortality[1].This process is characterized by progressive degeneration and loss of function across multiple physiological systems[2].While chronological age is the most straightforward indicator of aging,the variability in aging across different organ systems[3]results in a wide variation in aging characteristics among individuals of the same chronological age[4,5].Recently,several promising DNA methylation(DNAm)-based algorithms(e,g.,HorvathAge,GrimAge,GrimAge2)have been developed to assess biological age by analyzing age-associated changes in DNAm patterns[6].These algorithms are now widely used in biological age assessment.Some of them have demonstrated robust predictive power for mortality and various age-related conditions[1].However,due to differences in objectives,meth-odologies,and tissue types used across these algorithms[6],it remains uncertain which tool best captures the true state of bio-logical aging.
