The liver performs several vital functions such as metabolism,toxin removal,and glucose storage through the coordination of various cell types.With the recent breakthrough of the single-cell/single-nucleus RNAseq(sc/s...The liver performs several vital functions such as metabolism,toxin removal,and glucose storage through the coordination of various cell types.With the recent breakthrough of the single-cell/single-nucleus RNAseq(sc/snRNA-seq)techniques,there is a great opportunity to establish a reference cell map of the liver at single-cell resolution with transcriptome-wise features.In this study,we build a unified liver cell atlas uniLIVER(http://lifeome.net/database/uniliver)by integrative analysis of a large-scale sc/snRNA-seq data collection of normal human liver with 331,125 cells and 79 samples from 6 datasets.Moreover,we introduce LiverCT,a machine learning based method for mapping any query dataset to the liver reference map by introducing the definition of“variant”cellular states analogous to the sequence variants in genomic analysis.Applying LiverCT on liver cancer datasets,we find that the“deviated”states of T cells are highly correlated with the stress pathway activities in hepatocellular carcinoma,and the enrichments of tumor cells with the hepatocyte-cholangiocyte“intermediate”states significantly indicate poor prognosis.Besides,we find that the tumor cells of different patients have different zonation tendencies and this zonation tendency is also significantly associated with the prognosis.This reference atlas mapping framework can also be extended to any other tissues.展开更多
Purpose: In acute lymphoblastic leukemia (ALL), multidrug resistance is often mediated by AT- Pase Binding Cassette (ABC) proteins, which principally involve ABCC1 (multidrug resistance protein 1, MRP1) and ABCB1 (mul...Purpose: In acute lymphoblastic leukemia (ALL), multidrug resistance is often mediated by AT- Pase Binding Cassette (ABC) proteins, which principally involve ABCC1 (multidrug resistance protein 1, MRP1) and ABCB1 (multidrug resistance 1, MDR1). However, direct comparisons between the differential effects of ABCC1 and ABCB1 have been difficult, since identical cell lines with differential expression of these transporters have not been developed. Experimental Design: In this study, we developed and compared the biological profiles of Jurkat cell lines that selectively over-expressed ABCC1 and ABCB1. Vincristine (VCR) plays an important role in the treatment of T-lineage ALL (T-ALL), and is often the first drug given to newly-diagnosed patients. Because of its importance in treatment, we provide descalating, sub-lethal doses of VCR to Jurkat cells, and extended our observations to expression profiling of newly diagnosed patients with T-ALL. Results: We found that VCR-resistant cells over-expressed ABCC1 nearly 30-fold. The calcein AM assay confirmed that VCR-resistant cells actively extruded VCR, and that ABCC1-mediated drug resistance conferred a different spectrum of multidrug resistance than other T-ALL induction agents. siRNA experiments that blocked ABCC1 export confirmed that VCR resistance could be reversed in vitro. Analyses of T-lymphoblasts obtained from 100 newly diagnosed T-ALL patients treated on Children’s Oncology Group Phase III studies 9404 and AALL0434 that induction failure could be could be partially explained by the over-expression of ABCC1 and ABCB1. Conclusions: Taken together, these results suggest that over-expression of ABC transporters plays a contributing role in mediating treatment failure in T-ALL, and underscore the need to employ alternate treatment approaches in patients for whom induction failed or for those with relapsed disease.展开更多
Medical imaging is essential for the diagnosis and treatment of liver diseases,and the objective analysis of such images is vital for precision medicine.Integration of artificial intelligence(AI),particularly computer...Medical imaging is essential for the diagnosis and treatment of liver diseases,and the objective analysis of such images is vital for precision medicine.Integration of artificial intelligence(AI),particularly computer vision,into hepatology has seen considerable growth.This study conducts a bibliometric analysis to map the evolution,principal trends,and focal points of AI in liver disease imaging research.We conducted a comprehensive literature review using the Web of Science Core Collection and PubMed databases,spanning January 1990 to July 2023,with keywords related to liver diseases and AI in medical imaging.The search resulted in 3,629 documents,with a surge in publications after 2017.The United States and China led in terms of publication volume,with the former exhibiting higher H-index scores and citation counts.However,greater number of research institutions that contribute significantly to publications in the relevant fields are based in China.Keyword analysis revealed extensive research on liver fibrosis,hepatocellular carcinoma,cirrhosis,and fatty liver disease.Techniques such as image segmentation,classification,and registration are prevalent,meeting clinical needs like lesion detection and disease prognosis.Convolutional neural networks(CNNs),particularly U-Net models,are predominantly utilized.This review synthesizes the findings to guide future advancements in AI-assisted liver disease diagnosis and management.展开更多
Hepatocyte proliferation is essential for recovering liver function after injury. Inliver surgery, the mechanical stimulation induced by hemodynamic changes triggers vascularendothelial cells (VECs) to secrete large a...Hepatocyte proliferation is essential for recovering liver function after injury. Inliver surgery, the mechanical stimulation induced by hemodynamic changes triggers vascularendothelial cells (VECs) to secrete large amounts of cytokines that enhance hepatocyte proliferation and play a pivotal role in liver regeneration (LR). Piezo1, a critical mechanosensory ionchannel, can detect and convert mechanical forces into chemical signals, importing externalstimuli into cells and triggering downstream biological effects. However, the precise role ofPiezo1 in VECs, especially in terms of mediating LR, remains unclear. Here, we report on a potential mechanism by which early changes in hepatic portal hemodynamics activate Piezo1 inVECs to promote hepatocyte proliferation during the process of LR induced by portal vein ligation in rats. In this LR model, hepatocyte proliferation is mainly distributed in zone 1 andzone 2 of liver lobules at 24e48 h after surgery, while only a small number of Ki67-positive hepatocytes were observed in zone 3. Activation of Piezo1 promotes increased secretion of epiregulin and amphiregulin from VECs via the PKC/ERK1/2 axis, further activating epidermalgrowth factor receptor (EGFR) and ERK1/2 signals in hepatocytes and promoting proliferation.In the liver lobules, the expression of EGFR in hepatocytes of zone 1 and zone 2 is significantlyhigher than that in zone 3. The EGFR inhibitor gefitinib inhibits LR by suppressing the proliferation of hepatocytes in the middle zone. These data provide a theoretical basis for the regulation of LR through chemical signals mediated by mechanical stimulation.展开更多
The liver serves as a central organ regulating numerous complex metabolic processes[1,2].Hepatic lobule metabolic zonation supports distinct hepatocyte functions through spatially dependent gene expression that is gov...The liver serves as a central organ regulating numerous complex metabolic processes[1,2].Hepatic lobule metabolic zonation supports distinct hepatocyte functions through spatially dependent gene expression that is governed by intricate signaling networks and interactions with diverse non-parenchymal cells[3–5].Notably,liver sinusoidal endothelial cells(LSECs)provide critical regulatory functions during hepatic regeneration and pathological adaptation[6].However,current hepatic pathology research is limited by inadequate models that poorly replicate human disease phenotypes and pharmacological responses.展开更多
Hepatocellular carcinoma(HCC)is a leading cause of cancer-related mortality,and resistance to systemic therapies remains a significant clinical challenge.This study investigated the mechanisms by which metabolic repro...Hepatocellular carcinoma(HCC)is a leading cause of cancer-related mortality,and resistance to systemic therapies remains a significant clinical challenge.This study investigated the mechanisms by which metabolic reprogramming contributes to systemic treatment resistance in HCC.We established HCC cell lines with multidrug resistance characteristics and observed enhanced metabolic activity in these cells.Integrated multiomics analyses revealed hyperactive glucose‒lipid and glutathione metabolic pathways that play critical roles in supporting tumor cell proliferation and survival.We constructed a metabolic reprogramming atlas for HCC-resistant cells and identified aldo-keto reductase(Aldo-keto reductase family 1 Member B1,AKR1B1)as a key regulator of this reprogramming,which sustains drug resistance by regulating energy metabolism and enhancing stress tolerance.Importantly,AKR1B1 expression levels are closely associated with drug resistance and poor prognosis in HCC patients.The secretory nature of AKR1B1 not only underscores its predictive value but also facilitates the intercellular transmission of drug resistance.In terms of overcoming resistance,the AKR1B1 inhibitor epalrestat significantly mitigated drug resistance when it was used in combination with standard therapies.These findings underscore the importance of metabolic reprogramming in the development of HCC resistance.AKR1B1,a key enzyme that regulates metabolic reprogramming,has been identified as a potential biomarker and therapeutic target,providing new insights into overcoming resistance in HCC treatment.展开更多
The creation of ex vivo human liver models has long been a critical objective in academic,clinical,and phar-maceutical research,particularly for drug development,where accurate evaluation of hepatic metabolic dy-namic...The creation of ex vivo human liver models has long been a critical objective in academic,clinical,and phar-maceutical research,particularly for drug development,where accurate evaluation of hepatic metabolic dy-namics is crucial.We have developed a bioengineered,perfused,organ-level human liver model that accurately replicates key liver functions,including metabolic activities,and protein synthesis,thus addressing some of the limitations associated with traditional liver monolayers,organoids,and matrix-embedded liver cells.Our approach utilizes liver-specific biomatrix scaffolds,prepared using an innovative protocol and fortified with matrix components that facilitate cellular interactions.These scaffolds,when seeded with human fetal liver cells or co-seeded with liver parenchymal and endothelial cell lines,enable the formation of three-dimensional(3D)human livers with enhanced cellular organization.The“recellularized tissue-engineered livers”(RCLs)have undergone various analyses,demonstrating the capability for establishing liver microenvironments ex vivo.Within 7-14 days,the RCLs exhibit evidence of liver differentiation and metabolic capabilities,underscoring the potential for use in drug metabolism and toxicity studies.Although our study represents a significant step for-ward,we acknowledge the need for direct comparisons with existing models and further research to fully elucidate the spectrum of regenerative responses.The high drug-metabolizing enzyme activity of RCLs,as demonstrated in our study,provides a promising avenue for investigating drug-induced liver injury mechanisms,contributing to a more detailed understanding of early drug discovery processes.展开更多
The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implem...The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle.展开更多
基金funded by the National Key Research and Development Program of China(No.2021YFF1200901)the National Natural Science Foundation of China(Nos.61721003,62133006,and 92268104)。
文摘The liver performs several vital functions such as metabolism,toxin removal,and glucose storage through the coordination of various cell types.With the recent breakthrough of the single-cell/single-nucleus RNAseq(sc/snRNA-seq)techniques,there is a great opportunity to establish a reference cell map of the liver at single-cell resolution with transcriptome-wise features.In this study,we build a unified liver cell atlas uniLIVER(http://lifeome.net/database/uniliver)by integrative analysis of a large-scale sc/snRNA-seq data collection of normal human liver with 331,125 cells and 79 samples from 6 datasets.Moreover,we introduce LiverCT,a machine learning based method for mapping any query dataset to the liver reference map by introducing the definition of“variant”cellular states analogous to the sequence variants in genomic analysis.Applying LiverCT on liver cancer datasets,we find that the“deviated”states of T cells are highly correlated with the stress pathway activities in hepatocellular carcinoma,and the enrichments of tumor cells with the hepatocyte-cholangiocyte“intermediate”states significantly indicate poor prognosis.Besides,we find that the tumor cells of different patients have different zonation tendencies and this zonation tendency is also significantly associated with the prognosis.This reference atlas mapping framework can also be extended to any other tissues.
文摘Purpose: In acute lymphoblastic leukemia (ALL), multidrug resistance is often mediated by AT- Pase Binding Cassette (ABC) proteins, which principally involve ABCC1 (multidrug resistance protein 1, MRP1) and ABCB1 (multidrug resistance 1, MDR1). However, direct comparisons between the differential effects of ABCC1 and ABCB1 have been difficult, since identical cell lines with differential expression of these transporters have not been developed. Experimental Design: In this study, we developed and compared the biological profiles of Jurkat cell lines that selectively over-expressed ABCC1 and ABCB1. Vincristine (VCR) plays an important role in the treatment of T-lineage ALL (T-ALL), and is often the first drug given to newly-diagnosed patients. Because of its importance in treatment, we provide descalating, sub-lethal doses of VCR to Jurkat cells, and extended our observations to expression profiling of newly diagnosed patients with T-ALL. Results: We found that VCR-resistant cells over-expressed ABCC1 nearly 30-fold. The calcein AM assay confirmed that VCR-resistant cells actively extruded VCR, and that ABCC1-mediated drug resistance conferred a different spectrum of multidrug resistance than other T-ALL induction agents. siRNA experiments that blocked ABCC1 export confirmed that VCR resistance could be reversed in vitro. Analyses of T-lymphoblasts obtained from 100 newly diagnosed T-ALL patients treated on Children’s Oncology Group Phase III studies 9404 and AALL0434 that induction failure could be could be partially explained by the over-expression of ABCC1 and ABCB1. Conclusions: Taken together, these results suggest that over-expression of ABC transporters plays a contributing role in mediating treatment failure in T-ALL, and underscore the need to employ alternate treatment approaches in patients for whom induction failed or for those with relapsed disease.
基金supported in part by grants from the following sources:National Key Research and Development Program of China(Grant Nos.2022YFA1103400,2022YFC2406704)National Natural Science Foundation of China(Grant Nos.92168207,82090051,32371477)Tsinghua Precision Medicine Foundation(Grant No.2022TS013).
文摘Medical imaging is essential for the diagnosis and treatment of liver diseases,and the objective analysis of such images is vital for precision medicine.Integration of artificial intelligence(AI),particularly computer vision,into hepatology has seen considerable growth.This study conducts a bibliometric analysis to map the evolution,principal trends,and focal points of AI in liver disease imaging research.We conducted a comprehensive literature review using the Web of Science Core Collection and PubMed databases,spanning January 1990 to July 2023,with keywords related to liver diseases and AI in medical imaging.The search resulted in 3,629 documents,with a surge in publications after 2017.The United States and China led in terms of publication volume,with the former exhibiting higher H-index scores and citation counts.However,greater number of research institutions that contribute significantly to publications in the relevant fields are based in China.Keyword analysis revealed extensive research on liver fibrosis,hepatocellular carcinoma,cirrhosis,and fatty liver disease.Techniques such as image segmentation,classification,and registration are prevalent,meeting clinical needs like lesion detection and disease prognosis.Convolutional neural networks(CNNs),particularly U-Net models,are predominantly utilized.This review synthesizes the findings to guide future advancements in AI-assisted liver disease diagnosis and management.
基金supported by the National Key Research and Development Program of China(No.2022YFA1103400)the CAMS Innovation Fund for Medical Sciences(No.2019-I2M-5e056)+2 种基金the National Natural Science Foundation of China(No.81930119,92168207,32371477,82090051)the Precision Medicine Research Program of Tsinghua University(No.10001020612)the National High Level Hospital Clinical Research Funding(China)(No.2022-NHLHCRF-LX-03-0102).
文摘Hepatocyte proliferation is essential for recovering liver function after injury. Inliver surgery, the mechanical stimulation induced by hemodynamic changes triggers vascularendothelial cells (VECs) to secrete large amounts of cytokines that enhance hepatocyte proliferation and play a pivotal role in liver regeneration (LR). Piezo1, a critical mechanosensory ionchannel, can detect and convert mechanical forces into chemical signals, importing externalstimuli into cells and triggering downstream biological effects. However, the precise role ofPiezo1 in VECs, especially in terms of mediating LR, remains unclear. Here, we report on a potential mechanism by which early changes in hepatic portal hemodynamics activate Piezo1 inVECs to promote hepatocyte proliferation during the process of LR induced by portal vein ligation in rats. In this LR model, hepatocyte proliferation is mainly distributed in zone 1 andzone 2 of liver lobules at 24e48 h after surgery, while only a small number of Ki67-positive hepatocytes were observed in zone 3. Activation of Piezo1 promotes increased secretion of epiregulin and amphiregulin from VECs via the PKC/ERK1/2 axis, further activating epidermalgrowth factor receptor (EGFR) and ERK1/2 signals in hepatocytes and promoting proliferation.In the liver lobules, the expression of EGFR in hepatocytes of zone 1 and zone 2 is significantlyhigher than that in zone 3. The EGFR inhibitor gefitinib inhibits LR by suppressing the proliferation of hepatocytes in the middle zone. These data provide a theoretical basis for the regulation of LR through chemical signals mediated by mechanical stimulation.
基金supported in part by the National Key Research and Development Program of China(2022YFA1103400 and 2022YFC2406704)the National Natural Science Foundation of China(32371477,82090051,and 92168207).
文摘The liver serves as a central organ regulating numerous complex metabolic processes[1,2].Hepatic lobule metabolic zonation supports distinct hepatocyte functions through spatially dependent gene expression that is governed by intricate signaling networks and interactions with diverse non-parenchymal cells[3–5].Notably,liver sinusoidal endothelial cells(LSECs)provide critical regulatory functions during hepatic regeneration and pathological adaptation[6].However,current hepatic pathology research is limited by inadequate models that poorly replicate human disease phenotypes and pharmacological responses.
基金supported in part by grants from the following sources:the National Natural Science Foundation of China(No.82090051,32371477,92168207)the National Key Research and Development Program of China(No.2022YFA1103400,2022YFC2406704)+1 种基金the Chief Scientist Research Project of Hubei Shizhen Laboratory(HSL2024SX0001)the Beijing Tsinghua Changgung Hospital Foundation(No.12025C01011).
文摘Hepatocellular carcinoma(HCC)is a leading cause of cancer-related mortality,and resistance to systemic therapies remains a significant clinical challenge.This study investigated the mechanisms by which metabolic reprogramming contributes to systemic treatment resistance in HCC.We established HCC cell lines with multidrug resistance characteristics and observed enhanced metabolic activity in these cells.Integrated multiomics analyses revealed hyperactive glucose‒lipid and glutathione metabolic pathways that play critical roles in supporting tumor cell proliferation and survival.We constructed a metabolic reprogramming atlas for HCC-resistant cells and identified aldo-keto reductase(Aldo-keto reductase family 1 Member B1,AKR1B1)as a key regulator of this reprogramming,which sustains drug resistance by regulating energy metabolism and enhancing stress tolerance.Importantly,AKR1B1 expression levels are closely associated with drug resistance and poor prognosis in HCC patients.The secretory nature of AKR1B1 not only underscores its predictive value but also facilitates the intercellular transmission of drug resistance.In terms of overcoming resistance,the AKR1B1 inhibitor epalrestat significantly mitigated drug resistance when it was used in combination with standard therapies.These findings underscore the importance of metabolic reprogramming in the development of HCC resistance.AKR1B1,a key enzyme that regulates metabolic reprogramming,has been identified as a potential biomarker and therapeutic target,providing new insights into overcoming resistance in HCC treatment.
基金Financial support Studies were funded in part by grants to Yunfang Wang,including National Key Research and Development Program of China(No.2022YFA1103400)National Natural Science Foundation of China(No.92168207)+1 种基金in part to Lola Reid at UNC.Those to Lola Reid included funds from Vesta Therapeutics(Bethesda,MD)that has merged now with PhoenixSongs Biologicals to form Vesta Biotherapeutics(Branford,CT).Praveen Sethupathy,PhD,was funded by an NIDDK/NIH grant(R00DK091318-02)supported in part by Dr.Sethupathy’s R00 grant and as well by a F31 fellowship.
文摘The creation of ex vivo human liver models has long been a critical objective in academic,clinical,and phar-maceutical research,particularly for drug development,where accurate evaluation of hepatic metabolic dy-namics is crucial.We have developed a bioengineered,perfused,organ-level human liver model that accurately replicates key liver functions,including metabolic activities,and protein synthesis,thus addressing some of the limitations associated with traditional liver monolayers,organoids,and matrix-embedded liver cells.Our approach utilizes liver-specific biomatrix scaffolds,prepared using an innovative protocol and fortified with matrix components that facilitate cellular interactions.These scaffolds,when seeded with human fetal liver cells or co-seeded with liver parenchymal and endothelial cell lines,enable the formation of three-dimensional(3D)human livers with enhanced cellular organization.The“recellularized tissue-engineered livers”(RCLs)have undergone various analyses,demonstrating the capability for establishing liver microenvironments ex vivo.Within 7-14 days,the RCLs exhibit evidence of liver differentiation and metabolic capabilities,underscoring the potential for use in drug metabolism and toxicity studies.Although our study represents a significant step for-ward,we acknowledge the need for direct comparisons with existing models and further research to fully elucidate the spectrum of regenerative responses.The high drug-metabolizing enzyme activity of RCLs,as demonstrated in our study,provides a promising avenue for investigating drug-induced liver injury mechanisms,contributing to a more detailed understanding of early drug discovery processes.
基金The work of A.Jacobsen,C.Evelo,M.Thompson,R.Cornet,R.Kaliyaperuma and M.Roos is supported by funding from the European Union’s Horizon 2020 research and innovation program under the EJP RD COFUND-EJP N°825575.The work of A.Jacobsen,C.Evelo,C.Goble,M.Thompson,N.Juty,R.Hooft,M.Roos,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista is supported by funding from ELIXIR EXCELERATE,H2020 grant agreement number 676559.R.Hooft was further funded by NL NWO NRGWI.obrug.2018.009.N.Juty and C.Goble were funded by CORBEL(H2020 grant agreement 654248)N.Juty,C.Goble,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista were funded by FAIRplus(IMI grant agreement 802750)+13 种基金N.Juty,C.Goble,M.Thompson,M.Roos,S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista were funded by EOSClife H2020-EU(grant agreement number 824087)C.Goble was funded by DMMCore(BBSRC BB/M013189/)M.Thompson,M.Roos received funding from NWO(VWData 400.17.605)S-A.Sansone,P.McQuilton,P.Rocca-Serra and D.Batista have been funded by grants awarded to S-A.Sansone from the UK BBSRC and Research Councils(BB/L024101/1,BB/L005069/1)EU(H2020-EU 634107H2020-EU 654241,IMI(IMPRiND 116060)NIH Data Common Fund,and from the Wellcome Trust(ISA-InterMine 212930/Z/18/ZFAIRsharing 208381/A/17/Z)The work of A.Waagmeester has been funded by grant award number GM089820 from the National Institutes of Health.M.Kersloot was funded by the European Regional Development Fund(KVW-00163).The work of N.Meyers was funded by the National Science Foundation(OAC 1839030)The work of M.D.Wilkinson is funded by Isaac Peral/Marie Curie cofund with the Universidad Politecnica de Madrid and the Ministerio de Economia y Competitividad grant number TIN2014-55993-RMThe work of B.Magagna,E.Schultes,L.da Silva Santos and K.Jeffery is funded by the H2020-EU 824068The work of B.Magagna,E.Schultes and L.da Silva Santos is funded by the GO FAIR ISCO grant of the Dutch Ministry of Science and CultureThe work of G.Guizzardi is supported by the OCEAN Project(FUB).M.Courtot received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No.802750.R.Cornet was further funded by FAIR4Health(H2020-EU grant agreement number 824666)K.Jeffery received funding from EPOS-IP H2020-EU agreement 676564 and ENVRIplus H2020-EU agreement 654182.
文摘The FAIR principles have been widely cited,endorsed and adopted by a broad range of stakeholders since their publication in 2016.By intention,the 15 FAIR guiding principles do not dictate specific technological implementations,but provide guidance for improving Findability,Accessibility,Interoperability and Reusability of digital resources.This has likely contributed to the broad adoption of the FAIR principles,because individual stakeholder communities can implement their own FAIR solutions.However,it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations.Thus,while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways,for true interoperability we need to support convergence in implementation choices that are widely accessible and(re)-usable.We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible,robust,widespread and consistent FAIR implementations.Any self-identified stakeholder community may either choose to reuse solutions from existing implementations,or when they spot a gap,accept the challenge to create the needed solution,which,ideally,can be used again by other communities in the future.Here,we provide interpretations and implementation considerations(choices and challenges)for each FAIR principle.
