In addition, adsorption kinetics were also investigated and parameters were calculated. The functionalized porous carbon monolith showed a relatively higher adsorption capacity than that of pristine porous carbon monolith and the bulk PB to most radioactive ions such as 133Cs, 85Rb, 138Ba, 88Sr, 140Ce, and 205Tl. This material can be used for decontamination in expanded application fields.As the control over radioactive species becomes critical for the contemporary human life, the development of functional materials for decontamination of radioactive substances has also become important. In this work, a three-dimensional (3D) porous carbon monolith functionalized with Prussian blue particles was prepared through removal of colloidal silica particles from exfoliated graphene/silica composite precursors. The colloidal silica particles with a narrow size distribution were used to act a role of hard template and provide a sufficient surface area that could accommodate potentially hazardous radioactive substances by adsorption. The unique surface and pore structure of the functionalized porous carbon monolith was examined using electron microscopy and energy-dispersive X-ray analysis (EDS). The effective incorporation of PB nanoparticles was confirmed using diverse instrumentations such as X-ray diffraction (XRD), Fourier-transform infrared (FT-IR), and X-ray photoelectron spectroscopy (XPS). A nitrogen adsorption/desorption study showed that surface area and pore volume increased significantly compared with the starting precursor. Adsorption tests were performed with  Recently, the need for intensive energy sources has increased dramatically, because human life and activities are becoming complex and energy-consuming. At the same time, a significant interest has been drawn to nuclear energy and technology dealing with dangerous radioactive substances to increase energy production capacity/efficiency, leading to a rapid increase in nuclear waste production. Therefore, it becomes even more important for us to control the potentially hazardous nuclear wastes effectively. Even if several methods have been developed to remove the nuclear wastes, it is still a challenging task to remove the radioactive substances or produce functional media materials for contamination control ,3,4,5,6.Since the Fukushima accidents, a desire for the development of environmentally benign and functional materials for decontamination of radioactive substances is ever increasing. Among various strategies to remove the radioactive species, adsorption with porous materials can be promising, because of easy preparation and simple use ,10,11,12In this study, a functional porous carbon monolith (PCM) decorated with the Prussian blue (PB) nanoparticles (PB@PCM) was produced for removal of the radioactive substances by selective removal of colloidal silica microparticles working as the hard template and porogen from exfoliated graphene/silica composite precursors, which was easily obtained by direct mixing of graphene and colloidal silica particles. This approach was simple because the preparation and removal of the hard template with a complicated and tailored structure could be avoided. In addition, it was expected that an unprecedented pore structure could be generated because graphene/silica composite precursors possessing an irregular pore structure were introduced. An interconnected 3D pore structure with an increased surface area was generated after removal of the colloidal silica particles, as a controlled pore structure with a similar pore size was not mandatory for this study. However, it was important to analyze the pore structure and surface properties to see if the obtained material could be used for the decontamination of radioactive species. As the removal of radioactive materials was strongly dependent on the adsorption mechanism, a high surface area of the PCM was one of the most critical prerequisites. Moreover, the surface properties and pore structure were analyzed extensively using various instrumentations.+) ions. , and PCM. Typically, PCM was soaked in 10 M FeCl3 solution for 15 min and the solution in sample was completely eliminated with a filter paper. Then, the PCM decorated with Fe3+ ions was dried in a convection oven at 80°C for at least 3 h. Then, the preprocessed PCM was immersed in a K3[Fe(CN)6]  solution and stirred at 55 °C for 12 h. The final PB@PCM product was obtained and washed with distilled water 3 times and dried under vacuum at 80°C overnight to complete evaporation of the solvent. The mass of the finally obtained PB@PCM sample was 2.4 g, which can be scaled up by increasing the amount of the EG/silica composite precursor. The bulk PB was fabricated by direct mixing of equimolar FeCl3 and K4[Fe(CN)6] solutions at room temperature for 6 h. The final products were washed with ethanol several times to remove residual reagent. Subsequently, the resulting bulk PB was dried under a vacuum oven and pressed into pellets.The PB@PCM was manufactured by a redox reaction in an aqueous mixture solution of FeCl133Cs ion was monitored as follows: the cesium standard solutions with varying concentration from 0.01 to 100 mg/L (ppm) were produced in 100 mL of distilled water. To control the pH, ammonia or hydrochloric acid solution was injected into the aqueous solutions. Then, 0.1 g of adsorbents (PB@PCM) was introduced into the solution and stirred at 300 rpm, which would be suitable for 133Cs ion adsorption. Adsorption experiments were carried out at 20 °C and pH 7.0, and the adsorption capacity for 133Cs ion was monitored from 0 min to 24 h. After adsorption, 3 mL of the solution was filtered through a syringe filter , and then an ICP-MS test was performed to determine the 133Cs ion concentration as a function of adsorption time. To obtain accurate results, the 133Cs ion concentration was measured three times and the average values were collected. The adsorption capacity to the other ions—rubidium, barium, strontium, cerium, and titanium—was also measured identically.The adsorption behavior of the PB@PCM for The morphology was confirmed using a field emission scanning electron microscopy at 10 kV  and transmission electron microscopy . A particle size analyzer  was used to determine the silica particle size and zeta potential. The FT-IR spectra were recorded on Alpha-P . The XRD patterns were collected using an Ultima IV with Cu Kα radiation . The BET analyses were performed with an ASAP 2020  using the N2 adsorption–desorption isotherms. The pore size and distribution in the porous carbon was analyzed with an AutoPore IV 9500 mercury porosimeter at room temperature . The XPS data were obtained using an Axis Nova  with monochromatic Al-Kα X-ray source under 10-8 Torr vacuum analysis chamber. The ICP-MS was used to analyze and confirm the cesium concentration in solution .133Cs adsorption behavior could be described by both Langmuir and Freundlich isotherms, and fitting to the Langmuir isotherm provided a closer correlation with the experimental data. The porous carbon showed a better adsorption capacity than the precursor and an intermediate capacity for radioactive ion species such as 133Cs, 87Rb, 88Sr, 137Ba, 140Ce, and 205Tl. The maximum and minimum adsorption capacity values were obtained for 133Cs and 205Tl, respectively. As a porous carbon material was obtained by a relatively simple, cost-effective, and environmentally benign method, an interest in analogous functional porous materials for nuclear waste control is expected to increase significantly. Therefore, this research can offer important information for future relevant research and, moreover, development of advanced materials and devices.In this study, convenient manufacture of monolithic porous carbon material embedded with Prussian blue particles was demonstrated and its radioactive substance removal performance was also examined using various radioactive ion species. The functional porous carbon was prepared by etching of silica template and subsequent Prussian blue nanoparticle decoration. The obtained porous carbon possessed an increased surface area compared with the precursor and the intermediate. In addition, its pore structure was open and interconnected with small window pores, which was advantageous for ion transport and movement. The radioactive substance removal was achieved by the incorporation of Prussian blue nanoparticles, which can adsorb radioactive ion species effectively. The


Glioblastoma is a prevalent malignant brain tumor and despite clinical intervention, tumor recurrence is frequent and usually fatal. Genomic investigations have provided a greater understanding of molecular heterogeneity in glioblastoma, yet there are still no curative treatments, and the prognosis has remained unchanged. The aggressive nature of glioblastoma is attributed to the heterogeneity in tumor cell subpopulations and aberrant microvascular proliferation. Ganglioside-directed immunotherapy and membrane lipid therapy have shown efficacy in the treatment of glioblastoma. To truly harness these novel therapeutics and develop a regimen that improves clinical outcome, a greater understanding of the altered lipidomic profiles within the glioblastoma tumor microenvironment is urgently needed. In this work, high resolution mass spectrometry imaging was utilized to investigate lipid heterogeneity in human glioblastoma samples. Data presented offers the first insight into the histology-specific accumulation of lipids involved in cell metabolism and signaling. Cardiolipins, phosphatidylinositol, ceramide-1-phosphate, and gangliosides, including the glioblastoma stem cell marker, GD3, were shown to differentially accumulate in tumor and endothelial cell subpopulations. Conversely, a reduction in sphingomyelins and sulfatides were detected in tumor cell regions. Cellular accumulation for each lipid class was dependent upon their fatty acid residue composition, highlighting the importance of understanding lipid structure–function relationships. Discriminating ions were identified and correlated to histopathology and Ki67 proliferation index. These results identified multiple lipids within the glioblastoma microenvironment that warrant further investigation for the development of predictive biomarkers and lipid-based therapeutics. Despite surgical and therapeutic intervention, the prognosis for glioblastoma is bleak, with a median overall survival of 12–15 months after diagnosis2. The failure of therapeutic intervention is attributed to the intratumor heterogeneity in glioblastoma. Glioblastomas are difficult to fully resect and develop resistance to current therapeutic regimens, leading to high rates of recurrence, with limited treatment options3. Elucidating glioblastoma cellular heterogeneity within the tumor microenvironment (TME) is essential to identifying pathways that drive tumor progression for the development of curative therapeutics.Glioblastoma is the most common type of primary malignant brain tumor in adults and is classified by the World Health Organization as a Grade 4 neoplasm5. These studies identified the cellular composition of glioblastoma as either proneural, neural, classical, or mesenchymal. These subtypes were initially believed to contribute to glioblastoma heterogeneity between patients, but single cell RNA-seq demonstrated that all four were found within a single glioblastoma tumor6. The same study also identified a plasticity in cancer stem cell markers and reported a stemness gradient. These findings have been investigated in more detail recently, solidifying the notion that both tumor cells and glioblastoma stem cells (GSC) are not static and intratumoral plasticity results in diverse spatial and temporal heterogeneity that is shaped by the TME8. Despite these advancements in genomics and a greater understanding of the molecular heterogeneity within the glioblastoma TME, there are still no curative treatment options, and the prognosis is unchanged3.The Cancer Genome Atlas and two seminal publications using transcriptional studies laid the foundation for glioblastoma subtypes based on molecular profiles10. Studies have demonstrated that the perivascular niche maintains the GSC phenotype and contributes strongly to therapeutic resistance11. Despite the known roles of the PVN in the invasive and aggressive nature of glioblastoma, their phenotypes in relation to function remain ill-defined. The PVN has been categorized into subtypes based on their microvascular formations and include microvascular sprouting, vascular cluster, vascular garland and glomeruloid vascular proliferation12. These different vascular subtypes have been shown to correlate with prognosis13. Given the known involvement of the PVN and the failure of anti-angiogenic therapies in clinic; a greater understanding of the phenotype of the endothelial cells that comprise the TME is needed14.Non-tumor cells within the microenvironment also contribute to glioblastoma progression. The perivascular niche (PVN) and the aberrant microvascular proliferation (MVP) that is a characteristic feature of glioblastoma helps drive the invasive nature of this tumor15, differentiation16 and apoptosis17. It is thus unsurprising that altered lipid metabolism and cellular composition have been linked to cancer cell growth18, aggression19, metastasis20 and resistance to therapy21. Previous research has shown there are increased levels of free and lipid-incorporated long chain polyunsaturated fatty acids (PUFA) in GSCs that support oncogenic EGFR signaling22. The sphingolipid rheostat, a determinant of cell fate, is also dysregulated in glioblastoma, leading to a reduction in growth arrest pathways and an increase in proliferation pathways23. Many of these dysregulated lipid pathways are considered therapeutic targets21.Lipids are key regulatory molecules that have been intricately linked to cell fate through direct and indirect signaling mechanisms with roles in proliferation26. These studies have focused on the classification of glioblastoma from lower grade gliomas based on lipid profiles24 and changes between different morphological tissue regions such as tumor vs. stroma27. In the current study, high resolution MALDI Fourier transform ion cyclotron resonance MSI was used to determine the first intratumoral lipid heterogeneity within cancer cell subpopulations and the different subtypes of microvascular formations in human glioblastoma samples. Ceramide-1-phosphates, gangliosides, cardiolipins and phosphatidylinositiols were able to differentiate histologically similar regions of high tumor cell density, regions of pseudopalisading tumor cells and the different formations of MVPs. A loss in sphingomyelin, a lipid that is abundant in normal brain, was observed in all low–high tumor cell regions. Lastly, sulfatides were able to differentiate low-moderate tumor cell regions from high tumor cell regions and regions of pseudopalisading tumor cells.Mass spectrometry imaging (MSI) has been used previously to analyze the spatial distribution of lipids in preclinical and clinical glioblastoma samplesHistological analysis, mass spectrometry imaging and Ki67 immunostaining were carried out on five human glioblastoma samples. The deadly nature of glioblastoma and the timing of resection and banking of these samples meant that each patient underwent different treatment regimens. These included radiation alone or in combination with temozolomide, + /− bevacizumab or pembrolizumab, and the anti-seizure medications Kepra/Vimpat. Due to the diversity of the treatment regimens for each patient and the possible impact these could have on lipid profiles, initial investigations focused on intratumor heterogeneity within each sample. Slightly deeper sections were then taken for repeat MSI analysis and Ki67 staining to correlate lipid profiles with proliferation index. Discriminant analysis of these samples enabled the identification of several lipids that accumulated within high tumor cell regions with high Ki67 labeling across all samples analyzed, regardless of pathology or treatment. These results are discussed in detail in the following sections.Histological interpretation of each patient glioblastoma samples used in this study was carried out by a board-certified neuropathologist. Glioblastomas present with diverse histological features that include hypercellularity; atypia; pleomorphic nuclei; pseudopalisades surrounding necrosis and different formations of MVP. These histological features are shown in the patient samples presented in Fig. 28. This unsupervised multivariate classification method automatically extracts the underlying trends in the data based on the ions detected. The score images presented in Supplementary Fig. Due to the complexity and high‐dimensional nature of MSI data and to remove any potential bias in data processing, the datasets were initially processed using probabilistic latent semantic analysis29. Representative MS images of CL distribution are presented in Fig. 30, and the MVP formations characterized as microvascular sprouting and vascular clusters. The accumulation of several CLs in samples N167 and N118 demonstrated histological structure-based heterogeneity that was dependent upon the carbon number and levels of unsaturation in their fatty acid residues. This can be observed by comparing the distribution of CL(70:4) through to CL(74:10). A decrease in the detection of CLs was observed in the regions containing pseudopalisading tumor cells in sample N167 as the carbon number and levels of unsaturation increased. Conversely, the signal intensity of longer chain CLs increased in the microvascular formations surrounding necrosis in N167, and in distinct regions of tumor cells and vascular clusters in sample N118. A gradient of no signal to high signal was observed for all CLs in sample N158; correlating with low-to-high tumor burden in this sample. Similarly, all CLs were detected at or near noise level in sample N141, which contained few tumor cells and more closely resembled normal brain parenchyma. In sample N35, CLs were detected with highest intensity in regions surrounding the acellular fluid filled areas. The histology-based distribution and corresponding signal intensity for all CLs detected are presented in Supplementary Table Cardiolipins (CLs) are a mitochondrial specific phospholipid that are predominantly located in the inner mitochondrial membrane (IMM); the composition of their fatty acid residues play important roles in mitochondrial structure and function32. This destabilized CL interaction with cytochrome c leading to its release and the induction of the apoptosis cascade in these cells. While there is limited information on CLs in glioblastoma, several recent studies have demonstrated CL alterations and/or overexpression of the CL acetyltransferase, tafazzin, in prostate cancer33, thyroid cancer34, glioma35, pancreatic cancer stem cells36 and cervical cancer37. Upregulation of the CL modifying enzyme, lysocardiolipin acyltransferase (LYCAT) was also recently detected in non-small cell lung cancer and knockdown of LYCAT reduced cell proliferation, migration, invasion, and thus tumor size and burden in vitro and in vivo38. Understanding the functional relevance of CL composition in relation to their accumulation in the different tumor cell and endothelial cell populations in this study warrants further investigation as they offer novel therapeutic targets for the treatment of glioblastoma.Prior to this study, much of the information on CL dysregulation in glioblastoma has been derived from in vitro investigations and thus a single cell phenotype. Treatment of the glioblastoma cell line GL15 with palmitate or bromopyruvate resulted in a loss or degradation of CL species, respectively39. A total of 16 PIs were detected and descriptions of the pathological regions in which PIs were localized are available in Supplementary Table Phosphatidylinositols (PIs) are important cell signaling lipids and precursors for the PI3K pathway, which is dysregulated in many cancers40. The enzymes involved in the regulation of PIPs and thus PIP signaling are some of the most well-known and studied in cancer41. Phosphoinositide-3-kinase (PI3K), produces PIP3, which activates the AKT and the mammalian target of rapamycin (mTOR) signaling pathways42. The PI3K/AKT/mTOR pathway is upregulated in most human cancers and drives cell survival, proliferation and invasion42. Conversely, phosphatase and tensin homolog (PTEN), the enzyme responsible for dephosphorylation of PIP3 and known as a tumor suppressor, is silenced in many human cancers41. The impact of PI fatty acid composition in regulation of these pathways during glioblastoma development and progression is unknown. Recent studies, however, have shown that alterations to PI fatty acyl chain composition altered AKT localization and downstream signaling in a prostate cancer model43. Fatty acyl chain remodeling of PIs was also shown during the analysis of primary breast cancer tissue44. This study identified PI(38:3) as a hallmark of invasive cancer cells that was associated with higher incidence of lymph node metastasis44. In the current study, this lipid was also highly localized to regions containing actively migrating cell populations, histologically characterized as pseudopalisading tumor cells30. Understanding the functional relevance of PI(38:3) in these migrating glioblastoma cell populations is an important next step of research. Additionally, the PTEN/PI3K/AKT/mTOR pathway has been extensively studied in glioblastoma and a number of pathway inhibitors are in preclinical and clinical trials45. Targeting the downstream PIs that feed into this pathway may offer a novel therapeutic approach.PIs play central roles in cell signaling and regulation that is dictated by both the composition of their fatty acid residues and phosphorylation at the 3’, 4’ and 5’ position of their inositol head group, which gives rise to the second messengers, phosphatidylinositol phosphates (PIPs)Sphingolipids are a diverse family of lipids involved in numerous cell signaling processes that regulate cell division, differentiation, migration and apoptosis. Over 40 different sphingolipids were detected, encompassing the subclasses of ceramide-1-phosphates (C1P), sphingomyelin (SM), sulfatides (ST) and gangliosides. A full list of the sphingolipids detected along with their structure-based histology-specific accumulation within each sample are presented in Supplementary Tables 46. C1P has also been shown to be a potent chemoattractant involved in the trafficking of immune and stem cell populations through mechanisms that are not fully understood47. While much research has focused on the roles of ceramide and S1P in cancer progression, less is known about C1P in cancer and there are no studies on its role in glioblastoma17. C1P and ceramide kinase (CerK), the only enzyme identified to date that phosphorylates Cer to form C1P, have been implicated in breast51, lung53 and pancreatic cancer55 cell growth, survival and dissemination. In breast and lung cancer, upregulation of CerK was shown to promote tumor cell survival and migration/invasion of cancer cells through activation of the PI3K/AKT, ERK1/2 and the Rho kinase signaling pathways52. CerK expression has also been associated with breast cancer aggression and recurrence, and thus patient prognosis51. Inhibition of CerK with NVP-231, reduced C1P levels and resulted in M phase growth arrest in breast and lung cancer cell lines and decreased migration of metastatic breast cancer cells50. In pancreatic cancer cells, C1P stimulated cell migration and invasion was shown to be dependent upon the PI3K, AKT1, mTOR1, MAPK, ERK1-2 and RhoA/ROCK signaling pathways55. C1P signaling in pancreatic cancer cells has been shown through both intracellular and extracellular signaling mechanisms. A recent study demonstrated pancreatic ductal adenocarcinoma secreted C1P-containing extracellular vesicles, which promoted motility and recruitment of pancreatic cancer stem cells, suggesting C1P-related signaling mechanisms facilitate pancreatic tumor progression54. The pro-survival mechanisms of S1P and C1P may explain why many S1P inhibitors have failed in clinical trials, as C1P may be an alternative and compensatory pro-survival signaling molecule driving tumor progression. Similar to the distribution of CLs and PIs, a number of C1Ps were detected and differentially distributed within different cellular regions and pathological presentations of MVPs. Very little is known about the cellular phenotypes that constitute these pathologies in glioblastoma. Several studies, however, have demonstrated CerK activity and C1P formation was essential for both microvascular proliferation and the recruitment of endothelial progenitor cells and thus is pro-angiogenic56. Inhibition of C1P may offer a potential therapy targeting both select tumor cell populations and the aberrant microvascular proliferation observed in glioblastoma.C1Ps are part of the sphingolipid rheostat that determines cell fate, in which ceramide promotes cell growth arrest and death through multiple signaling pathways, whereas metabolism of Cer to sphingosine-1-phosphate (S1P) or phosphorylation to C1P promotes cell growth and proliferation58. GD2 expression in pediatric and adult brain tumors has been extensively studied and the anti-GD2 monoclonal antibodies, dinutuximab and naxitamab, are FDA approved for the treatment of neuroblastoma60. Anti-GD2 CAR T cells have also recently demonstrated efficacy in the treatment of several brain tumors and are under investigation in clinical trials . Of particular interest in the current study is the detection and distribution of GD3(36:1) within sub-populations of glioblastoma tumor cells along with its absence in sample N141. Mass spectrometry analysis of bulk homogenized brain tissue demonstrated GD3(36:1) was the predominant ganglioside in glioblastoma patient samples62. GD3 and GD3 synthase have also been identified as a biomarker for glioblastoma stem cells and treatment with a GD3 antibody suppressed tumor growth in vitro and in vivo64. GD3 involvement in pre/pro-tumorigenic events in the microenvironment away from the tumor margin was suggested following an in vivo study that detected GD3, NG2 and loss of PTEN in cells that were yet to undergo histologically identifiable neoplastic transformation64.Gangliosides are a class of glycosphingolipids composed of a ceramide moiety linked to a glycan head group that contains varying numbers of sialic acid residues. The disialogangliosides with 2 and 3 glycosyl groups, GD2 and GD3, have been shown to be highly abundant in numerous brain tumors66. In the cellular regions of samples N167, N118 and N158, STs were predominately detected and localized in regions consisting of lower tumor cell density and a more normal neuropil composition. Minimal-to-no signal was detected for this lipid class in areas of moderate-to-high tumor cell density, as evidenced by the example data presented for this lipid class in Fig. 66. Over expression of the SM metabolizing enzyme, acid sphingomyelinase (ASM), was also shown to be associated with shorter survival in patients68. Therapeutics targeting sphingolipid metabolism have shown efficacy in the treatment of glioblastoma during preclinical studies. Treatment of glioblastoma cells in vitro and in vivo with the non-toxic membrane lipid therapy drug, 2-hydroxyoleic acid (2OHOA), recovered SM cell composition69 and downregulated the MAPK/PI3K/AKT pathways, leading to cell death and reduced tumor burden69. The safety of 2OHOA is currently being tested when used alongside conventional glioblastoma therapies (NCT03867123 and NCT04250922). A recent study has also provided evidence linking SM metabolism with EGFR oncogenic receptor signaling on the plasma membrane of glioblastoma cells. By inhibiting ASM activity with the antidepressant drug, fluoxetine, the authors demonstrated the accumulation of SMs resulted in a loss of EGFR receptors from membrane lipid raft domains and the killing of glioblastoma cells via activation of lysosomal stress. These studies highlight the importance of the evolving field of membrane lipid therapy and the significance of this study in spatially identifying lipidomic alterations for the identification of lipid pathway therapeutic targets.Sulfatide and sphingomyelin are highly distributed to normal brain parenchyma where they are major components of the myelin sheathTo further highlight the histology-based lipid complexity in the glioblastoma TME in patient samples, several merged ion images were generated, displaying the spatial distribution of multiple lipids in each section Fig. . In all m/z, mass deviation, ion formation and chemical formula, are presented in Supplementary Tables A full list of species detected for the lipid classes discussed, along with their + cells were detected in the top biopsy only and for these reasons, this sample was also excluded from further analysis. The stained H&E section and the adjacent Ki67 section for this sample is shown in Supplementary Fig. 70.Lipid ions that have the ability to discriminate between different tumor and endothelial cell regions in the glioblastoma TME have the potential to be biomarkers and as discussed in the previous sections, their pathways hold the potential to be targeted with therapeutics. To identify ions capable of discriminating between different tumor and endothelial cell subpopulations, additional studies were carried out to correlate histopathology and lipid distribution/accumulation to tumor cell proliferation, based on Ki67 labeling index (LI). As sample N141 contained mostly normal brain parenchyma and few tumor cell nuclei, this sample was excluded from further investigation. Serial sections were taken ~ 2–300 µm deeper from those discussed in the previous sections. MSI and Ki67 staining were carried out on adjacent sections. The deeper sections taken from patient sample N35 contained few tumor nuclei, more normal parenchyma, and both hemorrhage and necrosis due to disease and/or treatment. A few Ki67High and GD3Low areas. Ion that were able to discriminate high tumor cell density and palisading tumor cells from moderate-to-low tumor cell regions were calculated using area under the ROC curve, with a stringent cut off of 0.9. Only ions that met these criteria in all paired samples were accepted and their statistical significance was then calculated by t test. All discriminative ions had calculated p-values of < 0.001. The AUC values for each discriminative ion along with their calculated p-values are presented in Supplementary Table 71. Furthermore, mitochondrial numbers within cancer cells was recently shown to have a direct impact on drug response, in which increased numbers conferred cells more resistant to therapy. Understanding the differences in CL detection in relation to mitochondrial numbers and function, in the different glioblastoma cell populations, is thus an important next step of research as these cells may respond differently to therapy72.Regions of interest (ROIs) were identified in each paired patient sample based on PLSA data, histological profiles and in the latter sections, Ki67 LI. These encompassed areas with low-moderate tumor cell density and low cellular proliferation, high tumor cell density and proliferation, and the migratory pseudopalisading tumor cells. As the sample taken from N167 had large regions of high tumor cell density that were separated by the accumulation of the reported GSC marker, GD3, two high tumor cell regions were selected from this sample, covering GD3A limitation of the current study was low sample number. Nevertheless, this is still an important pilot study as it is the first to map lipid profiles to regions of tumor cell subpopulations, including the migratory pseudopalisading tumor cells, in patient glioblastoma samples. It is also the first study to identify lipidomic differences within different formations of microvascular proliferations, which are known to aid in the aggressive nature of glioblastoma, and are being targeted with developmental chemotherapeutics.In conclusion, high resolution MALDI MSI identified a number of lipids that differentiate tumor and endothelial cell subpopulations within human glioblastoma samples. The heterogeneous distribution of C1Ps, gangliosides, CLs and PIs within these cell populations further highlight the complexity of the glioblastoma TME. Lipid ions presented here lay the foundation for future studies that are required to understand their interconnecting signaling pathways in relation to cell function, tumor progression, and resistance to therapy. Understanding their functional relevance is essential for the identification of new therapeutics based on lipid pathway targets. In agreement with the known heterogeneity and clinical outcome of glioblastoma, data herein further suggests that targeting a single cell population with one treatment will not be efficacious in the battle to cure glioblastoma. The distribution of the pleotropic signaling lipid, C1P, within both tumor cell and MVP formations, along with their known roles in cell proliferation and recruitment, indicate that this lipid class may offer a novel duel therapeutic target for both tumor and endothelial cell populations. Whereas targeting GD3 with immunotherapeutics, or the mitochondrial-specific lipid, CLs, may only be efficacious in the treatment of glioblastoma tumor cell subclones. Targeting several of these lipids and their signaling pathways simultaneously, however, may improve clinical outcome. As targeting C1P, CL and gangliosides have shown efficacy in the treatment of many other cancers, their roles in glioblastoma progression is an important next step of research. Future work will investigate a larger cohort covering primary and recurrent tumors along with functional studies to understand the relevance of these findings.Methanol, 9-aminoacridine (9AA), D.P.X, sodium chloride, donkey serum, gelatin from cold water fish skin, Trimza base for molecular biology, Tween 20 viscous liquid, Triton X-100 and bovine serum albumin were purchased from Sigma Aldrich . Hematoxylin, eosin, xylene, ethanol, methanol-free formaldehyde, Alexa Fluor Plus 488 antibody and ultrapure glycerin were purchased from Thermo Fisher Scientific . Ki67 antibodies (ab15580) were purchased from Abcam . TrueBlack autofluorescence quencher and Hoechst 33,342 dye were purchased from Biotium .Human glioblastoma samples were surgically resected at the Department of Neurosurgery, Hackensack Meridian Health (HMH), Hackensack, NJ, USA. Informed consent for the use of samples for scientific research was obtained from all patients according to the study protocol approved by the Institutional Review Board at Hackensack Meridian Health (Pro2018-1022). All procedures were performed in accordance with the Helsinki Declaration. Samples were de-identified and stored in HMH’s biorepository. All studies were conducted in accordance with the relevant guidelines and regulations, approved by the Ethics Review Committee of Hackensack Meridian Health.45, resulting in an estimated pixel size of ~ 30 µm. Following data acquisition, the slides were washed and stained with H&E according to the manufacturer protocol (Thermo Fisher Scientific). Stained samples were annotated by a board-certified pathologist using CaseViewer software .Glioblastoma samples were sectioned to 5 or 10 µm thickness using a CM 1860 cryostat , thaw mounted onto positively charged glass slides, and stored at – 80 °C until analysis. A 10 mg/mL solution of 9AA was sprayed onto the tissue samples using a TM Sprayer . The spraying method was 160 µL/min at 80 °C for four passes using the crisscross setting, track spacing of 3 mm, nozzle height of 4 cm, and a velocity 1200 mm/min. Mass spectrometry imaging data were acquired using a 7 T SolariX 2xR FT-ICR mass spectrometer  operated in negative ion mode. Data were acquired with the small laser setting, accumulating 250 shots per pixel using the oversampling methodA 1 L solution of TBST was prepared by dissolving 24 g of Tris base and 88 g of sodium chloride in 1 L of water, adjusted to a pH of 7.6, and sterilized by autoclaving. Tissues were fixed with 4% formaldehyde and washed with TBST prior to staining. Sections were incubated for 1 h at room temperature in a blocking and permeabilization solution made up of 0.1% w/v gelatin, 2.25% w/v glycine and 1% w/v bovine serum albumin in 9:1 TBST:donkey serum. After 1 h, the blocking and permeabilization solution was removed and samples were incubated with 100 µL of Ki67 antibodies diluted 1:250 in 5% Triton X-100 in TBST. Samples were washed with TBST after removal of the antibody solution, and incubated in the secondary antibody solution . Finally, samples were incubated with an autofluorescence quenching solution for 1 min and washed with TBST again. Slides were mounted and left to dry overnight in the dark. Immunofluorescent imaging was carried out on a Nikon Eclipse Ti2 microscope using a 10 × objective. Ki67 positive cells were counted using the “Analyze Particles” function in ImageJ (version 1.8.0_172).28. PLSA data process was carried out without normalization, using individual spectra and 5, 7, 10 and 14 components were evaluated to determine the optimal number. The ions in each spectral loading were uploaded to LipidMaps and HMDB for tentative assignment. Regions of interest were defined based on the resulting score images that correlated to areas of low-moderate tumor cell density, different subpopulations of high tumor cell density, pseudopalisading tumor cells, and different formations of MVPs. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to find ions that discriminated between these regions. A stringent AUC cut off value of > 0.9 was used. The significance for each ion between two ROIs were calculated using the t test.Data were analyzed using FlexImaging (version 5.0) and SCiLS Lab software . The H&E images and raw data for each patient sample were imported into the Scils lab software as individual files to investigate intratumor heterogeneity. Unsupervised multivariate analysis was carried out using probabilistic latent semantic analysis (PLSA) with deterministic initialization to identify regional trends in dataTumor samples were collected by Hackensack Meridian Health’s Tissue Biorepository under the IRB protocol Pro2018-1022. Each participant gave written informed consent for the use of their tissue for scientific research and all work was carried out in compliance with the Helsinki Declaration.Supplementary Information.


In the UK, different dietary systems are used to calculate protein or tyrosine/phenylalanine intake in the dietary management of hereditary tyrosinaemia, HTI, II and III (HT), with no systematic evidence comparing the merits and inadequacies of each. This study aimed to examine the current UK dietary practices in all HTs and, using Delphi methodology, to reach consensus agreement about the best dietary management system. Over 12 months, five meetings were held with UK paediatric and adult dietitians working in inherited metabolic disorders (IMDs) managing HTs. Eleven statements on the dietary system for calculating protein or tyrosine/phenylalanine intake were discussed. Dietitians from 12 of 14 IMD centres caring for HT patients participated, and 7/11 statements were agreed with one Delphi round. Nine centres (three abstentions) supported a 1 g protein exchange system for all foods except fruit and vegetables. The same definitions used in the UK for phenylketonuria (PKU) were adopted to define when to calculate foods as part of a protein exchange system or permit them without measurement. Fruit and vegetables contain a lower amount of tyrosine/phenylalanine per 1 g of protein than animal and cereal foods. The correlation of tyrosine vs. phenylalanine (mg/100 g) for vegetables and fruits was high (r = 0.9). In Delphi round 2, agreement was reached to use the tyrosine/phenylalanine analyses of fruits/vegetables, for their allocation within the HT diet. This allowed larger portion sizes of measured fruits and vegetables and increased the variety of fruit and vegetables that could be eaten without measurement. In HTs, a combined dietary management system will be used: 1 g protein exchanges for cereal and milk protein sources and tyrosine/phenylalanine exchanges for fruit and vegetables. Intensive, systematic communication with IMD dietitians and reappraisal of the evidence has redefined and harmonised HT dietary practice across the UK. Hereditary tyrosinaemia types I, II and III (HT) belong to a group of rare autosomal recessive, inherited metabolic disorders (IMDs). HTI, the most clinically challenging of these disorders, is caused by mutations in the gene fumarylacetoacetate hydrolase (FAH) leading to the accumulation of toxic metabolites causing apoptosis and liver and renal failure ,2. HTII,HTs are managed with a protein or tyrosine/phenylalanine-restricted diet. HTI is also managed with 2 (2-nitro-4-trifluoromethybenzoyl)-1, 3 cyclohexanedione) (NTBC), preventing the production of toxic metabolites by blocking the tyrosine pathway at step 3, so mimicking HTIII. For all HTs, the individual tolerance to protein or tyrosine/phenylalanine intake is assessed by the provision of natural protein-containing foods and regular monitoring of blood tyrosine and phenylalanine concentrations. In the UK, we aim to maintain a target tyrosine treatment reference range of 200–400 µmol/L and a phenylalanine concentration of ≥50 μmol/L . The dieSeveral collaborative European, Canadian and USA clinical guidelines are published ,12,13 byIn the UK, commonly a 1 g protein exchange system (1 g of protein = 1 exchange) is adopted for allocation of foods such as milk and cereals, but practices vary for fruit and vegetables, with some centres using 1 g protein exchanges  and someFollowing a successful collaborative project by the British Inherited Metabolic Disease Dietitians Group (BIMDG-DG) in which consensus for the dietary management of PKU was achieved ,16, the Over 12 months (January 2021 to December 2021), five virtual meetings, each lasting 60 to 90 min, were held with UK dietitians who were members of the BIMDG-DG. All worked with one or more types of HTs from both adult and paediatric IMD centres. Alkaptonuria was excluded as dietary care was directed from one UK National centre. To reach agreement about a national dietary system for HTs, the Delphi methodology was used . This syThe general dietary principles to be used for HTI, HTII and HTIII.The dietary exchange system to be adopted: either a 1 g protein exchange system or a combination of tyrosine/phenylalanine (mg/100 g protein). This distinguished between foods that contain 5% phenylalanine and 3–4% tyrosine for each gram of protein from milk and cereals and foods that contain 3–4% phenylalanine and 2–3% tyrosine for each gram of protein from fruit and vegetables .Clear definitions for measuring/calculating protein or phenylalanine/tyrosine from manufactured foods and when these can be given as part of the dietary exchange system or given without measurement.Statements were created on the following parameters:(1)‘McCance and Widdowson’s The Composition of Foods’ 1980, First supplementary amino acid mg/100 g foods ;(2)National society for phenylketonuria (NSPKU) database  and (per(3)Amino acid composition of food products used in the treatment of patients with disorders of amino acid and protein metabolism ;(4)www.usda.gov (accessed on 3 March 2021)) [United States of America Department of Agriculture www.Mevalia.com (accessed on 3 March 2020)) based on Frida.fooddata.dk version 4 National Food Institute, Technical University of Denmark [Mevalia website database .Ethical approval was not required as per UK Policy Framework for Health and Social Care Research  dietitians participating in each meeting. During the first round of voting, most centres  agreed to use 1 g protein exchanges to calculate/measure all protein-containing foods except for fruit and vegetables. It was also agreed to adopt the same protein cut-off points as the UK PKU dietary guidelines to determine when a protein-containing food should be calculated as an exchange food or given without measurement . The pla(1)Tyrosine vs. phenylalanine (mg/100 g for fruit and vegetables) a,b;(2)Tyrosine (mg/100 g for fruit and vegetables) vs. protein (g/100 g) c,d;(3)Protein (g/100 g) vs. the sum of tyrosine and phenylalanine (mg/100 g for fruits and vegetables) e,f.The dietary system for calculating fruit and vegetables received two rounds of Delphi consultations. A correlation was made comparing the following: These results are shown in There was a clear and close correlation (r = 0.9) between tyrosine and phenylalanine (mg/100 g of food) for all fruits and vegetables. Similarly, there was a good correlation with tyrosine (mg/100 g for fruit/vegetables) when compared with protein (g/100 g for fruit/vegetables): r = 0.7 for fruits and r = 0.8 for vegetables. The sum of tyrosine and phenylalanine combined compared with protein g/100 g gave a correlation r = 0.8. A fruit and vegetable containing a phenylalanine content of 75 mg/100 g  for fruits and vegetables, the amount of phenylalanine was greater than the tyrosine content except for a single analysis of jackfruit from the USA, although this differed from the recent UK analysis (NSPKU 2022).n = 3 centres abstained from voting.Nine centres voted on the fruit and vegetable exchange system and agreed the same dietary principles could be used for fruit and vegetables in HTs as in PKU . Two cenFive individual fruits and vegetables had variable protein and tyrosine/phenylalanine analysis, and their allocations as part of the HT dietary system are summarised in This is the first publication reporting a systematic approach to standardise UK practices for the dietary management of HTs. The aim of dietary treatment is to limit tyrosine and phenylalanine intake while maintaining blood tyrosine and phenylalanine concentrations within target treatment recommendations ,25. The Any dietary practices adopted for HTs must be consistent, logical, effective, straightforward and easy to implement for families and health professionals. No dietary management should be unnecessarily restrictive. The aim of this Delphi process was to agree consensus statements on dietary management using both scientific evidence and practical experience permitting harmonisation of dietary HT practice across all UK centres. All UK IMD dietetic teams caring for HT patients were invited to contribute and all centres participated in at least one Delphi round, with a majority agreeing with the statements.Several initiatives, issues and supporting data prompted this consultation process. Firstly, the success of the BIMDG dietetic collaborative process in defining consensus statements in PKU. This resulted in consistent and clear guidance on calculating and defining protein exchanges for fruits, vegetables and manufactured foods for PKU, hence a recognised need to standardise the dietary approach for other amino acid conditions . The DelFor all foods except fruit and vegetables, it was agreed to use the protein analysis (1 g protein exchange system) to determine their suitability in the diet. Work by Evans et al. ,16 in coThe protein, phenylalanine and tyrosine analysis of 171 vegetables and 20 fruits was considered. The median number of amino acid analyses for each vegetable was three (range 1–7) and two (range 1–6) for fruits. There was a total of 21 (11%) ‘one only’ amino acid analyses, which is a recognised limitation. There were some anomalies in the amino acid analysis for the same vegetables and fruits; for example, watercress analysed by USDA  , had thrDifferentiating between the lower amounts of tyrosine in vegetables and fruit compared to animal, dairy and cereal products is important. Using exchanges adapted from protein will provide only approximate estimations of tyrosine intake and possibly lead to less dietary freedom. In PKU, many vegetables only contain 35 mg phenylalanine per gram of protein although inconsistencies are recognised . In the Amino acid analysis is complex ,35; seveThe Delphi system allowed parity, and IMD centres who cared for HT patients collaborated in the consultation period and the final statements . HoweverThis collaborative process was constructive, allowing IMD dietitians to focus on the anomalies of current dietary practice in HTs. Consensus was agreed to use 1 g protein exchanges for all dairy and cereal-based foods. For fruits and vegetables, the same dietary principles as the UK PKU dietary guidelines were adopted, basing calculations on their phenylalanine/tyrosine content, which contains a lower percentage concentration per gram of protein compared to animal, milk and cereals. Guidelines help health care professionals to deliver a consistent message. Discussion and consultation produced agreement amongst experienced IMD dietitians to change dietary practices in the management of HTs.


The most common metastasis sites of malignant stromal tumors are the liver, peritoneum, lung, and bones. Metastasis to the breast is extremely rare. Therefore, this is a very rare combination. Both being primary concomitantly is a further rare combination. Gastrointestinal stromal tumors (GISTs) and other primary carcinomas in the same patient are not unusual, and they are frequently discovered by chance. GISTs are uncommon mesenchymal tumors of the gastrointestinal (GI) system. There is a scarcity of information on the prevalence of mesenchymal tumors and other primary tumors in the literature. Therefore, more studies are required to establish the same. Concomitant GISTs accompany the most prevalent epithelial malignancies of the gastrointestinal system. More research is needed to shed insight into the molecular and genetic pathways of GIST and synchronous tumor oncogenesis and progression. This case report brings to light a synchronous double tumor of the breast and gastrointestinal stroma. Although it was previously believed that some cases of gastrointestinal stromal tumors (GISTs) are benign (do not spread), it is now understood that all GISTs have some potential to metastasize. Therefore, the origin being benign is contentious. They range in severity from benign, little nodules detected by chance to malignant tumors. They account for less than 1% of all gastrointestinal (GI) tumors. Their clinical presentation varies, which may lead to differential diagnoses requiring careful evaluation. Gastrointestinal stromal tumors (GISTs) start in very early forms of special cells in the wall of the GI tract called the interstitial cells of Canal (ICCs). More than half of GISTs start in the stomach. Most of the others start in the small intestine. A histogenetic derivation from these cells has been proposed. C-kit (receptor tyrosine kinase) (CD117) positivity is found in GISTs. Despite lacking KIT mutations, platelet-derived growth factor receptor (PDGFR) appears to be expressed in some GISTs. The stomach is more likely to develop C-kit or platelet-derived growth factor receptor-alpha (PDGFRA) mutation-driven mesenchymal tumors, which have a variety of specific histologic traits such as spindle cells, epithelial, or pleomorphic shape. The C-kit transmembrane protein, encoded by the kit proto-oncogene (chromosome 4q11-q12), serves as a receptor for stem cell factor (SCF). It has been discovered that C-kit and PDGFRA’s gain of function appears to play a substantial role in the oncogenesis of practically all GISTs [Patient informationA 40-year-old housewife came with complaints of a lump in the abdomen for six months. She also complained of loss of appetite, followed by significant weight loss (12 kgs in four months). The patient has no other significant comorbidities. She had regular menstrual cycles. She also underwent an open appendectomy six years back, apart from which the patient has not undergone any other surgeries. There was no history of similar complaints in the patient’s family.Clinical findingsThe general examination went off without a hitch. Per the abdomen examination, a lump of approximately 6 × 6 cm was present in the left hypochondriac region extending up to the left lumbar region, which was firm, mobile, and non-tender. The lump had well-defined margins with no local rise in temperature. Ballotability was present. On further examination, there was a lump of approximately 2 × 2 cm in the outer upper quadrant of the right breast. The lump was firm, non-tender, mobile, and painless with well-defined margins. A simple lymph node of approximately 2 × 1 cm in the posterior group was also palpable. The left breast and left axilla were unremarkable.Diagnostic assessmentRoutine blood investigations were sent  and were within normal limits. Abdominal and pelvic ultrasonography was done and was suggestive of a heterogeneously enhancing hypoechoic mass lesion showing calcific foci and internal vascularity, measuring 9.3 × 9 × 5.9 cm in the left hypochondrium, possibly arising from bowel loops/mesentery.Ultrasonography of bilateral breasts and axillae was done, and there was evidence of a hypoechoic oval lesion of approximately 19.8 × 12 mm in the outer upper quadrant suggestive of intraparenchymal lymph node, possibly fibroadenoma.Contrast-enhanced computed tomography (CECT) of the abdomen and pelvis were advised and suggested a heterogeneously enhancing large exophytic mass lesion involving the midpart of the jejunum measuring approximately 78 × 65 mm. The lesion showed non-enhancing areas of necrosis with a few calcific foci. The center of the lesion shows a large area of air density, with a possibility of it being an ulcerative lesion Figure .The lesion was causing a mass effect in the form of displacement of adjacent bowel loops. There was evidence of perilesional fat stranding and multiple subcentimetric to centimetric lymphadenopathy.There was also evidence of numerous heterogeneously enhancing subcentimetric to centimetric lymph nodes seen in pre-parasitic, aortocaval, central mesenteric, and bilateral paracolic regions, the largest being 1.6 × 1.3 cm in the central mesenteric part. It was associated with the wall thickening of jejunal loops adjacent to the above lesion. Features were suggestive of gastrointestinal stromal tumors arising from the jejunum.CECT of the thorax was also done and suggested a homogeneously enhancing soft tissue density lesion in the right breast suggestive of fibroadenoma BIRADS 2), with lymphadenopathy in the bilateral axillary region .However, the histopathology report suggests evidence of metastatic deposits and epithelial malignancy (possibly of breast origin) (estrogen receptor (ER): weak focal positive, progesterone receptor (PR): negative, Her2Neu: positive).The histopathology report of the jejunal mass was suggestive of gastrointestinal stromal tumor (spindle cell variant). Twelve lymph nodes were identified and were negative for infiltration by malignant cells. Pathological TNM staging (eighth edition) was pT3pNxpMx. In immunohistochemistry studies, the tumor cells expressed C-kit, DOG-1, and SMA and were immune-negative for S-100 protein.The medical oncologist’s opinion was taken for further management, and tablet imatinib 400 mg once daily (OD) for three years was suggested along with surgery for locally advanced breast cancer (LABC), followed by adjuvant chemotherapy.The presented case is unusual as the patient was diagnosed with breast carcinoma in an already diagnosed case of gastrointestinal stromal tumor arising from the jejunum. Some experts believe that the association between breast cancer and gastrointestinal stromal tumor (GIST) is just coincidental, while others believe that undiscovered carcinogens cause epithelial and stromal cell proliferation and oncogenesis.In two significant retrospective studies by Agaimy et al. on the incidence of related non-GIST malignancies in GIST patients, breast cancer had 11% and 7%. The genetic mechanisms of tumorigenesis in the two neoplasms appear to be different, although both GIST and breast cancer have a hereditary predisposition that has been proven. There has been speculation about a potentially shared origin and genetic routes to carcinogenesis, as well as the potential for similar therapeutic approaches, in light of the high occurrence of GISTs in breast cancer patients .Normal breast ductal epithelium and myoepithelial cells have been shown to express C-kit (receptor tyrosine kinase). In contrast, carcinoma cells, which are assumed to be responsible for inhibiting breast cancer cell growth signals, did not.According to Agaimy et al., 18 (18.6%) of 97 surgically removed GISTs had a subsequent neoplasm (mostly carcinomas), with two 2%) of them having breast malignancies. These two women developed infiltrating ductal mammary cancer, one with two concurrent liver metastases removed in the same setting as the initial GIST and the other with a large malignant GIST (10.5 cm and 12 cm). After 75 and 95 months, respectively, both were still living well. One of them also developed endometrial malignancy later on [% of themLudmir et al. described two cases of GIST and primary breast lymphoma (PBL) that occurred simultaneously. Given the dubiousness of the co-occurrence of such rare tumors, there may be a common underlying variation driving both lesions, leading to speculation that these cancers may share common antiapoptotic pathways . HoweverIn a study piloted on a small sample of patients in 2000, Maiorana et al. provided the first documentation of the occurrence of different cancers in GIST patients, and 52 cases of gastric GIST were examined by the researchers. Six of them had additional tumors, stomach adenocarcinomas in five cases and carcinoid tumors in one case. None of the 52 cases was associated with breast carcinoma, thereby highlighting the rarity of our case .By dividing patients into four groups based on the index tumor and whether the linked neoplasm was synchronous or metachronous, Fernández et al. established a classification based on the temporal connection between GISTs and other malignancies. In 2018, the same authors reported a series of patients with GISTs associated with additional second major tumors, comparing the various subgroups of associated GISTs by the suggested classification. The primary study findings revealed that synchronic diagnoses of GIST and a second primary tumor occurred in 41.2% of patients. The related tumors were discovered before GIST in 23.5% of cases, after GIST in 35.2% of cases, and as synchronous associated neoplasm in 2.9% of cases during GIST staging [Based on this scenario, we wish to underline the importance of considering the possibility of synchronous and metachronous tumors during the clinical evaluation of patients with malignancies, rather than merely the occurrence of metastatic diseases. In conclusion, primary tumors and GIST might occur together more frequently than previously thought, and they typically become apparent by chance after surgery for another cancer. Even more cases of GIST may be found in patients with adenocarcinoma if the search for them is conducted more aggressively. Hence, initial evaluation is all the more important so as to not miss synchronous tumors. The molecular and genetic processes of carcinogenesis and progression linked to GIST and synchronous tumors need to be clarified through additional research.


The fasting blood glucose (FBG) values extracted from electronic medical records (EMR) are assumed valid in existing research, which may cause diagnostic bias due to misclassification of fasting status. We proposed a machine learning (ML) algorithm to predict the fasting status of blood samples. This cross-sectional study was conducted using the EMR of a medical center from 2003 to 2018 and a total of 2,196,833 ontological FBGs from the outpatient service were enrolled. The theoretical true fasting status are identified by comparing the values of ontological FBG with average glucose levels derived from concomitant tested HbA1c based on multi-criteria. In addition to multiple logistic regression, we extracted 67 features to predict the fasting status by eXtreme Gradient Boosting (XGBoost). The discrimination and calibration of the prediction models were also assessed. Real-world performance was gauged by the prevalence of ineffective glucose measurement (IGM). Of the 784,340 ontologically labeled fasting samples, 77.1% were considered theoretical FBGs. The median (IQR) glucose and HbA1c level of ontological and theoretical fasting samples in patients without diabetes mellitus (DM) were 94.0  mg/dL and 5.6 %, and 92.0  mg/dL and 5.6 %, respectively. The XGBoost showed comparable calibration and AUROC of 0.887 than that of 0.868 in multiple logistic regression in the parsimonious approach and identified important predictors of glucose level, home-to-hospital distance, age, and concomitantly serum creatinine and lipid testing. The prevalence of IGM dropped from 27.8% based on ontological FBGs to 0.48% by using algorithm-verified FBGs. The proposed ML algorithm or multiple logistic regression model aids in verification of the fasting status. The development of algorithms to identify patients with prediabetes and diabetes mellitus (DM) with high validity has become increasingly fundamental in improving the patients’ quality of care and preventing complications associated with DM. In current clinical practice, the phenotypes of DM are defined by various combinations of the different components of the EMR, such as diagnostic codes, medication data, and laboratory values related to glucose homeostasis2. Thus, current diagnostic algorithms have yielded significant variation in the validity for identification of DM2. In recent years, several studies have indicated that machine learning (ML) algorithms may better identify diabetic status in EMRs for cohort establishment4. Other studies applied ML techniques to predict DM or undiagnosed DM based on clinical information8. Systematic reviews reported that most ML studies used the supervised learning approach and a comparison of the approaches indicated that support vector machine (SVM) was the most widely used algorithm10. Deep learning (DL) models such as artificial neural networks (ANNs) and deep neural networks (DNNs) have been applied and reported in some studies showing superior performance than conventional ML approaches in predicting DM-related phenotypes12. However, these studies usually assumed that fasting blood glucose (FBG) values are valid if labeled as such by the clinical laboratory, which may lead to potential overestimation of fasting status13. As demonstrated in a survey conducted by Tseng et al., only approximately half of the patients reported to have adequately fasted before phlebotomy at a large academically affiliated hospital13. Another study surveyed around 150 outpatients and stated that 40% did not fast before going to the hospital for laboratory blood work14. Both studies pointed out that documentation of fasting state before phlebotomy was often non-existent as these data are not routinely collected by healthcare providers or the laboratory team and recorded in the EMR. Similarly, information regarding whether patients had been given instructions to fast before phlebotomy was also not recorded14. Despite the importance of the fasting status in patients undergoing phlebotomy, there has been relatively few research conducted in the current literature to verify the fasting status of patients before blood work. The lack of knowledge of the fasting state of patients presents a challenge for healthcare providers in determining whether patients had truly fasted before laboratory blood testing and may prohibit them from interpreting the results in accordance with diabetes screening guidelines, resulting in missed diagnoses of prediabetes and type 2 diabetes.With the universal implementation of electronic medical records (EMRs), researchers have actively leveraged real-world EMR data in diabetes research and management in clinical practice15. Verification of fasting blood samples is therefore a significant challenge in analyzing real-world EMR data for epidemiological research, particularly when the disease diagnostic criteria are based on fasting blood samples. The current reference standard for confirmation of the fasting status relies on self-reported information from the patients during phlebotomy, which may be influenced by recall and awareness biases. To the best of our knowledge, no studies have used EMR data to investigate the discordance between prescribed and actual fasting status based on the distribution of BG and concomitant HbA1c values. Using a large clinical data repository of more than 2.75 million patient records from a tertiary medical center in central Taiwan, we systematically evaluated the distribution of BG values. We used the HbA1c-estimated average glucose level to define fasting status, followed by the development of prediction models using ML.Misclassification of fasting status negatively influences the clinical accuracy of conventional or ML models in screening DM or predicting the risk of DM19. Of the 2,873,887 patients, 945,792 underwent glucose measurements using sera samples from inpatient and outpatient services. The sample selection flow is summarized in Fig. The China Medical University Hospital (CMUH) Clinical Research Data Repository (CRDR) carefully validated the EMRs of 2,873,887 patients who had sought care at CMUH between January 1, 2003, and December 31, 2018. The methodologic details have been published elsewhereThe covariables of interest were obtained from the CRDR, including patient demographics, specifically age and sex, and body mass index, which was calculated as the weight in kilograms divided by the height in square meters. The presence of hypertension or type 2 DM was captured based on associated ICD-9/-10 codes or the use of glucose-lowering medications or antihypertensive agents. A history of cardiovascular disease was also documented if the patients had a record of coronary artery disease, myocardial infarction, stroke or congestive heart failure in EMRs based on International Classification of Diseases (ICD) 9th and 10th edition codes. All other coexisting comorbidities were also captured based on ICD-9/-10 codes from the repository or EMR data. Additional provider- or patient-level factors such as medication records, health care provider specialty, and biochemical measures were obtained from repository data or the EMRs within a 1-year window prior to enrollment into the study cohort.22.Therefore, we calculated the straight-line distance between hospital to home as it is the most common method for this type of calculation23. The home-to-hospital distance was calculated in two steps. First, a geocoding application programming interface developed by Google Maps was used to transform the map coordinates of the entire study population’s home addresses and locations. The distance between the homes and the hospital was calculated using the geographic information system .Another patient-level factor that we included was the distance from the patients’ home to the hospital as we hypothesized that fasting status might be associated with the travel time to the healthcare facility. Currently, no studies have investigated the association of distance between healthcare facilities and homes and fasting status. However, a few studies have provided evidence that increasing travel distance to the primary care provider may affect and decrease glycemic control® LX20 and Beckman UniCel® DxC 800  from January 1, 2003, to September 30, 2007, and from October 1, 2007, to December 31, 2018, respectively. The level of HbA1c was measured using boronate affinity and high-performance liquid chromatography (HPLC) methods with the Primus CLC385 analyzer from January 1, 2003, to June 30, 2008, cation exchange HPLC methods with the Tosoh HLC-723 G7  from July 31, 2008, to December 31, 2013, and boronate affinity and HPLC methods with the Trinity Biotech Premier Hb9210 from January 1, 2014, to December 31, 2018.Blood glucose levels were determined by the central laboratory using the Beckman Oxygen electrode (glucose oxidase method) with a Beckman Synchronaverage) was defined based on Nathan et al.’s formula as a theoretical upper limit of fasting glucose24.From the CMUH-CRDR laboratory database, we selected the glucose measurements specified as fasting glucose , postprandial glucose , and random glucose. We excluded data recorded as nonnumerical values, values higher than 1000 mg/dL, or zero values. All glucose measurements could also be classified as inpatient, outpatient clinic, and emergency department services. Only measurements obtained in the outpatient setting were included in the final analysis. The HbA1c-derived averaged glucose level  as follows. Glucose measurements were reclassified as non-AContological if:the data were labeled as post cibum glucose or random glucose,the glucose measurement included additional descriptions/labels such as “one-touch”, “bedside check”, or “PC” or contained descriptions indicating active food intake before phlebotomy, regardless of the laboratory test prescribed ,ontological.patients had multiple fasting glucose measurements on the same day; only the first measurement was considered as non-ACTo investigate the “true” ontological fasting status on blood glucose measurements, we filtered glucose measurements that were highly likely nonfasting in the outpatient setting to derive ontological fasting glucose  of patients who underwent concomitant AContological and HbA1c measurements on the same day: (1) an AContological < 100 md/dL in patients without DM with HbA1c < 5.5%; (2) an AContological < ACaverage − 1 standard deviation of AContological glucose in patients without DM with an HbA1c between 5.5 and 6.4%; and (3) an AContological < ACaverage in patients with DM. Once the patients' glucose AC was defined as ACtheoretical, the corresponding blood samples were defined as fasting samples. Otherwise, they were considered nonfasting samples. These criteria are based on the physiological profiling of glucose and insulin variation over 24 h in individuals with and without diabetes26. The A1c-derived estimated average glucose (ACaverage) summarizes the daily glucose variation over the past 90 days, depicting an averaged value between the lowest and the highest glucose level in this time window among patients with a stable metabolic state. Therefore, if truly obtained in the fasting status, the glucose level should be theoretically less than the level of ACaverage27. To verify the validity of our proposed criteria, we used the glucose AC from 4519 patients who provided morning fasting samples before the procedure of pan-endoscopy in CRDR as the true fasting glucose AC and only 314 measurements (6.95%) were misclassified as nonfasting based on our criteria.Three criteria were used to define the theoretical fasting status  statistics and calibration curves.ontological and ACtheoretical, which was composed of 93,958 patients , a scalable end-to-end tree boosting model proposed by Chen and Guestrin28, to evaluate the performance of predicting fasting status. We additionally experimented with two efficient algorithms, CatBoost and ensemble models with H2O AutoML, to better handle the categorical variables and explore the predictive performance using multiple learning algorithms30. The objective function of this binary classification problem was to minimize binary entropy loss; the hyperparameters of our XGBoost model were determined using the Tree of Parzen Estimators (TPE) method31. Taking the implementation of XGBoost in Python as an example, the finalized hyperparameters were set as tree depth = 8, learning rate = 0.1, gamma = 0.5, minimum sum of instance weight = 7, number of estimators = 300, and the remaining parameters were set using the default setting. Detailed parameter ranges for grid search were summarized in Supplementary Table theoretical. The performance quantification of each ML algorithm was evaluated in terms of AUROC, accuracy, precision, recall, and F1 score using a fivefold cross-validation scheme. We used the bootstrapping method with 2000 repetitions to statistically test the difference between the paired AUROCs32. Finally, we compared the proportion of glucose AC ≥ 126 mg/dL calculated with or without the ML algorithm to classify the fasting status. We also classified glucose AC ≥ 126 mg/dL, regardless of ontological or predicted fasting samples, which did not lead to the diagnosis of diabetes over the study periods as ineffective glucose measurements (IGM). All statistical analyses were performed using SAS version 9.4 , R version 3.5.1 , and Python version 3.7.3 under a Linux operating system. The Python package version was 1.5.2 for XGBoost, 1.0.4 for CatBoost, and 3.36.0.2 for H2O AutoML. The two-sided statistical significance level of α was set at 0.05.To use ML for predicting whether the blood samples were obtained in the fasting state, a balanced dataset was curated to obtain a 1:1 ratio of ACThe study was approved by the Research Ethical Committee/Institutional Review Board of China Medical University Hospital (CMUH105-REC3-068).ontological data points were included in the final analysis, with a mean sample age of 59.7 ± 14.6 years. Approximately half of the sample population were female (46.1%). When restricting to only the patients’ first sample in the CRDR , the average age was 54.4 ± 15.5 years, and 45.9% of these patients were female. Of these 93,958 patients, 29.2% had been diagnosed with DM at the first AContological. Blood glucose measurements considered to be collected during fasting state were observed in younger non-DM patients but not among younger patients with DM. Nonfasting samples were more likely to be provided by male patients, regardless of their diabetic status. Moreover, samples were more likely to be fasting measures if the lipid profiles of the patients were concomitantly examined. Statistical differences were observed for the majority of the biochemical measures between fasting and nonfasting samples. Specifically, levels of triglyceride demonstrated clinically significantly different results (> 15 mg/dL) between fasting and nonfasting samples, regardless of the diabetic status , accuracy (80.9% vs. 78.5%), and F1 score , and the corresponding trend of prevalent prediabetes based on algorithm-verified FBGs was also 24.1% lower than that based on AContological (40.2%). Although the difference was not radical, the absolute misclassified number from DM to nondiabetes can be significant, depending on the population size. Indeed, due to the increasing interest and use of digital health tools to detect abnormal blood glucose levels, misclassification of nonfasting glucose measures as fasting may lead to potential overdiagnosis and treatment of patients without DM.Our results showed that lipid profiles, except triglyceride level, were not affected by fasting status. Especially among patients without DM, levels of fasting TCHO, LDL-C, and HDL-C were counterintuitively higher than those from the nonfasting samples. This finding supports the trends of using nonfasting lipid profiles to facilitate risk assessment of atherosclerotic cardiovascular disease and assures the feasibility of our algorithm in classifying fasting status by comparing the difference between AContological and algorithm-verified nonfasting glucose, which could serve as a checkpoint and reminder in the automatically digital phenotyping process for DM screening. Future research on clinical effectiveness and automatic fasting status prediction implementation in the flow of digital diabetic phenotyping systems is necessary to strengthen the public health impact.The concept of IGM is worthy of broader discussion as it stands for a measurement of FBG that did not change the clinical course of glucose metabolism even when the level was greater than 126 mg/dL among patients without a history of DM. Several reasons could help explain this observation, such as clinician knowledge of the nonfasting status or a missed interpretation of the result. Nonetheless, a potential consequence of IGM is missing the detection of diabetes, leading to complications and increased healthcare utilization in the long run. Failing to obtain a truly FBG may be problematic for diabetes screening. Our proposed algorithms drastically reduced the proportion of IGM, supporting their use in the real-world care flow to trigger actionable screening of diabetes. These algorithms also help generate a warning upon detecting the discrepancy between AContological should be less than ACaverage in the fasting status among outpatients with stable dietary habits and a steady level of carbohydrate metabolism. In the crude analysis, we found that patients from the Health Management Center were more likely to be in the fasting state before phlebotomy. This observance corresponds to our clinical experience, where patients who were relatively healthy and willing to attend health checkups typically have a higher motivation to provide fasting samples. Specifically, patients who undergo health checkups usually receive detailed instructions for fasting36. Furthermore, over 93% of FBGs obtained from patients prepared for a pan-endoscopy were accurately classified as ACtheoretical. Second, the algorithm was developed in a tertiary hospital under universal health care coverage; thus, it may not be generalizable to other settings. Further research with additional data from different populations is required to train and solidify our proposed algorithm. More importantly, integrating our algorithm into the clinical workflow is critical to verify its performance in the real-world setting.The present study has several limitations. First, the actual fasting status of the patients was not available. However, it is challenging, if not impossible, to obtain the actual fasting status. We assumed that ACTo the best of our knowledge, this is the first attempt at using a ML approach to evaluate the reliability of fasting samples in a large tertiary hospital. Only 65.3% of ontologically AC samples could be classified as algorithm-verified fasting status. Despite its moderate performance in predicting the fasting status among outpatients, our algorithms provide an innovative approach to clean medical data and facilitate true fasting BG detection. Notably, this study has introduced an essential step towards establishing automated phenotyping in EMR for effective diabetic screening and more accurate estimation of the global and local epidemiology of DM.Supplementary Tables.


Santalum album L.) trees by treatment with carbon dioxide, ethylene, nitrogen, and wounding was investigated. All treatments induced fragrant heartwood formation upward and downward from the drill hole. The amount of heartwood formed above and below the drill hole depended on the treatment in the order nitrogen>carbon dioxide>ethylene>wounding, whereas the radial extension proportion was, in order, nitrogen>carbon dioxide>ethylene=wounding. Based on the chemical analysis (GC–MS) and evaluation of the essential oil quality and heartwood properties, heartwood induced by carbon dioxide showed the maximum similarities to naturally formed heartwood, which included the same color, similar chemical composition, reasonable oil content, and quality essential oil, whereas ethylene, nitrogen, and wounding treatment showed fewer similarities to natural heartwood. The results suggest that carbon dioxide is a promising candidate gas elicitor for inducing heartwood formation in young S. album.Induction of heartwood formation in 6-year-old Indian sandalwood ( In most hardwood tree species, the trunk wood can be divided into living sapwood and dead heartwood. Heartwood lies in the inner layers of the secondary xylem, has ceased to contain living cells, and is characterized by the accumulation of extractives . Sapwood contains living cells  and is characterized by a high content of reserve materials Anon, . These dSantalum album L.), commonly known as East Indian Sandalwood, is the most famous valuable tree species belonging to the Santalaceae family and is highly valued for its fragrant heartwood, which has various applications in the perfumery, religion, cosmetic, wood carving, and pharmacological industries  atmosphere, heartwood flavonoids specific for A. mearnsii were induced  can induce discolored heartwood formation in Pinus sylvestris, and the chemical composition of induced the heartwood was quite similar to that of naturally formed heartwood  by affecting the activities of microorganisms in standing stems and suggested that there is a threshold for oxygen concentration to trigger red heartwood formation.Stem gases play the important roles related to many physiological or metabolic processes in trees, such as aerobic respiration, the tricarboxylic acid cycle, secondary metabolism, and heartwood extractive accumulation, which can further regulate heartwood formation  influence fragrant heartwood formation in young sandal.Compared to liquid elicitors, gaseous elicitors seem to induce a larger amount of heartwood because pressurized gases can permeate almost everywhere in stems or branches , Clausena lansium (Lour.) Skeels (Rutaceae), Ligustrum lucidum Ait. (Oleaceae), and Murraya exotica L. (Rutaceae), one of which was planted between two sandalwoods with a spacing of 3 × 3 m. A preliminary study showed that this area was suitable for sandalwood growth and that the trees formed heartwood naturally at an early age . The mean temperature is 23°C, and the annual rainfall is 1,700 mm. The plantation was first established in April 2004 in a laterite soil type with a sandalwood spacing of 3 × 3 m, and the main hosts were S. album) without natural heartwood formed were selected randomly from a 6-year-old sandalwood plantation planted in the above sandalwood experimental and demonstration base. The presence of natural heartwood was determined by the color and odor of wood chips drilled through the central bottom of each sandal using a hand drill. The average height was 5.14 ± 0.43 m, and the average diameter on breast height (DBH) was 8.52 ± 0.41 cm. The selected trees were then divided into three gas treatment groups, one wounding group and one control group, and each treatment consisted of 6 individuals.A total of thirty sandals (2), ethylene , and nitrogen . Nitrogen was applied to create a hypoxic environment, wounding group consisted of sandals that remained untouched during the whole experiment after the holes drilled, and another control group kept the same (without drilling hole), just to observe whether heartwood formed naturally during the experiment.Holes measuring 10 mm in diameter were drilled (without drilling through the trunk) using a hand drill at 1-m height above ground. The depth of each hole was calculated as the diameter minus 1 cm . After dAn increment borer  was applied to draw two core samples from each tree at approximately 1 cm above the hole and at right angles to each other. The presence of heartwood and the length of heartwood and sapwood were determined and recorded. To determine the maximum extension distance of heartwood in each tree, we repeated the core sample collection procedure every 5 cm above or below the hole until no heartwood was observed. Using the above data, the whole extension area upward and downward from the hole can be simulated by drawing software . All the cores were sealed separately with parafilm and then stored in a cooled insulated container before being transported to the laboratory, where the essential oil content and oil composition were determined.The basic density and relative water content of the induced heartwood were determined immediately after core sample collection. The basic density (bone-dry weight per unit of fresh volume) was determined using the water displacement method, and the dry weight was obtained after drying at 105°C to constant weight. The water content  was calculated as the percentage of water content per fresh weight  and then ground into fine particles. Essential oil was extracted from the heartwood powder using the solvent (diethyl ether) extraction method  according to the methodology by Howes et al.  and Liu Analysis of variance (ANOVA) was performed on each dataset using the statistical program SPSS 18.0 SPSS I,  after ex2), which showed the significant differences when compared to the other treatments (p < 0.05), and the corresponding extension ranges were 16 and 17 cm, respectively. The maximum radial extension proportion of induced fragrant heartwood was 56% on average; however, the color of induced heartwood seems to be paler or lighter than that of naturally formed heartwood  induced less extended heartwood than N2, the corresponding upward and downward extension ranges were 11 and 12 cm, respectively, and the radial extension proportion of induced heartwood was 45% on average, but the color of induced heartwood was quite similar to that of naturally formed heartwood. The ethylene (C2H4) and wounding treatments induced the least amount heartwood, and the upward and downward extensions from the drill holes were quite similar . The radial extension proportions of C2H4-induced and wounding-induced heartwood were 24 and 22%, respectively. The amount of fragrant heartwood induced by C2H4 was slightly higher than that induced by wounding in both the longitudinal extension range and radial extension proportion; however, no significant difference was observed  or basic density (p = 0.996) of the induced heartwood in young sandals (α = 0.05). Treatment with C2H4 resulted in the highest water content and basic density (The results of the different gas treatments on the properties of induced heartwood are shown in  density .p = 0.003) of the induced heartwood among the gas treatments according to the ANOVA, and the color of the extracted essential oil was different in shade  were observed among the different gas treatments in the content of the main characteristic compounds of the essential oil viz. α-santalene, α-bergamotene, epi-β-santalene, β-santalene, α-santalol, and β-santalol according to the ANOVA  from the essential oil, followed by treatment with CO2 and N2, both of which had 25 identified constituents. The wounding treatment obtained the lowest number of identified ingredients with only 23 components identified. Although great variations in chemical composition and relative content were observed among the different treatments, the most dominant compounds in all gas treatments were found nearly in the same order: α-santalol > β-santalol > α-trans-bergamotenol > epi-β-santalol , total santalenes (p = 0.003), total sesquiterpenes (p = 0.039), and total sesquiterpene alcohols (p = 0.002). Treatment with CO2 was most favorable for santalol and sesquiterpene alcohol synthesis, whereas treatment with C2H4 was helpful for santalene and sesquiterpene accumulation  requires that the essential oil contains both 41–55% α-santalol and 16–24% β-santalol  did not meet the current ISO standards and cannot be traded on the international market.The current International Organization for Standardization standard for ISO 3518: requiresectively . This maPopulus tremuloides  and Type II (Juglans-type). The phenols and terpenes stimulated by ethylene may partly accumulate in the newly formed heartwood  and the National Natural Science Foundation of China (Grant No. 31500512).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.