Formation of highly interpenetrated frameworks is demonstrated. An interesting observation is the presence of very large adamantane‐shaped cages in a single network, making these crystals new entries in the collection of diamondoid‐type metal–organic frameworks (MOFs). The frameworks were constructed by assembling tetrahedral pyridine ligands and copper dichloride. Currently, the networks’ degree of interpenetration is among the highest reported and increases when the size of the ligand is increased. Highly interpenetrated frameworks typically have low surface contact areas. In contrast, in our systems, the voids take up to 63 % of the unit cell volume. The MOFs have chiral features but are formed from achiral components. The chirality is manifested by the coordination chemistry around the metal center, the structure of the helicoidal channels, and the motifs of the individual networks. Channels of both handednesses are present within the unit cells. This phenomenon shapes the walls of the channels, which are composed of 10, 16, or 32 chains correlated with the degree of interpenetration 10‐, 16‐, and 32‐fold, respectively. By changing the distance between the center of the ligand and the coordination moieties, we succeeded in tuning the diameter of the channels. Relatively large channels were formed, having diameters up to 31.0 Å×14.8 Å. Tetrahydral achiral ligands and copper ions assemble into a record number of interpenetrating diamondoid networks. The networks intertwine akin to strands of a molecular rope to shape the chiral channels. The design of the ligand “arms” allows modulating their degree of interpenetration and the channel properties. The concurrent presence of such numerous interpenetrated networks and porosity is unprecedented for metal–organic frameworks. Better understanding how it evolves and recognizing when it is present are important, both for inferring general rules of fundamental interest and for enlarging the library of potential useful materials.4, 5 AWe previously reported that tetrahedral pyridine‐based ligands generate metallo‐organic single crystals having a uniform and/or unusual multidomain morphology.26, 27In this study, the coordination chemistry of three different but structurally related ligands with copper dichloride is reported. The structures we obtained confirm the tendency of this kind of ligand to generate chiral channels.27, 28L1‐L3) we used are achiral, and owing to their tetrahedral symmetry (Td), they are structurally suitable for the general strategy for forming diamondoid‐type structures.L1 and L2) or an adamantane (L3) core . The vessels were gradually cooled down after 16–48 h of heating. In order to solubilize the ligands in DMF, we used small amounts of HCl, which, by protonating the pyridine groups, enhances their polarity. This method may seem counterintuitive, as the coordination sites are actually inactivated; however, the formation of coordination‐based crystals is thermodynamically favored. The materials were analyzed by both bulk and single crystal measurements: optical microscopy, microRaman and UV/Vis spectroscopy, elemental and thermogravimetric analysis (TGA), Powder X‐ray Diffraction (PXRD), and single‐crystal X‐ray Diffraction (SCXRD) measurements. Optical microscopy images show that 10‐DIA consists of green rod‐like structures . Green rods and multibranched aggregates were observed for 16‐DIA . The sample obtained from the reaction between L3 and CuCl2 contains 32‐DIA as globular reddish structures and needles of L3, as judged by optical  and microRaman spectroscopy . Attempts to remove L3 by washing in organic solvents were unsuccessful because of its low solubility.The ligands  were observed both in the position and ratio of the peaks in the ν=1590–1633 cm−1 range, indicative of pyridine coordination to the metal centers.λ=370 up to the near IR region. The spectroscopic features indicate the presence of both ligand‐to‐metal and metal‐to‐ligand charge transfer . that makes the ten nets eclipse if viewed along the c‐axis. 16‐DIA is 16‐fold of the class IIIa, where the translation vector [001] relates to 8 interpenetrating networks, and the 8 other networks are related to former ones by two diagonal glide planes n oriented as (100) and (010). What is peculiar here is that this geometry does not affect the topological type of entanglement, which is the same as the one observed from 10‐DIA, where all the nets are related by a single translational vector. We can conclude that the two structures both present the most common interpenetration mode that aligns all nets equally spaced along the S4‐axis of the adamantane cage . ; 15 of the 17 known examples of diamondoid nets have 10‐fold or more interpenetration, as presented in the Table S1. The 10‐fold structures with CSD refcodes, FUXCOS, PUQDOW, XISXAY, and MOXPUL, and the 12‐fold structure, OMUNER09, have similar 1‐periodic helical channels of rectangular cross‐section, as observed in 10‐DIA and 16‐DIA because of a similar “normal mode” of interpenetration. From the analysis of the three structures, we can see that the record 32‐fold interpenetration of dia nets in 32‐DIA arises from the longer ligand bridged with metal cations . Bridging metal cations elongating the edges also gives rise to other structures with the highest degrees of interpenetration 20 (KUVMEV) and 25 (ZEFHEZ). Some loose correlation could be seen relating to the edge length and the angles at the mid edge, as shown in the plots for the 20 structures . The size of the accessible channels is also not always proportional to the elongation of linkers. Some of the straight edges of the underlying net of 32‐DIA intersect due to an abnormal mutual orientation of nets; therefore, the walls of the channels are constructed using bent linkers (angle 147°) . In this way, the observed mode of interpenetration  reduces the pore dimensions more than the normal mode would and increases the density of the structure due to the larger number of nets filling the same space. The abnormal mode of interpenetration also prevents the presence of accessible channels in six other highly interpenetrating structures . How do the crystal structures for the MOFs comprising L1, L2, and L3 compare? The obvious differences lie in the core and in the “arm” dimensions. Looking at the ligands in the crystal packing, one can observe the following characteristics: All the ligands have similar distortions. Starting from symmetric pyramids , where the ligands are inscribed with the pyridine units at the vertexes, deviations occur in asymmetric pyramids with isosceles triangles as facets . The ratio between the sides of the triangles is 1.3‐1.5. The triangle angles are about 43° and 68°. The volumes inscribing L1, L2, and L3 are 560.4, 2152.5, and 2895.1 Å3, respectively. The “arms” of L3 are more curved. We noted that for both L2 and L3 the pyridine groups are rotated either oppositely or coherently with respect to the phenyl rings. This results in two sets of two structurally different “arms” within one molecule. However, this effect is not observed in L1. Addressing the posed question is not trivial. The adamantane cage size, interpenetration level, and ligand curvature (bending) appear to be correlated. The increased size of the adamantane cages allows for a higher interpenetration of the networks. This structural effect is consistent with a higher bending of the ligand arms.The largest dimension of the adamantane‐type cages also increases from 76.4 Å , and ligand structure .. 1H NMR  δ 8.58 , 7.51 , 7.43 , 7.36 , 7.29 , 7.01 , 6.73 , 5.80 , 5.29 . 13C NMR  δ 150.18, 144.55, 137.99, 136.22, 135.60, 132.69, 127.20, 126.65, 125.80, 120.80, 114.47. ESI‐MS: m/z [M+H]+ calcd. for C15H14N: 208.28, found: 208.18, correct isotope distribution.L2Synthesis of : Compound 4E)‐phenylethenyl)]pyridine  were mixed in a 50 mL pressure tube. Subsequently dry N‐methyl‐2‐pyrrolidone (6 mL) was added in a N2 filled glovebox. The pressure tube was closed and heated in an oil bath at 130 °C for 5 days. After cooling down the tube, 30 mL of H2O was added and the resulting solid was collected via filtration. The solid was washed with water and dried under vacuum. Acetone (300 mL) was used to disperse the solid which was then filtered. The product (L2) was obtained by collecting the remaining solid which was further purified by flash column chromatography. The silica was first neutralized with triethylamine and then eluted with CHCl3 mixed with methanol (1.0‐4.0 %) resulting in the isolation of L2 . 1H NMR  δ. 8.45 , 7.49 , 7.41 , 7.36 , 7.28 , 7.24 , 7.11 , 7.05 , 6.98 . 13C NMR  δ 149.40, 146.09, 145.23, 137.88, 135.20, 134.86, 133.14, 131.19, 128.70, 127.98, 127.38, 126.83, 125.83, 125.31, 120.98. UV/Vis (CHCl3): λmax =367 nm (1.31×105). ESI‐MS: m/z [M+H]+ calcd. for C85H65N4: 1142.45, found: 1142.77, correct isotope distribution.L3Synthesis of : Compound 5E)‐phenylethenyl)]‐pyridine  were added in a 50 mL glass pressure tube. Dry N‐methyl‐2‐pyrrolidone (6 mL) was added in a N2‐filled glovebox. The sealed tube was heated for 130 °C for 5 days. After cooling down, 30 mL of H2O were added and the resulting precipitate was collected via filtration. The collected solid was washed with water and dried under vacuum. Acetone (300 mL) was used to disperse the solid which was then filtered. The product (L3) was obtained by collecting the remaining solid which was further purified by flash column chromatography. The silica was first neutralized with triethylamine and then eluted with CHCl3 mixed with methanol (1.0–4.0 %), Compound L3  was obtained after recrystallization from DMF. 1H NMR  δ 8.46 , 7.48 , 7.36 , 7.27 , 7.13 , 7.06 , 6.99 , 2.17 . 13C NMR  δ 149.58, 149.16, 145.40, 138.13, 135.27, 133.32, 129.03, 127.71, 127.53, 126.96, 126.73, 125.52, 125.42, 121.14, 45.91, 39.40. λmax =364 nm (1.55×105). ESI‐MS: m/z [M+H]+ calcd. for C94H77N4: 1262.64, found: 1263.00, correct isotope distribution.Formation of 10‐DIA, 16‐DIA, and 32‐DIA: In a 5.0 mL vial, the ligand was dissolved in DMF . Subsequently, 3 μL, 2 μL, and 5 μL of HCl (37 %) was added to DMF solutions containing L1, L2, or L3, respectively. The metal salt solution was prepared by dissolving CuCl2  in DMF (5.0 mL). This solution was added to the solutions containing L1(0.96 mL), L2 (0.52 mL), or L3 (0.4 mL). The vials were sealed and heated in an oven at 105 °C for 24 h (10‐DIA), 16 h (16‐DIA) and 48 h (32‐DIA). The reaction mixtures were allowed to attain room temperature by decreasing the temperature (10 °C/hour) of the oven by a controller . The precipitates were separated from the solutions by centrifugation, and then washed with methanol, affording 10‐DIA (green), 16‐DIA (light yellow), and 32‐DIA (dark red) in a yield of 50–70 %. The latter sample contains both 32‐DIA and L3 (needles).10‐DIA) and CCDC 2081777 (16‐DIA) and 2081778 (32‐DIA)2081776 ( contain(s) the supplementary crystallographic data for this paper. These data are provided free of charge by the joint Cambridge Crystallographic Data Centre and Fachinformationszentrum Karlsruhe Access Structures service.Deposition Number(s) The authors declare no conflict of interest.1As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.Supporting InformationClick here for additional data file.


Candida species – a major predisposing factor for disseminated candidiasis. Commensal bacteria such as Lactobacillus rhamnosus can antagonize Candida albicans pathogenicity. Here, we investigate the interplay between C. albicans, L. rhamnosus, and intestinal epithelial cells by integrating transcriptional and metabolic profiling, and reverse genetics. Untargeted metabolomics and in silico modelling indicate that intestinal epithelial cells foster bacterial growth metabolically, leading to bacterial production of antivirulence compounds. In addition, bacterial growth modifies the metabolic environment, including removal of C. albicans’ favoured nutrient sources. This is accompanied by transcriptional and metabolic changes in C. albicans, including altered expression of virulence-related genes. Our results indicate that intestinal colonization with bacteria can antagonize C. albicans by reshaping the metabolic environment, forcing metabolic adaptations that reduce fungal pathogenicity.Intestinal microbiota dysbiosis can initiate overgrowth of commensal  Lactobacillus rhamnosus can inhibit the pathogenicity of the fungus Candida albicans. Here, Alonso-Roman et al. investigate the interplay between C. albicans, L. rhamnosus and intestinal epithelial cells, showing that changes in the metabolic environment, induced by the bacteria, trigger adaptations in C. albicans that reduce fungal pathogenicity.Commensal bacteria such as  Candida albicans is a common commensal of the intestinal mycobiota2. However, certain predisposing conditions, such as a dysbalanced microbiota and a compromised immune system can favour its shift from a commensal to a pathogenic stage3. Consequently, C. albicans can translocate through the intestinal epithelium into the bloodstream5, resulting in disseminated candidiasis associated with high mortality rates6. Specifically, an intact epithelial barrier, the immune system, and the commensal intestinal microbiota play crucial roles in maintaining C. albicans commensalism by suppressing overgrowth and pathogenicity8. Bacteria belonging to different genera, such as Bifidobacterium, Streptococcus and, more extensively, Lactobacillus, have been studied with regard to their antagonistic effects against C. albicans10.The yeast Lactobacillus species have been discussed as oral probiotics to prevent candidemia in premature newborns12 and are also being explored as potential therapies against vulvovaginal candidiasis15. In vitro studies have demonstrated that lactobacilli can antagonize proliferation9, hypha formation21, biofilm formation23, or even kill C. albicans25. However, these studies often do not recapitulate the role of the host or its epithelial barriers as active partners in the interaction. Previously, we demonstrated that the antagonistic effects of L. rhamnosus on intestinal epithelial cells (IECs) are associated with reduced C. albicans invasion, and damage26. L. rhamnosus colonization of IECs prevented fungal outgrowth and reduced the number of host cell-associated C. albicans cells through shedding26. Similarly, L. rhamnosus colonization in an intestine-on-chip-model reduced the fungal burden, epithelial damage, and fungal translocation into a surrogate bloodstream compartment27.L. rhamnosus colonization against C. albicans pathogenicity remain, to a large extent, unresolved. Several antagonistic mechanisms of lactobacilli have been described using models excluding host cells, such as peroxide production28 or lactic and acetic acid production29. However, these antagonistic mechanisms did not play a role in the protection of host cells26. More complex in vitro models are required to dissect the interactions between the host, lactobacilli, and C. albicans in a physiologically relevant manner to understand the principles of the observed protective activities.However, the molecular mechanisms underlying the antagonistic effects of L. rhamnosus colonization of IECs mediates protection against C. albicans infection. This included dissection of the metabolic crosstalk between epithelial cells, L. rhamnosus, and C. albicans. Using this approach, we elucidated how multifactorial changes in the metabolic environment force C. albicans transcriptional adaptation, resulting in a reduced capacity to damage epithelial cells.In this work, we took a systems-biology approach involving multi-omics (transcriptome/metabolome) profiling, in silico metabolic modelling, and in vitro infection biology to uncover how L. rhamnosus reduced the number of C. albicans cells in contact with IECs26, which may reduce invasion and damage of the tissue. Infections with a lower number of C. albicans cells also resulted in a reduced fungal burden in the tissue after infection . Killing L. rhamnosus after colonization still abolished their protective effect  unless IECs are present, yet active growth is essential for their antagonistic potential 30, IEC supernatants were predicted to sustain an increased bacterial biomass, while the culture medium (KBM) did not , lipid-related metabolism, and Coenzyme A (CoA) synthesis. In addition, diverse amino-acid metabolic pathways showed differing feasible flux ranges in response to IEC-derived metabolite profiles  were simulated for IECs, ns Figs. ; S3. Theles Fig. . In comples Fig. . Here, oL. rhamnosus-mediated protection against C. albicans cytotoxicity is contact-independent 37, and 3-hydroxyoctanoate38, have previously been reported to have antifungal potential. We validated the effects of phenyllactic acid and 2-hydroxyisocaproic acid, and observed that these metabolites changed the pH of the medium. Nevertheless, compared to pH-adjusted medium, an impact on C. albicans filamentation was still observed. Further screening of the L. rhamnosus colonization-derived metabolites revealed several additional metabolites that differentially influenced C. albicans filamentous growth  enrichment analysis revealed that a variety of metabolic processes were down-regulated at 6 hpi, while the opposite was observed at 24 hpi Fig. . As the MIG1 and TYE7 were significantly up-regulated at 6 hpi, possibly to compete for any remaining favoured carbohydrates. Nevertheless, at 24 hpi MIG1 and TYE7 as well as GAL4, SUC1, HMO1, and STD1 were significantly down-regulated. Despite increased expression of MIG1 and TYE7 early during infection, genes encoding major glycolysis enzymes such as PFK1 were down-regulated during the entire infection , genes in the glyoxylate shunt , and genes in the gluconeogenesis pathway  were up-regulated at 6 hpi  was investigated60. Both genes were down-regulated at later time points in our model.Several studies suggest that C. albicans. However, when more than one of these genes are not expressed C. albicans loses its metabolic flexibility, which is associated with reduced pathogenicity. In line with this, a closer look at the carbohydrate catabolism revealed the down-regulation of glycolysis-relevant genes and an up-regulation of several TCA cycle and glyoxylate shunt genes starting at 6 h. Interestingly, this matches the metabolic phenotype of ace2Δ/Δ64. However, the ace2Δ/Δ mutant has a large cell morphology defect64, which is associated with attenuated virulence63. Nevertheless, the phenotype of this mutant suggests that transcription factors like Ace2 affect both virulence as well as metabolism.Based on this, we believe that individual deletion or down-regulation of these metabolic transcription factors can be compensated by redundancy, which secures a high level of metabolic flexibility for L. rhamnosus colonization, such as ADH1 or COX2. Impaired oxidative phosphorylation could limit ATP production, which may reduce fungal growth, filamentation, and virulence. A link between respiration and fungal pathogenesis has been described65 and specific correlations between C. albicans oxidative phosphorylation and pathogenicity mediated by ADH1 have been observed66.Several genes of the oxidative phosphorylation pathway were supressed upon C. albicans virulence was validated using deletion mutants. Deletion mutants of the genes PTP3, AHR1, ACE2, and orf19.4292, which are down-regulated during infection of L. rhamnosus-colonized IECs, exhibited an attenuated damage potential. Moreover, ptp3Δ/Δ was compromised in growth and filamentation. PTP3 encodes a protein tyrosine phosphatase required for hyphal maintenance67. The transcription factor Ahr1 regulates the virulence genes ALS3 and ECE168, but can also repress the white-to-opaque switch69. Orf19.4292 encodes the prevacuolar trafficking protein Pep12, which is essential for virulence in mice70. The transcriptional regulator Ace2 regulates glycostress metabolism64 and its role in virulence is discussed above. Our data underscores that down-regulation of each of these genes could be sufficient to reduce pathogenicity. This supports the notion that C. albicans metabolic and transcriptional adaptations upon infection of L. rhamnosus-colonized IECs are intertwined with pathogenic potential.The impact of transcriptional changes on C. albicans gene expression induced by lactobacilli. During oral epithelium infection, C.albicans-induced expression of genes associated with diverse metabolic pathways71. L. plantarum, L. helveticus, and L. crispatus also down-regulated hypha-associated genes (HAGs)73. As the majority of HAGs were not affected in our dataset, we hypothesize that niche-specific modes of action exist for the diverse Lactobacillus species.Other studies also observed changes in the L. rhamnosus colonization is a multifactorial process that synergistically affects C. albicans growth and pathogenicity. Different aspects of this complex interaction have been individually assessed in the past. Here we provide a multilevel comprehensive picture of the interplay between C. albicans and its antagonist L. rhamnosus in a human, gut-like experimental setup. The metabolic and transcriptional insights into the antagonistic potential of a single member of the microbiota underline the importance and complexity of a balanced intestinal microbiota that keeps C. albicans in its commensal state.Collectively, our results demonstrate that protection by C. albicans pathogenicity can be controlled or prevented.Our combined metabolome data, in silico metabolic modelling, transcriptome and mutant screening, as well as in vitro validations, provide fundamental, contextualized insights into how C. albicans-infection model was used to perform the experiments as previously described26. C2BBe1 (ATCC CRL-2102) and HT29-MTX  cells were seeded in collagen I coated  6-well, 24-well or 96-well plates at a ratio of 70:30 with a total cell density of 4 × 105 cells/well (6-well), 1 × 105 cells/well (24-well) and 2 × 104 cells/well . Cells were used for experiments after 14 days of differentiation in Dulbecco’s Modified Eagle’s Medium  supplemented with 10% foetal calf serum , 10 µg/ml Holotransferrin , and 1% non-essential amino acids  with medium exchange three times per week. Cell lines have been authenticated via commercial STR profiling on November 29, 2019 (Eurofins Genomic) and checked for mycoplasma contaminations using a PCR mycoplasma test kit (PromoKine) according to the manufacturer’s instructions.An in vitro intestinal Lactobacillus rhamnosus ATCC 7469 (OD 0.2 in KBM) for 18 h prior to infection. For contact-independent colonization, DMEM was exchanged for 600 µl in the bottom of a 24-well plate and a transwell insert with 125 µl L. rhamnosus (OD 0.4 in KBM) was placed on top.For colonization, DMEM was exchanged for 1.3 ml (6-well) or 50 µl (96-well) serum-free Keratinocyte Basal Medium (KBM)  and monolayers were colonized with 1.3 ml (6-well), 250 µl (24-well) or 50 µl (96-well) C. albicans WT SC5314 (4 × 105 cells/ml in KBM). For the samples with antibiotic treatment, 500 µg/ml Gentamicin (Merck) and 1× PenStrep  were added 4 hpi. For infection in presence of metabolites, a solution of each metabolite in KBM was prepared fresh and sterile filtered. Then, concentration was adjusted and 50 µl  of this solution with C. albicans (MOI 1) were used to infect the cells for 24 h. Wells with only medium, L. rhamnosus, or C. albicans in the presence or absence of the host cells served as controls. Infected cells and controls were incubated at 37 °C with 5% CO2. Data from in vitro damage, fungal burden, and translocation assays were analysed using GraphPad prism version 8. Data from at least 3 biological replicates were analysed for statistical significance using a t-test or a one-way ANOVA with multiple comparisons. Statistical significance is depicted in the figures: * = p ≤ 0.05, ** = p ≤ 0.01, or *** = p ≤ 0.001.Fungal infection was performed with 1.3 ml (6-well), 250 µl (24-well) or 50 µl (96-well) C. albicans cells were present 24 hpi, CFU quantification was performed in 96-well plates. Supernatants were collected and IECs were treated for 5 min with 0.2% Triton-X-100 (Sigma-Aldrich) to lyse the host cells and release adherent fungal cells. After detaching adherent host cells via scraping with a pipette tip, the lysate was added to the respective supernatant. Wells were washed twice with PBS. The final samples were diluted appropriately with PBS and plated on YPD agar with 1× PenStrep  and incubated at 30 °C until adequate growth for CFU counting was reached (24 h).To determine how many 74 . All results across all mentioned clusters are presented and significant hits are indicated. FDR correction was done per cluster and time point, and FDR ≤ 0.1 was considered. Proportional Euler diagrams were done using the R package “eulerr”79.Raw metabolome data was rescaled to set the median equal to 1, and the missing values imputed with the minimum. Data were loaded in R version 1.2.5019L. rhamnosus was cultured in MRS Broth for 48 h at 37 °C with 5% CO2 and 1% O2. Afterwards, cells were washed, and 3000 cells/ml were inoculated in the different media and IECs were colonized. At 0, 24, and 48 h independent wells were resuspended, and the content was appropriately diluted and plated on MRS agar. Plates were incubated for 48 h at 37 °C with 5% CO2 and 1% O2 until CFU quantification. Tested metabolites are shown in Table C. albicans (1 × 104 cell/ml) in KBM with or without supplementation of individual metabolites or in combination was incubated for 24 h at 37 °C with 5% CO2 inside the Cell Discoverer 7 microscope (Zeiss), in which a bright field picture was taken every hour, images were exported with Zeiss Zen3.1 (blue edition). Hyphal length was measured at 4 h images using Zeiss Zen3.1 (blue edition) Table 2. Afterwards, samples were diluted in PBS, plated on YPD agar, and incubated at 30 °C for 24 h.To determine translocation through the epithelial barrier, infections were performed in transwell inserts (Sarstedt) with a pore size of 5 µm. 24 hpi, zymolyase (260 U/ml) was added to the bottom compartment and incubated for 2 h at 37 °C with 5% COC. albicans infection in 6-well plates, RNA isolation of C. albicans was performed  and RNA quality was verified with an Agilent 2100 Bioanalyzer (Agilent Technologies). RNA was subsequently converted into Cy5-labeled cRNA  using a QuickAmp labelling kit (Agilent). Samples were co-hybridized with a common Cy3-labeled reference  on Agilent arrays (C.a.: AMADID 026869), scanned in a GenePix 4200AL with GenePix Pro 6.1 . Differentially expressed genes (DEGs)  were analysed with GeneSpring 14.9 (Agilent) and the Candida Genome Database . Out of the 6130 C. albicans genes, 5125 genes were used for the analysis after filtering on the minimal fluorescent signal and subtraction of the background signal. Genes were considered differentially regulated when they had a moderated T-test, Bonferroni-corrected p-value of <0.05 and a Log2 fold change of more than 1 or less than −1.After 6 and 24 h of med Fig. . At the 75, rows were normalized and Euclidian distances were calculated. The heatmap was generated with the “pHeatmap” package v1.0.1276 and the distance matrix was subjected to hierarchical cluster analysis using the complete linkage agglomeration method. Colour bars indicating condition were added to the dendrograms using the R package “dendextend” v 1.15.277. The PCA was calculated using the R function “prcomp”. Graphs were generated using the “ggbiplot” package v 0.5582. Proportional Euler diagrams of the DEGs were done using the R package “eulerr”79 and “eulerAPE”83.Gene expression data were exported from GeneSpring and loaded in R version 3.6.2Candida genome database84, which uses a hypergeometric distribution with Multiple Hypothesis Correction (Bonferroni Correction) to calculate p-values. Subsequently, the significantly enriched GO-terms were processed using REVIGO85 (similarity: Tiny (0.4); database: whole Uniprot; semantic similarity measure: SimRel) to remove overlapping and redundant GO-terms.GO term enrichment of differentially expressed genes was analysed using the GO-Term Finder on the C. albicans, human, and L. rhamnosus metabolism were used to simulate and analyse different growth scenarios in silico. Specifically, the recently published model for C. albicans39 was downloaded from the supplementary material of the publication. The GEMs for Lactobacillus rhamnosus LMS2-1 for L. rhamnosus32, and Recon3D 3.0131, a comprehensive generic GEM of human metabolism used to simulate human intestinal epithelial cells, were downloaded from www.vmh.life. Metabolomics data were used to modulate feasible nutrition uptake for each model via respective exchange reactions as defined by each GEM. Feasible uptake rates for available metabolites were adapted from the metabolome measurements across all investigated conditions. Feasible uptake flux ranges for each metabolite in our GEMs were kept in the range  mmol/g(DW)h. The metabolite concentrations for each sample were transformed into this range based on the metabolite glutamine showing the highest concentration in the 12 hpi L. rhamnosus supernatant compared to all measured metabolites and all samples. The uptake rate of glutamine was set to 1000 mmol/g(DW)h accordingly, whereas all others were set to the respective proportion to the maximum glutamine value. The biomass function of each GEM was used as objective function for all metabolic modelling simulations. To obtain objective function values mimicking an anaerobic environment (oxygen influx prohibited) as well as feasible reaction flux ranges supporting at least 90% of the objective function flux, we applied flux balance analysis (FBA) and flux variability analysis (FVA) across all tested conditions for all tested GEMs33. All GEM analyses were done in COBRApy86 using Python 3.6.4 and the IBM ILOG CPLEX Optimizer (version 12.8).GEMs for L. rhamnosus-conditioned supernatants, a culture of L. rhamnosus was washed and adjusted to an OD600 of 0.2 in KBM, and 1 ml was used to colonize a confluent layer of differentiated intestinal epithelial cells  for 24 h . L. rhamnosus was also adjusted to an OD600 of 0.2 in KBM +  and incubated in a 24-well plate independently of host cells for 24 h . After 24 h, conditioned media were filtered. C. albicans was washed and adjusted to a concentration of 1 × 105 or 1 × 106 cell/ml in the different media and incubated in a 96-well plate for 1 h . After that time, the plate was centrifuged and supernatants were exchanged with XTT reagent . The plate was then incubated for 2 h at 37 °C. Afterwards, 100 µl of the supernatants were transferred to a new plate and absorbance at 492 nm measured.To obtain the To compare XTT absorbance to biomass, a crystal violet assay was performed afterwards. The supernatant from each well was removed and the plate was left to air dry. Afterwards, 150 µl crystal violet 1% (Sigma) was added. After 45 min incubation at room temperature, crystal violet was removed, and the wells were washed three times with distilled water. Crystal violet was then solubilized with 200 µl ethanol 99% for 45 min. Afterwards, 100 µl of the supernatants were transferred to a new plate and absorbance was measured at 550 nm .C. albicans concentration was 1 × 104 cell/ml.The same procedure was used to assess the effect of the metabolites in the mitochondrial activity, except the preincubation with the metabolite was done for 24 h prior to the XTT assay and the initial C. albicans mutants from the deletion mutant library40 . Damage was measured via the LDH activity assay (see Quantification of cytotoxicity (LDH)). Positive hits were validated with additional damage experiments where the mutants were cultivated in YPD broth in 25 ml Erlenmeyer flasks overnight at 30 °C with shaking at 180 rpm. Fungal cells where then washed in PBS, counted, and adjusted to a concentration of 4 × 105 cells/ml in KBM. The epithelial cell monolayer was infected with 50 µl  or 250 µl (24-well). For growth curves, the diluted overnight cultures were diluted 1:2 in KBM in 96-well plates and incubated for 24 h at 37 °C with 5% CO2 in a microplate reader . Growth was monitored with OD600 measurements every 30 min over 24 h. Data was analysed using Graphpad prism version 8. Data from at least 3 biological replicates was analysed for statistical significance using a one-way ANOVA with multiple comparisons.y40 Tab.  were culFurther information on research design is available in the Supplementary InformationReporting SummaryPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Movie 1: CytosineSupplementary Movie 2: Control


The increasing environmental protection demand has prompted the development of passive thermal regulation systems that reduce temperature fluctuations in buildings. Here, it is demonstrated that the heat generated by the sun can trigger a spin crossover (SCO) in a molecule‐base material, resulting in a concomitant color variation (from pink to white) and a phase transition. This leads to a cooling effect with respect to other thermochromic materials. In addition, when the material is cooled, a dampening of the temperature decrease is produced. Therefore, these materials can potentially be implemented for passive temperature control in buildings. Furthermore, SCO materials are remarkably stable upon cycling and highly versatile, which allows for the design of compounds with properties tailored for the desired climatic conditions and comfortable temperature. The heat produced by the sun can induce a spin transition in a spin‐crossover material, leading to a color change coupled with the absorption/release of energy, which results in a cooling effect at high temperatures and a dampening of the temperature decrease at low temperatures. Hence, these materials can potentially be applied for passive temperature control in buildings. These CO2 emissions are a major contributor to climate change, which has become one of the biggest concerns of humankind. A reduction in emissions could be achieved by eliminating coal, oil, and natural gas as sources of building heating, and by reducing the energy consumption derived from the use of air conditioning systems. Thus, the growing energy‐saving demand and environmental protection have prompted the development and implementation of more energy‐efficient and environmentally friendly thermalization technology. In this regard, remarkable efforts have been focused on the implementation of passive thermal regulation systems, that can be incorporated directly into windows, roofs, or walls of buildings and operate without the need for electricity.Nowadays, building thermalization is a widespread human necessity, accounting for 30% of the total final energy use and 28% of energy‐related carbon dioxide , which present high‐density thermal energy storage, therefore minimizing temperature fluctuations through the use of latent heat.Although to keep buildings cool the light absorption and reflection properties have been used for millennia, nowadays more sophisticated approaches are being explored for passive thermal regulation of buildings. The first one is based on the so‐called radiative cooling technique, in which a surface is naturally cooled by reflecting sunlight and radiating heat to the cold outer space.17 The require different materials to reduce temperature fluctuations in both directions. Therefore, certain PCMs are so far applied for thermal regulation in both senses, although they display some limitations. Nevertheless, from a global warming perspective, the need to reduce temperature fluctuations calls for the development of new materials and/or novel alternative approaches to tackle this problem in a more effective manner.Employing the first two approaches, subambient cooling was achieved both during the day and night. While this is interesting for places where the weather is hot throughout the whole day, certain regions of the world, with climates where high temperatures are reached during the day and low temperatures at night, for example, New Delhi,28 req coupled with the release/absorption of energy associated with a phase transition. One can easily imagine the advantage in thermal efficiency for buildings with a coating that changes color from a clear, reflecting color in summer to a darker, absorbing color in winter, or even in shorter day/night cycles since they could also dampen thermal fluctuations as a consequence of the phase change.In this respect, a new strategy could be the use of materials that combine two of the principles mentioned before by switching between multiple phases that display distinct thermo‐induced optical properties, resulting in different light reflections,33 cou These materials undergo a spin transition between two electronic states, low spin (LS) and high spin (HS) upon external stimuli, including temperature variation. This spin transition is associated with a color change, which could result in a different capacity for reflecting sunlight  compounds.40 The as well as the use of SCO materials as thermal protective barriers in microelectronic circuits and in buildings. However, these ideas consisted of the use of latent heat associated with the SCO, in contrast to the present work, in which we consider primarily the role of thermochromic properties. The key advantage in the use of these switchable materials is that the appropriate selection of a SCO material could result in effective passive temperature control in circumstances where large temperature fluctuations need to be avoided . Moreover, the remarkable versatility of SCO compounds may allow adapting the desired phase change temperature and hysteresis to the climatic conditions and the desired comfort temperature. Therefore, the objective of this work is to give a proof‐of‐concept of this idea by demonstrating, in the first place, that the heat generated by the solar radiation is enough to produce a spin transition in an SCO material and, second, that the use of this material allows, in both heating and cooling, to reduce temperature fluctuations.The application of SCO materials for thermal management purposes has been considered recently in different contexts. In particular, there have been a few reports about possible barocaloric refrigeration applications46 as 22trz)3](OTs)2 (1), [Fe(Htrz)2(trz)[(BF4) (2) and [Zn(NH2trz)3](NO3)2 (3) have been synthesized, where NH2trz = 4‐Amino‐4H‐1,2,4‐triazole; OTs = p‐toluenesulfonate; Htrz = 1,2,4‐Triazole and trz = 1,2,4‐triazolate. These materials present the widely studied structure of the family of the triazole‐based SCO coordination polymers  is used as the metal center, these materials can exhibit SCO properties. Of particular interest for this work is that compound 1 displays this spin transition around room temperature (RT). To investigate and compare the temperature control ability of 1, two different compounds , from here on 1@PMMA, 2@PMMA, and 3@PMMA, respectively  is a d10 transition metal, and the possibility of SCO is nonexistent. All these materials were further characterized by Fourier‐transform infrared spectroscopy (FTIR), powder X‐ray diffraction (PXRD), and thermal gravimetric analysis (TGA) . This configuration mimics the temperature in a closed room. This process was recorded with an infrared thermal camera, so that the temperature inside the vials and in the polymer could be characterized over time, visualizing their thermal gradients.In order to simulate temperature fluctuations in a room, two different experiments were devised. The first one , a temperature inside the vial (T2), and two temperatures underneath the vial: one inside the vial (T3) and another outside (T4).The recorded infrared thermal images can be seen in Figure 1, top graph) shows that 2@PMMA increases from 24 to 41.6 °C (ΔT = 17.6 °C). Therefore, starting from roughly the same temperature, the 2@PMMA temperature increases 8 °C more than that of 1@PMMA (ΔT = 10 °C), and 16 °C more than in 3@PMMA and PMMA (ΔT = 1.3 °C). The rate at which the temperature increases in the first 2 min is as follows: 1@PMMA 4 °C min−1, 2@PMMA 8 °C min−1, 3@PMMA 0.5 °C min−1, and PMMA 0.4°C min−1. Upon examination of T2, it can be seen that in all cases, an increase in temperature is observed as the irradiation time progresses, although in 3@PMMA and PMMA the temperature rises significantly less than in the other two. For compounds 1@PMMA and 2@PMMA, the temperature increases with time in a similar manner, up to 50 s, where the two plots diverge and 2@PMMA heats up more than the SCO sample. More precisely, the temperature in 2@PMMA increases by 14.4%, and by 10.2% for 1@PMMA, which means a slight control in temperature was achieved.The sample temperature . The composite temperature is recorded with an infrared thermal camera, and the sensor temperature using a thermocouple.The second setup . Immediately, both Again, the system is set in heating mode and the same behavior as in the first cycle is observed: 2@PMMA and 3@PMMA reach higher temperatures than 1@PMMA and the highest temperature is reached when no sample is used. These experiments were repeated, and the same result was obtained  ions (at −2 °C) to 88% of HS at the highest temperature (29.6 °C). This translates into fewer temperature fluctuations during both cooling and heating. The control at high temperatures can be associated with the synergy between thermochromism and phase change. The control in the low‐temperature region is believed to be due to the energy release associated with the spin transition, with typical ΔTtarget (25 °C) is reached more slowly for 1@PMMA when in comparison with the references . When no sample is used, the minimum Ttarget recorded is 29 °C. This result reinforces the conclusion that the material exhibiting SCO is capable of reducing temperature fluctuations and providing certain control over the temperature.In addition, to simulate what would occur upon a temperature decrease under solar irradiation, this same setup was used but, in this case, the solar lamp remains lit during the entire experiment, accompanied by Peltier on‐off cycles , a dampening of the temperature decrease is produced. This is believed to be due to the energy release associated with the spin transition. Here, the material also regains its initial behavior and can be employed again to control fluctuations at increasing temperatures. Therefore, this type of material can be used to reduce temperature fluctuations, which could potentially be implemented for passive temperature control in buildings, by combining selective light reflection and phase‐change materials. SCO molecule‐based materials are remarkably stable upon cycling and highly versatile, which may allow for the design of compounds adapting the intended properties (transition temperature and hysteresis) for the climatic conditions and the desired comfort temperature.42trz  in 3 mL of ethanol on top of a solution of 0.20 mmol of Fe(OTs)2 (OTs = tosylate) in 3 mL of distilled water. The solution was stirred for 1 h, filtered, and washed with ethanol. 1 was obtained as a pink powder in 87% yield.Compound 1 was synthesized at room temperature, by adding drop by drop to a solution of 0.59 mmol of NH2O: C 36.53%, H 4.11%, N 25.56%; found C 36.34%, H 4.05%, N 25.79%.Anal. calcd for 1 0.4H−1): ν = 3441 ), 3293 ), 3210 (w), 3062 ar), 3012 (w), 2924 (w), 1631 (m), 1600 (w), 1546 ), 1496 (w), 1449 ar), 1396 (w), 1170 OTs), 1122 (s), 1098 (m), 1033 OTs), 1008 OTs), 908 (w), 881 (w), 813 ), 709 (w), 681 OTs), 623 (s), 563 OTs), 493 (w), 457 (w).FTIR 1 (cm4)2 6H2O in 3 mL of distilled water and adding it drop by drop to a solution of 3 mmol of Htrz  in 3 mL of ethanol. The resulting solution was stirred for 24 h, filtered, and washed with ethanol obtaining 2 as a pink powder (76% yield).Compound 2 was synthesized at room temperature, dissolving 1 mmol of Fe: ν = 3170 ), 3093 ar), 3008 (w), 2915 (w), 2845 (w), 2698 (w), 2621 (w), 2535 (w), 2535 (w), 2457 (w), 1749 (w), 1719 (w),1639 (w), 1535 ), 1495 (m), 1453 ar), 1309 (m), 1285(m), 1220 (w), 1190 (w), 1163 (m), 1144 (m), 1063 BF4), 1034 BF4), 977 (m), 912 (w), 866 (m), 827 (w), 765 (w), 679 (m), 631 (s), 523 (m), 468 (w), 437(w).FTIR 2  in 3 mL of ethanol on top of a solution of 1 mmol of Zn(NO3)2 in 3 mL of distilled water. The solution was stirred for 1 h, and the white precipitate was filtered and washed with ethanol. 3 was obtained as a white powder (85% yield).Compound 3 was synthetized at room temperature, by adding drop by drop to a solution of 3 mmol of NH2O: C 15.68, H 3.07, N 42.66; found C 15.33, H 3.14, N 43.01.Anal. calcd for 3·1H−1): ν = 3520 (w), 3319 ), 3218 (w), 3070 ar), 3004 (w), 1753 (w), 1632 as,NO3), 1547 ), 1485 ar), 1339 sim,NO3), 1219 (m), 1088 (m), 1030 (m), 996 (m), 904 (w), 828 trans/cis,NO3), 712 (w), 690 (w), 622 (s), 421 (w).FTIR 3 (cmw ≈120 000 g mol−1). This mixture was dissolved in CHCl3, sonicated for 30 min, and deposited in a mold (5 cm × 5 cm), that was placed in the fridge overnight so the CHCl3 evaporates slowly and no bubbles appear. The composite was then carefully extracted from the mold.The 1@PMMA, 2@PMMA, and 3@PMMA films (3% w/w) were prepared by mixing 0.2 g of the respective sample powder with 1.98 g of PMMA : ν = 3290 ), 3110 ar), 2995 , 2950 , 2851 (w), 1724 , 1614 (w), 1546 ), 1480 , 1446 , 1435 (m), 1386 , 1269 , 1239 , 1189 , 1169 OTs), 1146 , 1122 (s), 1098 (w), 1033 OTs), 1009 OTs), 988 , 966 , 912 , 880 (w), 841 , 812 , 749 , 683 OTs), 625 (s), 563 OTs), 481 .FTIR 1@PMMA (cm−1): ν = 3170 ), 3095 ar), 3006 (m), 2915 (m), 2848 (m), 2748 (w), 2698 (w), 2622 (w), 2536 (w), 1728 , 1644 (w), 1536 ), 1496 (m), 1453 (m), 1388 (w), 1309 (m), 1284 (w), 1221 , 1190 , 1162 (m), 1144 (m), 1109 (w), 1063 BF4), 1034 BF4), 977 (m), 912 (w), 866 (m), 826 , 764 , 679 (m), 631 (s), 524 (m), 482 , 471 (w), 437 (w).FTIR 2@PMMA (cm−1): ν = 3321 ), 3219 (w), 3070 ar), 2998 , 2950 , 2844 (w), 1721 , 1635 as,NO3), 1547 ), 1481 , 1434 , 1363 sim,NO3), 1269 , 1238 , 1190 , 1143 , 1088 (m), 1062 , 1029 (w), 993 (m), 968 , 913 (w), 842 , 828 trans/cis,NO3), 748 , 667 , 623 (m), 554 , 479 , 458 (w).It should be noted that at temperatures above 125 °C the PMMA started degrading, so 2@PMMA, whichundergoes the spin transition at higher temperatures, could not be characterized in HS by SQUID and only partially by optical reflectivity. FTIR 3@PMMA  analyzed under the ImageJ program. The temperature was controlled using a Linkam T95 system controller and a LNP 95 Liquid Nitrogen Cooling System.−1 under air from 30 to 600 °C.Thermogravimetric analyses performed using a TA Instrument TGAQ500 with a ramp of 2 °C min−1 on a Bruker Tensor 27 (ATR device) Spectrometer.FT‐IR spectra recorded as neat samples in the range 400–4000 cmElemental analyses were performed on a LECO CHNS‐932 Analyzer at the “Servicio Interdepartamental de Investigación (SIdI)” at Autónoma University of Madrid.−1. Each sample was secured inside a plastic capsule. Pascal constants were used to correct the diamagnetic contribution.Magnetic susceptibility measurements carried out in a Quantum Design MPMS‐5S SQUID magnetometer under a 10 000 Oe field at a rate of 1 °C minα radiation (λ = 0.1541 nm). The samples were measured between 5° and 50° with a speed of 1.8° min−1 under an X‐Ray fluorescence reduction mode, at room temperature.Powder X‐ray diffraction collected in a Rigaku Smartlab SE diffractometer with a Bragg‐Brentano configuration, using Cu‐K−1. The temperature dependence experiments were performed using the Linkam T95 system controller and a LNP 95 Liquid Nitrogen Cooling System.Absorption spectra measured with a CCS200 – Compact Spectrometer between 1000–400 cm−2) simulated sunlight.Thermo‐optic analyses performed using a VeraSol LED solar simulator (Newport) producing 1 sun AM 1G  . Measurements were performed several times to ensure reproducibility. Each measurement was conducted for 10 min till thermal equilibrium (or steady‐state temperature) was reached ±2% of the reading.A RS41 Digital Thermometer (±0.5% of reading) was employed to measure the target temperature in the second experimental setup.The authors declare no conflict of interest.Supporting InformationClick here for additional data file.


Soil bacterial abundance indices  differed significantly along the elevation gradient, whereas the Shannon index remained unchanged. Principal Coordinates Analysis indicated separated soil bacterial communities of the different elevations. The dominant phyla in all soil samples were Proteobacteria, Acidobacteria, Actinobacteria, Verrucomicrobia, and Bacteroidetes, which in combination reached 80%–85%. Soil pH to some extend related to soil bacterial community along altitude gradations. The relative abundance of a multiple phyla was negatively affected by the soil nutrients, such as ammonium and nitrate nitrogen, available potassium, soil moisture content, available phosphorus, microbial biomass nitrogen and soil organic C. The strongest effects were seen for Proteobacteria. The pH either positively or negatively correlated with specific genera. The soil bacterial function differed significantly among four elevations. The chemoheterotrophy, aerobic chemoheterotrophy and nitrification were the most dominant functions of soil bacteria among four elevations. Overall, the changes in soil physicochemical properties with elevation are important in shaping the bacterial diversity, composition and function in soil with the same above-ground vegetation of Changbai Mountains.Soil bacteria play important roles in biogeochemical cycling and biodiversity in mountain ecosystems. Past studies have investigated the bacterial community composition and diversity in elevation gradations covered by different vegetation types, but for a better assessment of elevation effects, here we studied bacterial communities in soil under identical vegetation cover. High-throughput amplicon sequencing of the V3-V4 region of bacterial 16S rDNA was used to investigate the diversity and composition bacterial communities in soil from 700 to 1,000 m above sea level collected on the north slope of Changbai Mountains, Northeast China. Obviously differences ( Soil bacteria are an important component of the soil microbiota and play crucial roles in regulating ecological functions such as litter decomposition, biogeochemical cycling, and maintaining biodiversity . Since bBacterial community composition significantly corresponds to vegetation and habitat selection , and theThe Changbai Mountains in the northeast of China represent an area with rich and well-preserved subtropical biodiversity gene pools at the same latitude. The area is sensitive to climate changes and is a current hotspot for research . SeveralTilia amurensis Rupr. is dominant at a wide altitude distribution on the northern slopes of Changbai Mountains (T. amurensis). The questions addressed were: (1) How do the soil bacterial community characteristics  change along an altitudinal gradient under the same vegetation? (2) What are the driving factors for the elevational distribution patterns of soil bacterial community characteristics? In order to solve above questions, the high-throughput sequencing technology was applied to analyze the structural composition, diversity and function of soil bacterial communities from 700 m to 1,000 m under an identical trees . The results contribute to a better understanding of the bacterial diversity in soil and the ecological roles of bacterial communities, and assist in elucidating the driving factors shaping soil bacterial communities related to elevation in Changbai Mountains.The deciduous tree ountains . It is aThis study location is within the Changbai Mountain Nature Reserve  in Jilin Province, northeast of China, which belongs to a typical temperate climate with cold winters and warm summers. The average annual temperature is 4.3°C, and the average annual precipitation is 745 mm. The growing season lasts from May to September. The soil is dark brown soil developed from volcanic ash.Pinus koraiensis, Acer mono, Tilia amurensis, Fraxinus mandshurica, Quercus mongolica, Populus ussuriensis. The dominant vegetations of 800 m were P. koraiensis, Betula platyphylla, T. amurensis, F. mandshurica, Abies nephrolepis, Phellodendron amurense, Picea koraiensis. The dominant vegetations of 800 m were P. koraiensis, T. amurensis, Q. mongolica, A. nephrolepis, P. jezoensis, A. mandshuricum, A. mono, Ulmus laciniata, Larix gmelinii, B. costata, P. davidiana. The dominant vegetations of 800 m were P. koraiensis, P. jezoensis, A. nephrolepis, A. mono, T. amurensis, F. mandshurica, P. cathayana, L. gmelinii, A. tegmentosum. For each elevation the above-ground vegetation was inspected and five plots were identified per elevation that all contained the same vegetation (T. amurensis). In October 2017, soil samples were collected at a depth of 0–20 cm with an 8 cm diameter soil auger from 10 to 15 locations along an S-shaped path. After that, the soils (10–15 soil samples) were mixed into one sample. Therefore, we finally had 5 mixed soil samples in each elevation. After removal of the surface litter and humus layer, the sampled soil sample was mixed per plot. Plant rests and coarse material was removed and the soil was homogenized and sieved through 2 mm meshes before transfer to the lab. There, the samples were divided into two parts; one was stored in the −80°C for soil microbial analysis and the other was air-dried for soil physicochemical properties analysis.Four elevations were selected: 700, 800, 900, and 1,000 m above sea level, located on a north slope of Changbai Mountains. The GPS position of each elevation showed in 4+-N and NO3−-N were extracted with 2 mol·L−1 KCl (Soil moisture content (SMC) was determined by weight loss following desiccation. The soil organic carbon (SOC) and total nitrogen (TN) contents were determined using an elemental analyzer . The total phosphorous (TP) content was determined by the digestion method of concentrated sulfuric acid and perchloric acid treatment , and NH4·L−1 KCl  and meas·L−1 KCl . TK, AK −1 dNTPs, 1.0 μl each of 5 μmol·L−1 upstream primer 338F and downstream primer 806R, 0.4 μl FastPfu polymerase, 0.2 μl BSA, and 20 ng DNA template. The amplification protocol was 95°C for 5 min, followed by 33 cycles with 30s at 95°C, 20s at 55°C, and 45 s at 72°C and final extension of 10 min at 72°C. Triplicate amplification products of the same sample were mixed and checked by electrophoresis on a 2% agarose gel, excised and were recovered with a TAKARA DNA Gel Extraction kit . The purified amplicons were subjected to high-throughput sequencing using the Illumina MiSeq platform. The high-throughput sequencing was performed by the Biomarker Technologies Company (Beijing China).Total DNA was extracted from the soil with an E.Z.N.A.™ Soil DNA kit . The V3-V4 region of the bacterial 16S rDNA gene was amplified by PCR using bacterial universal primers 338F (5′-ACT CCT ACG GGA GGC AGC A-3′) and 806R  software on the Biomaker bioinformation cloud platform.https://www.drive5.com/usearch/). Exact barcode matching was implemented, which allowed for a two-nucleotide mismatch during primer matching. Operational taxonomic units (OTU) were generated at a similarity level of 97% for which the RDP  classifier Bayesian algorithm was used  at different altitudes for soil pH (range: 5.48–6.15), and contents of TK (2.74–4.21 g·kg−1), TP (0.05–0.8 g·kg−1), AP (9.74–16.12 mg·kg−1), and SOC (10.77–17.31 g·kg−1). Other physical and chemical properties were significantly different (p < 0.05). A relatively wide range was observed for NH4+ (18.48–59.96 mg·kg−1) and SMC (19.17%–49.08%), while NO3− (2.37–11.32 mg·kg−1), TN (11.69–33.27 g·kg−1) and AK (12.28–21.70 mg·kg−1) also significantly varied. The microbial parameters MBC also strongly varied, with a range of 55.52–510.54 mg·kg−1 for MBC and a range of 7.30–54.87 mg·kg−1 for MBN ( for MBN .p > 0.05), but the abundance indices  all varied significantly (p < 0.05). The Chao1 index showed significant differences at 900 m and 1,000 m, whereas no differences were observed at other altitudes; the ACE index was significant different at 900 m and 1,000 m, and the Richness index differed between 700 and 900 m , while the Richness, ACE and Chao1 indices were strongly negatively correlated with soil NH4+, and SMC (p < 0.01). Significant negative correlations were also observed between these three indices and MBC .The bacterial community structure along the altitudinal gradient was graphically compared by Principal Coordinates Analysis . The fivp < 0.05). The r.a. of the other phyla listed in p > 0.05).The obtained sequences were attributed to OTUs to investigate the bacterial community composition. A total of 52 bacterial phyla were identified; sequences that could not be classified to a known phylum were collectively reported as ‘others’ . The higCandidatus Solibacter, Bryobacter, Haliangium, Bradyrhizobium, Sphingomonas, Acidibacter, Reyranella, Gemmatimonas, Rhodoplanes, and Variibacter, which in combination accounted for 50% or more of the identified genera (p < 0.05) in r.a. between the altitudes was observed for the genera Variibacter, Rhodoplanes, Lysobacter, Woodsholea, Dongia, Terrimonas, Sorangium, and Nitrospira (p < 0.05).The sequences were also analyzed at the genus level . For alld genera . Ten mord genera . StatistAcidothermus for 700 m, Lysobacter for 800 m, Bauldia and Granulicella for 900 m and Rhodoplanes, Variibacter, Dongia, and Woodsholea were indicator genera for 1,000 m.A total of 52 genera were identified in the four elevations , as indip < 0.05), with differences noted at the different altitudes: strong correlations were seen at 800 m and 900 m for pH (p < 0.01) but the correlation was weaker at 1,000 m (p < 0.05) and not significant at 200 m.A Mantel analysis of soil bacterial OTU levels and environmental factors showed that pH was the main soil factor affecting the bacterial communities . The correlation patterns for the various genera of NO3−, NH4+, AK, and SMC clustered together, as did the patterns for MBC and MBN , but the dominant genera relative abundance were affected by pH, MBC, MBN, NO3, AK, and SMC. This showed that the composition of soil bacterial has different correlations with soil physicochemical parameters, which supports our 2nd hypothesis. This comprehensive study to characterize bacterial communities and their diversities at different elevations under same above-ground vegetation in Changbai Mountains revealed that the soil physiochemical characteristics have a significant effect on the overall diversity of bacterial communities along the elevation gradient, but from the available data it is difficult to predict overall bacterial diversity along elevation. Nevertheless, this study contributes to the understanding of bacterial community composition and diversity patterns at local altitudinal scales, and provides a theoretical basis for predicting the response, adaptation and feedback of microbial communities to changes in environmental conditions.Soil bacterial richness differed significantly, but Shannon diversity did not change under same above-ground vegetation in Changbai Mountains, which supports our 1The data presented in the study are deposited in the Sequence Read Archive repository, accession number PRJNA888966.ML designed and performed the experiment and prepared this manuscript. GD helped to collect the soil samples and revised this manuscript. LM designed this experiment. All authors contributed to the article and approved the submitted version.This work was supported by the Ministry of Science and Technology Fundamental Resources Investigation Project of China (2019FY100505).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.


Curcumin (Cur) has a short duration of action which limits its therapeutic efficacy. Carbonic acid 17--10,13-dimethyl-2,3,4,7,8,9,10,11,12,13,14,15,16,17-tetradecahydro-1H-cyclopenta[a]phenanthren-3-yl ester 4--2-methoxy-phenyl ester (CUD), as a small molecule derivative of Cur with superior stability, has been developed in our laboratory.CUD-loaded solid lipid nanoparticles (CUD-SLN) were prepared to prolong the duration of the drug action of Cur.in vitro release of CUD and CUD-SLN was investigated. CUD-SLN (5 mg/kg) was injected into Sprague Dawley (SD) rats to investigate its pharmacokinetic behaviour.CUD-SLN were prepared with Poloxamer 188 (F68) and hydrogenated soybean phospholipids (HSPC) as carriers, and the prescription was optimized. The in vivo by 35.6-fold, and had an improved area under the curve (AUC0–t) of 37.0-fold.CUD-SLN features high entrapment efficiency (96.8 ± 0.4%), uniform particle size (113.0 ± 0.8 nm), polydispersity index (PDI) (0.177 ± 0.007) and an appropriate drug loading capacity (6.2 ± 0.1%). Optimized CUD-SLN exhibited sustained release of CUD for about 48 h. Moreover, the results of the pharmacokinetic studies showed that, compared to Cur, CUD-SLN had a considerably prolonged half-life of 14.7 h, slowed its metabolism CUD-SLN is a promising preparation for the development of a small molecule derivative of Cur. Curcuma longa L. (Zingiberaceae), has been widely used in traditional Chinese medicine. It has been reported that Cur has several valuable pharmacological properties, including antibacterial, anti-inflammatory, antitumor and neuroprotection activities , a natural polyphenolic compound, can be found in the tuber or rhizome of in vivo stability and ameliorate the pharmacokinetic behaviour of Cur  to 7.66 h  of Cur in rats by nearly 20-fold , which are key sites for metabolism and potential sites for binding with biological macromolecules. Therefore, the PhOH groups of Cur could be modified to improve the Solid lipid nanoparticle (SLN) is a class of drug delivery system which was developed in the early 1990s -3,5-dioxo-hepta-1,6-dienyl]-2-methoxy-phenyl ester, named CUD -10,13-dimethyl-2,3,4,7,8,9,10,11,12,13,14,15,16,17-tetradecahydro-1amed CUD  , cholesteryl chloroformate (RoCL), triethylamine (TEA), isopropanol, dichloromethane (anhydrous), HSPC, Poloxamer 188 (F68) and sucrose were purchased from Luzhou Renkang Biotechnology Co., Ltd. . CUD was obtained from our laboratory.Sprague Dawley (SD) male rats aged 8 weeks weighing 250–300 g were provided by the Laboratory Animal Center of Southwest Medical University and were placed in a pathogen-free environment, and had free access to food and water. Studies involving animals were approved  2013-17) by the Ethics Committee of Southwest Medical University.UV wavelength scans of Cur and CUD from 700 to 200 nm were recorded at 25 °C using a UV spectrophotometer .CUD-SLN was prepared by using film ultrasonic dispersion technology , the input ratio of HSPC:F68 (w/w), and CUD:(HSPC + F68) (w/w) on particle size, polydispersity index (PDI) and encapsulation efficiency (EE%) of CUD-SLN were investigated by the single factor method. The specific formulations are listed in 2) comprehensively designed experiment  (A) and HSPC:F68 (B) (each factor had three levels) were arranged according to an L9  were characterized for particle size, PDI and zeta potential by a Malvern’s Zetasizer Nano ZS instrument . CUD-SLN was measured three times in a sample cell (1 mL), and the light scattering angle was set to 90°.A = 0.0495C – 0.0061, R2=0.9998). The formulas used for the calculation of the EE% and DL% were as follows:We is the amount of drug loaded in CUD-SLN, Wt is the total amount of drug in CUD-SLN and W0 is the total weight of SLN.CUD is a hydrophobic molecule. Hence, CUD-SLN with smaller particle sizes cannot form a precipitate under low-speed and medium-speed centrifugation, while the drug in the free state will be precipitated in crystal form. Therefore, to evaluate the EE%, low-speed centrifugation  was selected to separate free CUD. The same volume of SLN suspension before and after low-speed centrifugation was measured, demulsified and diluted with solvent . Lyophilized powder of SLN was accurately weighed, dissolved in methanol, and demulsified by ultrasound  to ensure the complete release of all drugs. After the sample was filtered and diluted with solvent , the concentration of CUD was determined by UV–vis spectrophotometer at 409 nm, using a standard curve  was to study the physical integrity of the drug in the SLN. The DSC thermograms of the CUD, blank-SLN and CUD-SLN were obtained by microcalorimeter . Samples were heated in the temperature range of 30–400 °C on an aluminium pan at a rate of 10 °C/min, under nitrogen atmosphere.' D/MAX-2500/PC diffract metre .X-ray diffraction (XRD) analysis was performed to monitor changes in crystallization characteristics of the drug when CUD was loaded into SLN. The XRD patterns of CUD, blank-SLN and CUD-SLN were measured using an XSolid freeze-dried nanoparticles were dissolved in ultrapure water, dripped on a slide, and a negative stain was performed with 2% phosphotungstic acid. Sample was placed on a copper grid until dried. The morphology of CUD-SLN was observed by transmission electron microscope (TEM) .in vitro was studied using a dialysis membrane diffusion technique  , namely, the Cur group and CUD-SLN group, Rats in both groups were injected intravenously with 5 mg/kg of corresponding drugs. Approximately, 200 µL of blood was collected using a heparin-coated syringe at 2, 5, 15 and 30 min and at 1, 2, 4, 6, 8, 12, 24, 30, 36, 48, 54, 60, 72 and 84 h after injection. Blood was centrifuged for 10 min at 3000 rpm, and plasma was obtained. Furthermore, 50 µL of acetate buffer (pH 3.5) was added to 100 μL of plasma. After vortexing for 1 min, 0.5 mL of extract solvent  was added to the mixture, the mixture was vortexed again for 3 min, followed by centrifugation for 3 min at 8000 rpm. Then, 0.5 mL of supernatant was removed and evaporated with nitrogen flow. Next, 200 μL of reconstituted solvent (acetonitrile contains 0.1% phosphoric acid) was added to the dry residue, vortexed for 4 min, sonicated for 4 min, and centrifuged for 10 min at 10,000 rpm, A total of 50 μL of the supernatant was removed for the high-performance liquid chromatography (HPLC)  and calculated with the standard curve  μg/mL; CUD: A = 18.159 C + 0.4884, R2=0.9998, range:  μg/mL; A = 46.552 C – 179.81, R2=0.9997, range:  μg/mL). Separation was performed on a reverse-phase C18 column  at 25 °C and a mobile phase flow rate of 1.0 mL/min. The detection wavelength was 409 nm . Fitting of the release curve was performed by Origin 8.0 software. Pharmacokinetic data were processed by DAS 2.1.1 software to obtain relevant pharmacokinetic parameters. Student’s in vivo included oxidation, reduction, glycosylation and sulphation. PhOH is the key site of glycosylation and sulphation, and significantly influences the metabolism processes and the stability of Cur in vivo. Therefore, the modification of PhOH can improve the stability of Cur in vivo. In vivo, drugs need to penetrate cell membranes to work. Cholesterol is regarded as an important component of the cell membrane. Thus, taking the active 4-OH group of Cur as the site, through covalent bonding with cholesterol, new derivatives are formed, which can improve the permeability of Cur to the cell membrane, enhance the stability of Cur in vivo, and improve the efficacy , F68 (non-ionic surfactant) and sucrose (lyoprotectant). As shown in Formulations F5–F7 showed that with the increase in the ratio HSPC:F68, the particle size decreased, but this change was not significant. The EE% increased with a decrease in the ratio HSPC:F68. When the HSPC:F68 ratio was 3:7 (F5), the EE% was the highest at 98.3 ± 2.4%. The amount of surfactant F68 may play a crucial role in stabilizing CUD-SLN; however, excessive F68 may not be induced to film formation of the lipid material, thereby reducing the EE% of the drug. Therefore, the HSPC:F68 ratio was temporarily set to 3:7 for subsequent experiments. The EE% of CUD-SLN was significantly influenced by the content of the excipients in the formula, and the particle size and PDI hardly changed with a change in the drug excipients ratio. When the drug excipients ratio was reduced from 1:7 to 1:3, no significant changes were observed in EE%. However, when the adjuvant ratio was decreased to 1:1, the EE% decreased sharply to 58.6 ± 4.9%. To obtain a higher DL% with lower excipients, a drug excipients ratio of 1:3 was used for subsequent experiments.Based on a preliminary experiment, it was found that the amount and type of lyophilized protectants had the greatest effect on particle size and PDI of CUD-SLN. In this study, sucrose was chosen as a lyophilized protectants and the results are presented in 2) comprehensive design experiments were performed to determine a stable and feasible technological formula. The results of DL% and EE% are presented in p values of 0.021 and 0.001, respectively. Moreover, factor B had no significant effect on EE% and DL% , which was consistent with the results of the intuitive analysis. Taken together, the optimal proportion of CUD, HSPC and F68 in the formulation was 11:12:21.Based on the single-factor test, two main factors affecting the quality of CUD-SLN were identified, namely HSPC:F68 (A) and CUD:(HSPC + F68) (B), and each factor has three levels. L (3p > 0.05), thus indicating that the optimized formulation method was stable and feasible.To investigate whether the optimal prescription process is stable and feasible, three batches of CUD-SLN were prepared by the optimized formulation, and the EE%, DL%, PDI, particle size and zeta potential were measured and are presented in The TEM image of CUD-SLN is shown in in vitro was studied by the dialysis membrane diffusion technique, and compared with CUD suspensions. The results are shown in in vitro, and the kinetic parameters of the release rate are shown in r2=0.9458), while the release data of CUD-SLN were fit into Higuchi’s equation (r2=0.9624), as has been reported for drug-loaded SLN systems , and was significantly increased. The clearance value of CUD-SLN in rats was 0.287 L/h/kg, which was nearly 35.67-fold lower than that of Cur (10.237 L/h/kg) (p < 0.05). In addition, the half-life (t1/2) of CUD-SLN was 14.774 h, which was about 2.64-fold that of Cur (5.6 h), and was significantly increased. Combined, these results indicated that the drug content in plasma was increased and that the existence of drugs in the systemic circulation was prolonged. This might be due to the physical and chemical properties of SLN, such as proper particle size and zeta potential, which reduced the uptake of macrophages by the mononuclear phagocytic system and increased delivery to target tissues (Li HJ et al. 0–t only increased 9.02-fold after injection, while the AUC0–t of CUD-SLN increased 37.01-fold (Feng X et al. The plasma concentration–time curves are shown in in vivo and prolonging the duration of drug action. The study offers a methodology for the pharmaceutics research of Cur or flavonoid drugs. The efficacy of CUD-SLN warrants further investigation.The purpose of this study was to prolong the duration of drug action of Cur. In this study, CUD was used as the model drug, and F68 and HSPC were chosen as carriers to develop CUD-SLN. The results indicated that CUD-SLN has satisfactory solubility, release behaviour and pharmacokinetic behaviour. Therefore, CUD-SLN is a promising preparation for Cur in improving the stability


To investigate the value of intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) to discriminate spinal metastasis from tuberculous spondylitis.slow, ADCfast, and f), and the stretched-exponential model parameters (distributed diffusion coefficient (DDC) and α), were acquired. Receiver operating characteristic (ROC) and the area under the ROC curve (AUC) analysis was used to evaluate the diagnostic performance. Each parameter was substituted into a logistic regression model to determine the meaningful parameters, and the combined diagnostic performance was evaluated.This study included 50 patients with spinal metastasis , and 20 with tuberculous spondylitis. The IVIM parameters, including the single-index model (apparent diffusion coefficient (ADC)-stand), double exponential model . The logistic regression model results showed that ADCfast and f were independent factors affecting the outcome (P < 0.05). The AUC values of ADCfast and f were 0.823 : 0.719 to 0.927) and 0.876 (95%CI: 0.782 to 0.969), respectively. ADCfast combined with f showed the highest AUC value of 0.925 (95% CI: 0.858 to 0.992).The ADCIVIM MR imaging might be helpful to differentiate spinal metastasis from tuberculous spondylitis, and provide guidance for clinical treatment. Osteoporosis, trauma, infection, or tumors are typical causes of clinically common diseases of the spine. Their diagnosis mainly depends on imaging findings and clinical features. However, benign and malignant lesions in the spine might have similar imaging findings, especially in the early stages of the disease . In addislow), perfusion-related diffusion (ADCfast), and the perfusion fraction (f). Recently, IVIM has been used to estimate tissue water diffusivity and micro-capillary perfusion. Perfusion MRI based on IVIM, which does not require contrast agents, has been widely used in studies of oncology. IVIM has been used for glioma grading, tumor diagnosis, central nervous system and abdomen since its development (Intravoxel incoherent motion (IVIM) is a noninvasive magnetic resonance imaging (MRI) method to visualize microscopic motions of water, which refers to translational motion that presents a velocity direction and/or amplitude distribution within a given voxel and over a measured time . Water melopment –10.slow and ADCfast values of malignant spinal tumors were significantly different from those of tuberculous spondylitis   . In addi < 0.05) , 12. IVI lesions . IVIM an lesions . IVIM-DW lesions . In addi lesions . IVIM MR lesions . Zhu et  lesions . AccordiFrom January 2016 to October 2018, 70 consecutive patients were enrolled in this study, and IVIM MRI was performed at 3.0T before treatment and puncture. Among them, 50 patients had spinal metastasis  and 20 patients had tuberculous spondylitis. The inclusion criteria were: Clinically definitive diagnosis or histopathological diagnosis. The exclusion criteria were as follows: 1) A history of interventional therapy such as radiotherapy, chemotherapy, or radiofrequency ablation before examination; 2) serious artifacts in the image; 3) the presence of smaller lesions (< 1 cm in diameter), resulting in inaccurate measurements; and 4) no clinical diagnosis.2. The scanning time was 252 s.Scanning was performed using a 3.0T MRI system  and 8-channel spinal coils. Conventional MRI sequence scanning was performed to help lesion localization. For patients with multiple lesions, lesions with the largest diameter were selected for DWI scanning. Conventional MRI sequences included axial and sagittal fast recovery fast spin echo (FRFSE) sequence (T2 WI) with a repetition time (TR) of 2800 ~ 4341 ms, echo time (TE) of 98–142ms, a slice thickness of 3.0 mm, a slice gap of 0.3mm, a band width of 62.5 kHz, a field of view (FOV) of 20 cm × 20 cm to 36 cm × 36 cm, and a matrix of 288 × 288  and 488 × 320 . The sagittal FSE sequence T1WI FSE had a TR of 500–642 ms, a TE of 8–11 ms, a slice thickness of 3. 0 mm, a slice gap of 0. 3 mm, a bandwidth of 62.5 kHz, an FOV of 28 cm × 28 cm to 36 cm × 36 cm, and a matrix of 320 × 320. The cervical and thoracic sagittal position IDEAL sequence T2 WI had a TR of 3000 ms, a TE of 69 ms, a slice thickness of 30 m, a slice gap of 0.3 mm, a band width of 833 kHz, an FOV of 28 cm × 28 cm to 36 cm × 36 cm; and a matrix of 320 × 192. The lumbar and sacro coccyx lipid suppression FRFSE sequence T2 WI had a TR of 2409–3100 ms, a TE of 88–98 ms, a slice thickness of 3. 0 mm, a slice gap of 0. 3 mm, a bandwidth of 50.0 kHz, and an FOV of 28 cm × 28 cm to 36 cm × 36 cm. IVIM-DWI was obtained with an axis single excitation spin-echo echo-planar imaging sequence, with the following parameters: a TR of 3000 ms, a TE of 64 ms, a slice thickness of 4.0 mm, a layer spacing of 0.4 mm, a bandwidth of 250. 0 kHz, an FOV of 24 cm × 24 cm, and a matrix of 128 × 64. The b values were 0, 20, 50, 100, 150, 200, 400, 800, 1200, and1500 s/mm2 (The region of interest (ROI) was set in the lesion center where the cross-section showed the largest level of the tumor with an area of 30–100 mm2 , 19 and slow, ADCfast, and the perfusion fraction (f)) and stretched-exponential model parameters (distributed diffusion coefficient (DDC) and intravoxel water diffusion heterogeneity (α)) were acquired. Two radiologists measured these parameters separately for each lesion by drawing an ROI -stand), double exponential model (ADCg an ROI 2. Receislow) + exp (b× ADCfast)], where S0 is the mean signal intensity, ADCslow is the molecular diffusion coefficient, ADCfast is the perfusion-related coefficient, and f is the perfusion fraction. The formula for the stretched-exponential model was as follows: Sb = S0 × exp (-b × DDCα), where α reflects the diffusion heterogeneity of water molecules in voxels.The ADC value was obtained by using high and low b values that were monoexponentially fitted to the following equation: Sb = S0 × exp (-b × ADC), where Sb is the signal intensity observed in the absence of a diffusion gradient. The formula for the biexponential model was as follows: Sb = S0 × [(1- f) × exp . Continuous variables are expressed as the mean ± standard deviation (SD). The intraclass correlation coefficient (ICC) was used to analyze the agreement between the two radiologists and was interpreted as follows: 0.00–0.20, poor agreement, 0.21–0.4, fair agreement, 0.41–0.60, moderate agreement, 0.61–0.80, good agreement, and 0.81–1.00, excellent agreement. Categorical variables are expressed as a percentage with a 95% confidence interval (CI). Two independent sample t-tests were used to compare normally distributed data, and the Mann-Whitney U test was used to compare non-normally distributed data. The variables with statistical significance in univariate analysis were included in the multivariate logistic regression model. Nonparametric ROC analysis was performed to evaluate the diagnostic performance of the IVIM parameters. The AUC was calculated to investigate the performance of these parameters, and the cut-off values with the largest sum of sensitivity and specificity were calculated from the ROC curves. The significance level set at p < 0.05.There were 50 patients with spinal metastasis , with a mean age ± SD of 56.92 ± 9.29 years; and 20 patients with tuberculous spondylitis (means age ± SD: 48.82 ± 19.84 years). The participants’ basic information is provided in stand, ADCslow, ADCfast, f values, DDC and α, with ICC values of 0.929 (95% CI: 0.889 to 0.956), 0.946 (95% CI: 0.914–0.966), 0.849 (95% CI: 0.768 to 0.903), 0.868 (95% CI: 0.796 to 0.916), 0.924 (95% CI: 0.880 to 0.952), and 0.911 (95% CI: 0.860 to 0.944), respectively.Excellent interobserver  reproducibility was obtained for ADCstand, ADCslow, ADCfast, f, DDC, and α of tuberculous spondylitis and spinal metastasis are shown in fast of spinal metastasis was significantly higher compared with that of tuberculous spondylitis, and the f values in patients with spinal metastasis were lower compared than those in patients with tuberculous spondylitis   Table 2.fast and f were independent variables affecting the outcome (p < 0.05)  Table 3.fast and f were 0.876  and 0.823 , respectively. The sensitivity and specificity of the ADCfast value to differentiate spinal metastasis from tuberculous spondylitis were 80.0% and 85.0%, respectively. The sensitivity and specificity of the f value were 86.0% and 65.0%. ADCfast combined with f showed much higher AUC than ADCfast and f, which the AUC values were 0.925 . Using the ADCfast combined with f as an index to discriminate spinal metastasis from tuberculous spondylitis, the sensitivity and specificity were 94.0% and 80.0%, respectively , and the combination of the two approaches can be used to assess neurological diseases .Recently, it was reported that the IVIM parameters could help to assess the early diagnosis and differentiation of diseases more precisely, as well as quantitatively monitor the effectiveness of treatment for tumors and other diseases. Ding et al.  comparedIn early or atypical spinal tuberculosis, there is no typical obvious bone erosion or abscess, and the imaging findings are complex and are sometimes similar to tumors, leading to misdiagnosis. While this is not common, it is still necessary to find ways to avoid it. Within the spinal column, metastasis is more commonly found in the thoracic region, followed by the lumbar region, while the cervical region is the least likely place to find metastasis. The aim of this study was to evaluate the diagnostic performance of IVIM MRI to differentiate spinal metastasis. To the best of our knowledge, our investigation is the first to illustrate the use of IVIM parameters to differentiate spinal tuberculosis from spinal metastasis.Our results showed that some IVIM parameters could help to discriminate spinal metastasis from tuberculous spondylitis and could investigate the feasibility of tumor type differential diagnosis of different metastases, including lung cancer, breast cancer, and renal cancer. Conventional DWI is based on the micro-movement of water molecules, which reflects the speed of water diffusion in the tissue. ADC values can quantitatively evaluate tissue diffusion and show microscopic changes at the cellular level caused by pathophysiological changes. In our study, no significant difference in ADC values was found between spinal metastases and tuberculous spondylitis, suggesting an ADC overlap in distinguishing them. Therefore, the results showed that the role of traditional ADC DWI in differentiating benign and malignant lesions of the spine is limited, which is consistent with previous studies , 24, 25.slow is mainly affected by water molecule diffusion of the lesion tissue and ADCfast is mainly affected by capillary microcirculation perfusion. Our results showed the ADCfast value of spinal metastases was significantly higher than that of tuberculous spondylitis, which suggested that perfusion is greatly increased. However, no significant differences were found between the ADCslow values between them. However, the ADCslow value of spinal metastasis with lung cancer was significantly lower than that of spinal metastasis with breast cancer as well as with renal cancer, suggesting that true diffusion is more restricted in lung cancer than in breast cancer and renal cancer. ADCfast and f values, but not the ADCslow value, showed better diagnostic performance than ADC values to differentiate spinal metastasis from tuberculous spondylitis. The f value is mainly affected by the blood volume of microcirculation perfusion, reflecting the proportion of microcirculation perfusion in tissue diffusion. Our results showed that the f value of spinal metastasis was lower than that of tuberculous spondylitis. Similar findings were reported in nasopharyngeal, pancreatic, and cervical lymph node metastases  for the publication of any potentially identifiable images or data included in this article.All authors contributed extensively to the work presented in this paper. Their roles are given below. Design of the work: NL. Acquisition of data: YL, XX. Interpretation of data: EZ, SQ. Drafting/Critical revision: EZ, YL, HY. Final approval: NL.This study has received funding by National Natural Science Foundation of China ; Beijing Natural Science Foundation (No. Z190020); Peking University International Hospital Research Grant (No. YN2019QN03).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.