High pMVD was associated with high blood flow (p = 0.008) and low ADC (p = 0.032). High Ktrans, kep, and blood flow were associated with high Gleason score. High pMVD, GMP, and low ADC were associated with most adverse clinico-pathological factors. Regarding prognosis, high pMVD, Ktrans, kep, and low ADC were associated with reduced biochemical recurrence-free- and metastasis-free survival (p ≤ 0.044) and high blood flow with reduced time to biochemical- and clinical recurrence (p < 0.026). In multivariate analyses however, microvascular proliferation was a stronger predictor compared with blood flow. Indirect, dynamic markers of angiogenesis from mpMRI and direct, static markers of angiogenesis from immunohistochemistry may aid in the stratification and therapy planning of prostate cancer patients.Active angiogenesis may be assessed by immunohistochemistry using Nestin, a marker of newly formed vessels, combined with Ki67 for proliferating cells. Here, we studied microvascular proliferation by Nestin-Ki67 co-expression in prostate cancer, focusing on relations to quantitative imaging parameters from anatomically matched areas obtained by preoperative mpMRI, clinico-pathological features and prognosis. Tumour slides from 67 patients  were stained for Nestin-Ki67. Proliferative microvessel density (pMVD) and presence of glomeruloid microvascular proliferation (GMP) were recorded. From mpMRI, forward volume transfer constant (K Tumours may thus be treated by angiogenesis inhibitors, as hypothesized by Judah Folkman in 19713. Histological biomarkers reflecting angiogenesis, such as microvascular density (MVD), could be useful prognostic indicators, as evaluated in numerous studies7. In prostate cancer, the results of these studies are somewhat conflicting13. MVD reflects inter-capillary distance and is determined by stimulating and inhibiting angiogenic factors as well as by the metabolic need of the tumour cells4. MVD is thus not a genuine marker specific for active angiogenesis nor the angiogenic dependence of the tumour tissue4. Measurement of vessels with proliferating endothelial cells by dual immunohistochemistry (IHC) with Factor VIII and Ki67 may be a better marker for ongoing tumour angiogenesis and outcome prediction16. Nestin is an intermediate filament protein found in neuroepithelial stem cells and glioma cells, but also in rapidly growing endothelial cells during active angiogenesis17. Hence, Nestin could be used as a marker of immature, newly formed vessels. Our group has used dual IHC by Nestin and Ki67 to assess proliferating immature blood vessels and its prognostic value in prostate cancer in a different cohort18, breast cancer19, and lung cancer20.Angiogenesis, the sprouting of new vessels from existing blood vasculature is essential for tumour growth and metastasis21. By measuring the uptake and washout of contrast on DCE-MRI, tumour angiogenesis can be estimated indirectly by mathematical pharmacokinetic models23. The rate of enhancement and washout of contrast is depending on the perfusion, the vascular permeability, and the volume of extravascular, extracellular space (EES) per unit volume of tissue (ve)22. Quantitative parameters such as the forward (Ktrans) and reverse (kep) volume transfer constant between blood plasma and EES24) yield combined information on vascular permeability and perfusion and may hence reflect the tumour angiogenesis in vivo22.In prostate cancer, multiparametric MRI (mpMRI) including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCE-MRI) add functional information to conventional T1-and T2-weighted anatomic imaging32. The relationship between mpMRI-parameters and ongoing angiogenesis, estimated by microvascular proliferation, has been studied to a much lesser extent in clinical tumour samples33 and is to our knowledge not previously examined in prostate cancer.Correlations between quantitative DCE-MRI-parameters and direct tissue-based biomarkers of angiogenesis, such as vascular endothelial growth factor (VEGF) and MVD have been studied in several malignancies, including in prostate cancer, with varying resultstrans, kep, ve, and blood flow were studied as indirect, dynamic estimates of angiogenesis. In this study, we focused particularly on relations between microvascular proliferation and quantitative parameters from mpMRI and on potential associations with clinico-pathological features and patient outcome.Here, we evaluated microvascular proliferation by Nestin-Ki67 co-expression in radical prostatectomy specimens from 67 patients as a direct, static measure of ongoing angiogenesis. From anatomically matched areas obtained by preoperative mpMRI, the quantitative imaging parameters K2, proliferative microvessel density (pMVD)/mm2 and vascular proliferation index (VPI = pMVD/MVD%) and parameters from mpMRI (forward volume transfer constant (Ktrans [min-1]), reverse volume transfer constant (kep [min-1]), volume of EES (ve), blood flow (mL/100 g/min), and apparent diffusion coefficient (ADC [mm2/s])) are presented in Table Descriptive statistics for the immunohistochemical markers of angiogenesis (microvessel density (MVD)/mmrans min-), reversp = 0.008), low ADC (p = 0.032) and with a trend for high kep (p = 0.063). High VPI was associated with low ADC and low ve (both p = 0.038), with a trend for high tumour blood flow (0 = 0.054). MVD and GMP were not associated with any of the quantitative mpMRI-parameters (Table trans and high kep were associated with high blood flow (p = 0.001 and p = 0.010). Neither Ktrans, kep nor blood flow were associated with ADC.High pMVD was associated with high tumour blood flow ( p = 0.03 and withp = 0.063 and p = 0.050). Furthermore, high pMVD was significantly associated with extra-prostatic extension, high pathological stage, and large tumour dimension, as seen in Table p = 0.041). High pMVD, GMP, Ktrans, kep, and blood flow were all associated with the D`Amico high-risk group.High pMVD was borderline associated with high Gleason score (Gleason GG ≥ 4) and a cribriform Gleason pattern in the hot-spot area chosen for vessel counting (trans and high kep and high blood flow were associated with high Gleason score (Gleason GG ≥ 3) in the surgical specimen (p ≤ 0.044), and high Ktrans was also associated with high s-PSA (p = 0.045) , similar results were achieved  (Table p = 0.032 and p = 0.093) together with kep .Multivariate Cox’ survival analyses were performed using the end-points biochemical recurrence and clinical recurrence. When including the tissue-marker of angiogenesis from IHC (pMVD) together with quantitative parameters from mpMRI (Kw) Table , pMVD intrans, kep, and ADC independently predicted biochemical recurrence , whereas kep and ADC independently predicted clinical recurrence . Gleason score remained an independent predictor in all models , pathological stage (≥ pT3 vs pT2), and preoperative s-PSA  , presence of GMP, and the D`Amico high-risk group (Supplementary Table SP ≤ 0.036) by univariate survival analyses  and clinical recurrence  together with Gleason score , we also assessed tumour blood flow, by using a different model. We demonstrate that increased direct  and indirect  measures of tumour-associated angiogenesis were associated with adverse clinico-pathological factors and disease progression, with a strong association between high microvascular proliferation and high tumour blood flow. In multivariate survival analyses, we found that microvascular proliferation was a stronger predictor compared with blood flow and that Kep was a stronger predictor compared with Ktrans and blood flow.In this study, angiogenesis was assessed in prostate cancer by dual Nestin-Ki67 IHC along with the quantitative mpMRI-parameters K32. Some of the studies found a positive correlation between kep and MVD, others did not find any correlation32. However, microvascular proliferation is a better marker of active, ongoing angiogenesis and a better predictor of outcome than MVD20 and has to our knowledge not been investigated in prostate cancer together with imaging parameters.Studies investigating the relationship between MVD and basic estimates of angiogenesis from mpMRI have been previously performed on matched tumour areas in relatively small series of prostate cancertrans, kep, and ADC independently predicted biochemical recurrence, whereas kep and ADC independently predicted clinical recurrence, but blood flow was not an independent predictor of any end-point. However, a subgroup of patients with combined high pMVD and high tumor blood flow independently predicted both biochemical and clinical recurrence. Our results invite further studies to investigate the potential use of quantitative parameters from mpMRI as indirect in vivo markers of angiogenesis and tumour aggressiveness already at the time of diagnosis. These indirect markers of angiogenesis are more functional and might be combined with direct but static tissue-markers of angiogenesis from IHC for potential use in prognostication and risk stratification of prostate cancer patients.In multivariate Cox’ survival analyses, pMVD, K38, probably a reflection of increased tumour cellularity37, resulting in restricted movement of water molecules. Studies have also demonstrated an association between low ADC and reduced biochemical recurrence-free survival40. Furthermore, some studies demonstrate an inverse relationship between ADC and MVD42, VEGF42, or Hif-1α38 in prostate cancer, suggesting that ADC may be a potentially useful surrogate marker of angiogenesis as well. In concordance with this, low ADC was associated with high pMVD, aggressive tumour features, and reduced recurrence-free and metastasis-free survival in our material.Several studies have found a negative correlation between ADC and Gleason score in prostate cancer18. The results are also in line with previous studies from our group on breast carcinoma19 and lung carcinoma20. However, direct assessment of angiogenesis is time-consuming with inter-observer variations. Further studies are needed to validate our findings and to establish a standardised and possibly automated method for pMVD-assessment for practical implementation.Our findings on pMVD validate the prognostic importance of microvascular proliferation in prostate cancer as found in a previous study presented by our group using an independent cohort43. GMP is one of the diagnostic features of glioblastoma multiforme44, but have also been found as a prognostic marker in several other malignancies48. GMP is suggested to be a better prognostic marker than MVD48, and has been associated with lack of response to neoadjuvant chemotherapy in breast cancer45. In our study, presence of GMP was associated with increased pMVD and with most adverse clinico-pathological features, but not with outcome. Overall, pMVD was a better prognostic marker compared to GMP in our material.GMPs are small blood vessels arranged in aggregates resembling renal glomeruli20 originally described by Weidner et. al6. To obtain more objective measurements, counting in random areas or even counting in the whole tissue have been proposed13 as has the use of image analysis32. Another limitation of our study is the MRI procedure. The current standard at our hospital is to perform pre-biopsy mpMRI. In our study, mpMRI was performed preoperatively on patients with biopsy-proven prostate cancer and haemorrhage after the biopsy procedure may potentially have influenced the MRI parameters. However, with a median time delay of more than three months between biopsy and MRI, the risk for an influence from tissue trauma following biopsy is likely to be low. A strength of our study is the high anatomical correspondence between the ROIs for quantitative imaging parameters and the selected areas for IHC measurements. To reduce the problem of tumour heterogeneity, not being captured by a single ROI, the MRI parameters may also be analysed by pixel-by-pixel analysis of the whole tumour, requiring time consuming whole-volume tumour segmentations28. However, ROI seems to be better for model fitting49 and is frequently used33.This study has some limitations. It is a retrospective study with a relatively small sample size, hence results should be interpreted carefully. Assessment of MVD and pMVD is not standardised, and it is difficult to compare the results with other studies using different antibodies, different methods for vessel counting and different cut-off values. We decided to count vessels manually in hot-spot areas using established criteria50. We used the open-source software Quantiphyse to collect the basic quantitative parameters. Here, more patients were included, and this software has a robust method of estimating T1. NordicIce was primarily used to obtain data on tumour blood flow. However, extracted data correlated between softwares.Two different softwares were used to extract the mpMRI data. Inter-software variation may be explained by different methods of estimating baseline T152. Anti-angiogenic therapy has demonstrated some efficacy in clinical trials on hormone-sensitive prostate cancer patients55, but fails to improve overall survival for patients with castration resistance56. Our investigated markers of angiogenesis might aid in the prediction of response to anti-angiogenic treatment and could potentially be of value in patient stratification. The markers may also have the potential to aid in the evaluation of treatment effect and should be further studied in clinical trials of prostate cancer patients undergoing such therapy.Although angiogenic activity is essential for cancer growth, progression, and metastasis, the use of anti-angiogenic agents for treatment has not been as straightforward as initially advocated, as shown by standard quantitative parameters Ktrans and kep, as well as tumour blood flow. Of these mpMRI-acquired parameters, kep was the strongest predictor of outcome.Angiogenesis is essential for tumour growth and metastasis. We here show that microvascular proliferation, by dual IHC with Nestin-Ki67, is superior to standard microvessel density to reflect active, ongoing angiogenesis and to predict patient outcome. DCE-MRI allows quantitative assessment of vascular permeability and perfusion and may hence characterize the dynamic tumour microvasculature and reflect tumour angiogenesis in vivoTo summarise, we have demonstrated significant relations between microvascular proliferation by dual IHC with Nestin-Ki67 on radical prostatectomy specimens and in vivo quantitative parameters from preoperatively acquired mpMRI. These investigated markers of angiogenesis were associated with disease progression, microvascular proliferation being a stronger predictor compared with blood flow. The use of direct and indirect measures of angiogenesis, maybe in combination, has the potential to aid in the assessment of prognosis and treatment planning of prostate cancer patients.trans, kep, and ve were successfully quantified for 60/67 patients using the software Quantiphyse, whereas blood flow was successfully obtained for 52/67 patients, using NordicIce. All cases were acinar adenocarcinomas, including one case with partly pseudohyperplastic features and several cases with focal mucinous features. No patients received neo-adjuvant therapy except one patient who received bicalutamide a short period pre-operatively before deprescribing. Diagnostic biopsies were taken prior to mpMRI, the median number of biopsies was 10 (range 3–14) (Supplementary Table p = 0.518) or number of biopsies taken (p = 0.228), and with one exception , mpMRI parameters were not significantly associated with time since biopsy or number of biopsies taken. The entire prostate was routinely studied using whole-mount sections with 5 mm intervals, corresponding to the axial MR images. For each case, a radiologist (LARR) and two pathologists (KG and OJH) independently selected and registered the area of highest tumour grade by MRI and histopathology, respectively. Afterwards, the high-grade tumours were compared by looking at drawings from the whole-mount histological sections of the entire prostate and the at that time standard reporting scheme for locating 27 regions of interest on MRI58. The high-grade areas were then cut out of the original paraffin block, re-embedded in paraffin, and sectioned for IHC. In ten cases, the high-grade tumours were placed in different areas according to radiological and pathological examination. In these cases, both areas were cut out and examined without finding any significant differences between the areas regarding MVD, pMVD, VPI, Ktrans, kep, ve, blood flow, or ADC (McNemar and Wilcoxon tests). These patients had only Gleason GG 1–3, ≤ cT2b tumours, but did otherwise not stand out from the others. Only results from the pathological high-grade area are used in this study. This study was approved by the Western Regional Committee for Medical and Health Research Ethics, REC West (REK 2015/2178) and the South Eastern Regional Committee for Medical and Health Research Ethics, REC South East (REK 2009/711). All patients gave their written informed consent. All methods were performed in accordance with guidelines and regulations by the University of Bergen and REK, and in accordance with the Declaration of Helsinki Principles.The study includes 67 prostate cancer patients, treated with robot-assisted laparoscopic radical prostatectomy (2010) at Haukeland University Hospital, Bergen, Norway. All patients underwent a pre-operative endorectal 1.5-T mpMRI. The DCE parameters K59 were registered from the clinical patient files , clinical recurrence , locoregional recurrence , metastases , overall survival, and prostate cancer-specific survival were obtained from hospital records. At the last follow-up, 8 patients had died (two due to prostate cancer). There were 16 biochemical recurrences, 14 clinical recurrences, and 7 locoregional recurrences. 9 patients developed metastases   was obtained in target retrieval solution, pH 6.0 . After cooling, the slides were transferred to an autostainer instrument (Dako). Dual endogenous enzyme blocking solution (Dako) was added for 7 min. The slides were incubated  with both Nestin mouse IgG SC-23927 10c2 , diluted 1:50 and Ki67 rabbit IgG Clone SP6 , diluted 1:100. HRP anti-mouse EnVision (Dako) for Nestin and goat anti-rabbit IgG (H + L) alkaline phosphatase  for Ki67 in the ratio alkaline phosphatase:EnVision 1:100 was added for 30 min in room temperature. The last part of the staining procedure was done manually, using a humidifying chamber . The alkaline phosphatase was localised by Ferangie Blue™ Chromogen System   and HRP by AEC + Substrate Chromogen (Dako) . Counterstaining was not done. Faramount aqueous mounting medium (Dako) was used to mount the slides. Sections from colon cancer tissue with known reactivity were used as positive controls. Negative controls were obtained by applying diluent without the primary antibody.6 was used, blinded to MRI findings and patient information. The slides were evaluated at low magnification (× 40 and × 100) to find the most vascular areas (“hot-spots”) of the tumour. One hot-spot area per case was outlined with an ink marker. In hot-spot areas, 10 non-overlapping high-power fields  were examined for each case for the total number of Nestin-positive vessels. The number of stained vessels/mm2 was recorded as the MVD. The Nestin-positive structures needed to contain cells that resembled endothelial cells or clusters of endothelial cells to be counted. It should be clearly separate from adjacent microvessels. A vessel lumen was not required to be counted as a microvessel. Fibroblasts, nerves, and other non-endothelial cells in the stroma stained weaker than the endothelial cells and were not counted. The pMVD was evaluated in the same ten fields as MVD as the number of Nestin-positive vessels containing at least one proliferating endothelial cell/mm2. A proliferating endothelial cell was recognised by a blue Ki67-positive endothelial nucleus in a red Nestin-positive vessel , 0.86 (p = 0.001), and 0.74 (p = 0.010) for MVD, pMVD, and VPI. Spearman`s rho for MVD by CD31 and Factor VIII were 0.86 (p < 0.0005) and 0.83 (P < 0.0005).Before evaluation of the slides in the cohort, a period of training was performed on a training set of colon carcinomas (n = 25) stained with CD31, Factor VIII, and Nestin-Ki67. As the dual staining had faded with time, only 11 cases could be used for Nestin-Ki67 counting. After a training period, Spearman`s rho for Nestin-Ki67 were 0.87 (p < 0.0005), 0.82 (p < 0.0005), 0.83 (p < 0.0005), and 0.58, 0.81, and 0.70, respectively.Intra-observer variability was tested in a blinded manner (AB) by evaluating the main series twice. For MVD, pMVD, and VPI, the Spearman`s rho and Kappa values (cut-off by median) were 0.89  covered the entire prostate gland with a temporal resolution of 6.16 s for the DCE.All images were acquired using a 1.5 T MR scanner  with an integrated endorectal phased-array coil . The scanning protocol has been published previously60, an Open Source software available from the University of Oxford. The quantitative parameters Ktrans, kep, and ve were obtained61 by applying the Tofts model24. The ADC values were collected from the high-grade tumours using DWI58. The ADC value was measured in the region of interest (ROI), including 2/3 of the lesion on axial ADC maps. Both mean, median, minimum, and maximum values of Ktrans, kep, and ve were recorded within each ROI. Median values were superior in the evaluation of all results, only median values are presented in this study.Two observers , with more than 3 years’ experience in reading prostate MRIs, read the MRI datasets. The matched areas for ROI placement within the predefined high-grade tumour areas were carefully selected by the radiologist (LARR) in cooperation with the pathologist who performed the IHC vessel assessment (AB). One tumour ROI was drawn per patient, except for the ten patients where two areas were assessed by IHC, here two ROIs were drawn. As a standard, three MRI planes through the tumour were included in the ROIs, one from the centre of the tumour focus and one from each side of the centre. All ROIs were segmented and analysed using Quantiphyseep, Ktrans, and ve were extracted (by the Tofts model), for comparison with the similar DCE parameters extracted in Quantiphyse23. The DCE parameters derived in NordicICE were all positively correlated to the comparable parameters derived in Quantiphyse , Supplementary Table ep, and ve derived in Quantiphyse (n = 60), and the mean lesion blood flow derived in NordicIce (n = 52).Additionally, to obtain data on tumour blood flow, ROIs of all lesions were re-drawn by one radiologist (AR) and analysed using NordicIce v.4.1.3 . Mean tumour blood flow was calculated as the peak of the residue function. Furthermore, mean tumour ktrans, kep, and ADC. The lower quartile was used as cut-off for tumour blood flow. For pMVD, the median as cut-off value (0.00 vs ≥ 0.41) equalled absence/presence of pMVD and coincided with VPI using the lower quartile as cut-off. GMP was categorised as present or absent. s-PSA and the largest tumour dimension were dichotomised by the upper quartile.Median, tertile, and quartile values of the variables in the patient cohort were examined. The number of events and size of subgroups were considered and categories with comparable survival were merged. The median was selected as cut-off value for pMVD, KU test. For related samples, the McNemar test and the Wilcoxon signed rank test were used. For univariate survival analyses, Kaplan–Meier plots were computed for visualisation and differences between the groups were analysed by the product-limit procedure (log-rank test). Cox’ univariate survival analyses were used for continuous variables. For multivariate survival analyses, the Cox’ proportional hazards method (likelihood ratio test for differences) was conducted, including variables with p < 0.10 in univariate analysis. Proportional hazard assumptions were examined by log–log plots.The SPSS statistical package  version 27.0 was used for statistical analyses. The Spearman correlation test and Cohen’s kappa statistics were used to evaluate inter-and intra-observer agreement. The Spearman correlation test was used to analyse the relationship between continuous variables from quantitative mpMRI-parameters. Pearson’s chi-square or Fisher’s exact test were used to analyse associations between categorical variables. Associations between continuous and categorical variables were assessed by the Mann–Whitney Supplementary Information.


Prospective randomized control trial” Saudi Med J 2021; Vol. 42 (10): 1065-1071 doi: The affiliation should appeared as: From the Department of Anesthesiology ; from the Department of Orthopedic Surgery (Aljurayyan), College of Medicine, King Saud Universityahaji@ksu.edu.saThe e-mail should appear as:


In the aortas of ApoE–/– mouse, adropin treatment ameliorated the decrease in the mRNA expression of endothelial cell markers , but increased that of EndMT markers . In vitro, an adropin treatment (30 ng/ml) arrested the hydrogen peroxide (H2O2)-induced EndMT in human umbilical vein endothelial cells (HUVECs), attenuated the morphological changes of HUVECs, reduced the number of immunofluorescence-positive α-SMA, increased the mRNA and protein expressions of CD31 and VE-cadherin, and decreased those of α-SMA. Furthermore, the adropin treatment decreased the mRNA and protein expressions of transforming growth factor (TGF)-β1 and TGF-β2, and suppressed the phosphorylation of downstream signal protein Smad2/3 in HUVECs. These mitigative effects of adropin on H2O2-induced EndMT were reversed by the transfection of TGF-β plasmid. The findings signify that adropin treatment may alleviate the atherosclerosis in ApoE–/–/Enho–/– mice by inhibiting EndMT via the TGF-β/Smad2/3 signaling pathway.Adropin, a secreted protein, coded by energy homeostasis-associated gene (Enho), is recently reported to modulate atherogenesis, with endothelial-to-mesenchymal transition (EndMT) involved in the early process. We explored whether adropin may alleviate atherosclerosis by regulating EndMT. We found that an intraperitoneal injection of adropin [105 μg/(kg·d) for 13 weeks] inhibited the progression of high-fat diet (HFD)-induced aortic atherosclerosis in apolipoprotein E-deficient mice (ApoE Endothelial dysfunction is involved in the initial stage of atherosclerosis, in which the endothelial-to-mesenchymal transition (EndMT) plays a significant role in the early development of atherosclerotic lesions –3. The oThe process of EndMT can also change the morphology of endothelial cells, resulting in the loss of their barrier function. The aggravation of EndMT can dramatically decrease the expressions of leukocyte differentiation antigen (CD) 31 and vascular endothelial cadherin (VE-cadherin), which are the markers of morphology and function of endothelial cells. Meanwhile, the occurrence of EndMT will induce a gradual expression of alpha smooth muscle actin (α-SMA), smooth muscle 22 alpha (SM22α), and fibroblasts specific protein (FSP)-1, which are usually not expressed in endothelial cells. Therefore, the expressions of these markers can be manipulated to detect whether the endothelial cells have been converted into mesenchymal cells , 5.Enho) that plays an important role in maintaining energy balance, fat metabolism, and insulin response . However, the adropin treatment (the HFD + Adropin group) significantly lowered the lipid accumulation  when compared with the HFD group. In addition, the double gene knockout mice (DKO-HFD group) showed the most lipid accumulation among all the groups, which was significantly decreased by adropin treatment , indicating that adropin can reduce the accumulation of lipid under intima %, P < 0.05]. Compared with the DKO-HFD+Adropin group, the HFD + Adropin group displayed only local bulging plaques on the intimal surface with complete fiber caps at the top of the plaques  % vs. (45 ± 1)%, 05] Fig. . These f05] Fig. .-/- mice  and the markers of mesenchymal cells (α-SMA and FSP-1) Fig. . The HFD2O2-induced EndMT model was further adopted to evaluate the effects of adropin on the conversion. Light microscopy revealed smooth muscle-like cells due to the H2O2-induced morphological changes of human umbilical vein endothelial cells (HUVECs). The results showed that after 4 days of culture, H2O2 significantly changed the morphology of endothelial cells into the fusiform shape, producing smooth muscle-like cells % vs. (3 ± 1)%, P < 0.001] % vs. (10 ± 4)%, P < 0.001]  led to a lower gene and protein expressions of CD31 and VE-cadherin, but a higher expression of α-SMA, indicating significant EndMT, which was improved by the adropin treatment (the H2O2 + Adropin group). However, the adropin-induced increase in the gene and protein expressions of CD31 and VE-cadherin and that in protein expression of α-SMA were blocked by the transfection of TGF-β1 plasmid into HUVECs (the H2O2 + Adropin + TGF-β group). These results suggest that adropin can maintain the expressions of CD31 and VE-cadherin but inhibit the expression of α-SMA in HUVECs, and that the TGF-β signaling pathway may be involved in adropin-induced attenuation of EndMT.Compared with the Control group, H2O2 (the H2O2 group) increased the mRNA and protein expression of TGF- β2 and the mRNA expression of TGF-β1, which were significantly decreased by adropin treatment (the H2O2 + Adropin group) (P < 0.05)   Fig. . Compare05) Fig. . We furt-βR Fig. . These r2O2 increased the phosphorylation of Smad2/3, which was downregulated by the adropin treatment (P < 0.05). The adropin-induced downregulation of p-Smad2/3 was blocked by the transfection of TGF-β1 plasmid (the H2O2 + Adropin + TGF-β group). These data suggest that the TGF-β/Smad2/3 signaling pathway may be involved in the adropin-induced attenuation of EndMT.As a downstream signal protein of TGF-β, Smad2/3 protein is closely related to the occurrence of EndMT. Therefore, we analyzed the total and phosphorylated protein expression of Smad2/3 (p-Smad2/3/t-Smad2/3) by Western blotting Fig. . Compare-/-/Enho-/- mice, and further demonstrated that adropin inhibited the occurrence and development of atherosclerosis in high-fat diet (HFD)-fed ApoE-/- mice by inhibiting the EndMT. Moreover, the anti-atherosclerotic effect of adropin was achieved by inhibiting the expression of TGF-β and weakening the phosphorylation of Smad2/3 in endothelial cells. These findings provide some novel insights into the therapeutic value of adropin for the treatment fo atherosclerosis.In this study, we provided more reliable evidence for the anti-atherosclerotic effects of adropin by using ApoEEnho gene and is expressed and secreted in the liver, brain, coronary arterial endothelium and other tissues and organs [Adropin, composed of 76 amino acid residues, is a new secretory protein discovered by Kumar et al. in 2008 [d organs .-/- mice receiving HFD [-/- mice receiving HFD and intraperitoneal injection of adropin from 8 weeks of age for 13 weeks, with the 13-week HFD scheme chosen according to a previous report [-/-/Enho-/- mice) that has a severer atherosclerosis and found that the supplementation of adropin significantly ameliortated the above effects. Altogether, these findings strongly suggest that adropin may exert anti-atherosclerotic effects in the ApoE-/- mice and the ApoE-/-/Enho-/- mice.Recent studies have reported that adropin, at a dose of 10 μg/kg/h (240 μg/kg/d) using subcutaneously osmotic minipumps for 4 weeks, may confer anti-atherosclerotic effects in ApoEving HFD . In thiss report . The ints report . However-/- mice fed with HFD, which is consistent with the previous study [Although the suppression of monocyte-endothelial cell adhesion and SMC proliferation has been involved in adropin-conferred anti-atherosclerotic effects, the exact mechanism remains unknown . A previus study . The disEndMT is a fundamental process during development, including the cardiovascular system . Many st2O2-induced EndMT model of HUVECs. The changes in both morphology (smooth muscle-like cells) and phenotype (cell markers) were also directly observed under light and confocal microscopes. In this study, both HUVECs culture in vitro and ApoE-/- mice in vivo confirmed that adropin inhibited the conversion of endothelial cells into SMCs, thus suppressing the EndMT.Here, we furtherly explored the role of EndMT in adropin-conferred anti-atherosclerosis. Available literature has demonstrated that treating HUVECs with adropin at a dose of 10–25 ng/ml can confer a protective effect . Our useIn addition, EndMT has been documented to contribute considerably to the vascular remodeling and neointimal formation that arises after a vein graft transplantation into the arterial circulation . This pr2O2-treated HUVECs. The involvement of TGF-β was confirmed by the facts that adropin may directly inhibit the gene and/or protein expressions of TGF-β1 and TGF-β2, and that adropin-induced alteration of cell markers is blocked by the transfection of TGF-β1 plasmid. We found that adropin had no significant inhibitory effect on the expression of TGF-βR. Nevertheless, adropin significantly decreased the phosphorylation of Smad2/3, which is the downstream of the TGF-βR pathway. The effects of adropin was blocked by the transfection of TGF-β1 plasmid in this study. These data suggest that the TGF-β/Smad2/3 pathway may be involved in adropin-induced attenuation of EndMT.In previous studies, the TGF-β/Smad2/3 signaling pathway has not be involved in the processes of adropin-conferred metabolic regulation and endothelial protection, although these processes may involve other signaling pathways, including phosphatidylinositol 3-kinase-Akt , extraceSome limitations remain in this study. First, only single dose of adropin was in vivo and in vitro used in this study. Second, the inhibitors of TGF-β/Smad were not used in this study, although the use of TGF-β1 plasmid helped explore the mechanism. Third, we did not involve noncanonical signaling pathways which also have a bearing on TGF β- Smad cascade. Fourth, we did not explore other mechanisms underlying the effect of adropin on AS. Fifth, in vitro cell models cannot fully simulate in vivo animal models.-/-/Enho-/- mice through non-lipid-regulating pathway, by inhibiting EndMT via the TGF-β/Smad2/3 signaling pathway. The findings signify the potential therapeutic value of adropin in the prevention of atherosclerosis.In conclusion, adropin can reduce atherosclerosis in ApoEThis study was reviewed and approved by the Experimental Animal Care Committee of Fujian Medical University Union Hospital and the experimental procedures observed the Guide for the Care and Use of Laboratory Animals revised by the National Institutes of Health in 2011.-/- and DKO mice (aged 8 weeks old and weighed 18g–25g) were respectively purchased from Beijing Huafukang Biotechnology Co., Ltd (China) and Beijing Viewsolid Biotechnology Co., Ltd (China). The animals were housed in a conventional animal facility. To establish the models of atherosclerosis, ApoE-/- and DKO mice were fed with HFD  for 13 weeks as described previously [n = 10 mice/group)  HFD group, with ApoE-/- mice fed with HFD; (3) HFD+Adropin group, in which the ApoE-/- mice received HFD and were intraperitoneally injected with adropin (105 μg/kg)  every day for 13 weeks; (4) DKO-HFD group, with the DKO mice fed with HFD; (5) DKO-HFD+Adropin group, in which the DKO mice received HFD and an intraperitoneal injection of adropin.Specific pathogen free grade male ApoEeviously . All mic-/- mice per group for the assessment of biochemical indexes. Their aortic roots were dissected to evaluate the severity of atherosclerosis by Oil Red O (ORO) and haematoxylin-eosin (H&E) staining. The expression of EndMT-related markers was detected by immunofluorescence. The mRNA of aortic inner wall cells  was collected by repeatedly washing the inner cavity of thoracoabdominal aortas with TRIzol Reagent . The mRNA expression of EndMT-related markers was measured by quantitative real-time PCR (q-PCR); (2) the aortic roots from five DKO mice per group were dissected for ORO and H&E staining; (3) The whole aortas  were dissected from another five animals per group and stained with ORO to further assess the severity of atherosclerotic lesions.At the end of the experiments, all animals were anesthetized with an intraperitoneal injection of ketamine (75 mg/kg) and diazepam (7.5 mg/kg). Afterwards, the tissue and blood samples were collected as follows  containing 5% fetal bovine serum , 1% endothelial cell growth supplement  and 100 U/mL penicillin-streptomycin .HUVECs were purchased from ScienCell Research Laboratories  and were cultured in a 5% CO2O2 for 6 days as described previously [2O2 group, with cells treated with H2O2; (3) H2O2 + Adropin group, in which cells were incubated with 30 ng/ml adropin 10 min before the H2O2 treatment; (4) H2O2 + Adropin+TGF-β plasmid group, receiving the same treatment as the H2O2 + Adropin group, as well as the cellular transfection of transforming growth factor (TGF)-β1 plasmid.To establish the in vitro EndMT model, HUVECs were treated with 100 μmol/L Heviously , and div® HiPure Plasmid MaxiPrep Kit  according to the manufacturer’s protocol. For the transfection (at a density of 2 × 105 HUVECs per well), the DNA of TGF-β1 plasmid (0.8 μg) was diluted in 50 μl of a serum-free medium and placed in a resting state for 5 min. Lipofectamine 2000 (2 μl) was diluted in 48 μl of the serum-free medium and left in a resting state for 5 min. Afterwards, the diluted DNA was combined with the diluted Lipofectamine 2000  and incubated at room temperature for 20 min. Next, the 100 μl of complexes were added to each well. Subsequently, the cells were further incubated at 37 °C in a CO2 chamber for 24–48 h prior to transgenic expression testing.The TGF-β1 plasmid was amplified in Escherichia coli  and then extracted by plasmid isolation with the EasyPure2O2-induced EndMT under light and confocal microscopes. The expressions of CD31, VE-cadherin, α-SMA, TGF-β1, and TGF-β2 in HUVECs were assessed by q-PCR and Western blotting. The expressions of TGF-βR and Smad2/3 were respectively detected by q-PCR and by Western blotting.After a 6-day culture, HUVECs were collected to assess the effects of adropin on H2, as described previously [To visualize atherosclerotic lesions and determine plaque size, consecutive frozen sections from aortic roots were treated by ORO and H&E staining , and the whole aortas by ORO staining, as described previously , 27. In -/- mice and α-SMA in the H2O2-treated HUVECs were determined by immunofluorescence. Consecutive frozen aortic sections used in ORO and H&E staining were also used in immunofluorescence. The frozen aortic sections and HUVECs were fixed with 4% paraformaldehyde, permeabilized with 0.5% Triton X-100, and blocked in 2% bovine serum albumin for 30 min at room temperature. CD31, SM22α and α-SMA were treated their primary antibodies and their expressions were examined using anti-Rabbit or anti-Mouse IgG. After a 2-min staining with 4’,6-diamidino-2-phenylindole (DAPI), the fluorescent images were taken under a confocal laser scanning microscope . Qualitative analysis was performed for aortic tissues and quantitative analysis for cultured HUVECs. The α-SMA positive HUVECs were calculated and expressed as a percentage over the total number of DAPI positive nuclei in the field of the confocal microscope. Smooth muscle-like cells, which occurred due to H2O2-induced morphological changes, were measured and expressed as a percentage relative to the total number of HUVECs in the field of the light microscope. All antibodies used in this study are summarized and listed in Supplementary Table To evaluate the extent of EndMT, the expressions of CD31 and SM22α in aortic roots from the ApoEq-PCR was performed to detect the mNRA expressions of CD31, VE-cadherin, α-SMA, and fibroblasts specific protein-1 (FSP-1) in the aortic inner wall, and those of CD31, VE-cadherin, α-SMA, TGF-β1, TGF-β2, and TGF-βR in the HUVECs.-ΔΔCt method. Primers used are summarized in Supplementary Table Trizol reagent  was applied to extract the total RNA from the aortic inner wall (intima) and HUVECs. The extracted RNA samples were converted into first strand cDNA using an RT2 First Strand kit, following the manufacturer’s protocol . Quantitative gene expression was analyzed by q-PCR and performed on an ABI Prism 7900 HT . Gene specific primers  and SYBR Green q-PCR detection kit  were employed as instructed by the manufacturer. Data were analyzed by the 23VO4, 50 mmol/L NaF, protease inhibitor cocktail; pH 7.5; Beyotime; phosphatase inhibitor cocktail, Roche). The concentrations of the samples were determined with a BCA kit , with the bovine serum albumin (BSA) as a reference protein. The samples were separated by SDS-PAGE and transferred to nitrocellulose membranes, followed by incubation with primary antibodies at 4 °C overnight. After an incubation with the fluorescence-conjugated secondary antibodies  at room temperature for 1 h, the immunoreactive proteins were visualized with a Chemiluminescence gel imager (Tanon-5500) . Data were normalized by setting the densitometry of control sample at 1. All antibodies used in this study are listed in Supplementary Table Western blotting was performed to determine the protein expressions of CD31, VE-cadherin, α-SMA, TGF-β1, TGF-β2, and the total and phosphorylated protein of Smad2/3 in HUVECs. Cells were lysed with a buffer (containing 20 mmol/L Tris, 150 mmol/L NaCl, 1 mmol/L EDTA, 1 mmol/L EGTA, 1% Triton × 100, 2.5 mmol/L sodium pyrophosphate, 1 mmol/L β-glycerophosphate, 1 mmol/L Nat tests or ANOVA. When a statistical difference appeared, the least significant difference procedure was applied. A value of P < 0.05 was considered statistically significant.The measurement data were expressed by mean ± SEM. Statistical analysis was performed with SPSS 20.0 for Windows. For comparison between multiple groups, data were analyzed by Supplementary Table 1Supplementary Table 2Supplementary Figure LegendsSupplementary Fig. 1Supplementary Fig. 2Original Data File


Alb) evaluation in the diagnosis of CNS diseases. We also discussed the collection of cerebrospinal fluid , time of transport to the laboratory, and storage conditions. Finally, we briefly presented the role of cerebrospinal fluid examination in CNS disease diagnosis of various etiologies and highlighted that research on identifying cerebrospinal fluid biomarkers indicating disease presence or severity, evaluating treatment effectiveness, and enabling understanding of pathogenesis and disease mechanisms is of great importance. Thus, in our opinion, research on cerebrospinal fluid is still necessary for both the improvement of CNS disease management and the discovery of new treatment options.Cerebrospinal fluid plays a crucial role in protecting the central nervous system (CNS) by providing mechanical support, acting as a shock absorber, and transporting nutrients and waste products. It is produced in the ventricles of the brain and circulates through the brain and spinal cord in a continuous flow. In the current review, we presented basic concepts related to cerebrospinal fluid history, cerebrospinal fluid production, circulation, and its main components, the role of the blood–brain barrier and the blood–cerebrospinal fluid barrier in the maintenance of cerebrospinal fluid homeostasis, and the utility of Albumin Quotient (Q In the literature, the first mentions of cerebrospinal fluid appear as early as the 16th century B.C. in the Edwin Smith Papyrus, which contained 48 case reports related to head, spinal cord, and peripheral nerve injuries, each of which included a detailed description of examination, diagnosis, and treatment ,3. LaterIn ancient times and the age of the Renaissance, autopsies were not widely practiced. If they were performed, they were always by decapitation, which precluded the study of cerebrospinal fluid. Progress in discovering the functions of the cerebrospinal fluid began in the age of the Renaissance when, in the year 1490, Leonardo da Vinci presented a wax cast of the ventricular system of the brain, with a high probability that it was based on Galen’s descriptions. However, it was Andreas Vesalius, the author of De humani corporis fabrica, who, in the 16th century, accurately illustrated the ventricles of the brain and noted that they were filled with aqueous humor, not gas. This discovery disproved Galen’s theory of three forms of pneuma .In the years 1741–1744, Emanuel Swedenborg presented a detailed description of cerebrospinal fluid, which was published in 1887. Swedenborg described cerebrospinal fluid as “spirituous lymph” secreted from the atrium of the fourth ventricle into the medulla oblongata and spinal cord . HoweverA few years later, in 1891, the German neurologist Heinrich Quincke described the method of lumbar puncture, enabling the safe collection of cerebrospinal fluid. Quincke performed lumbar puncture for the first time in children with increased levels of cerebrospinal fluid pressure, one of whom suffered from tuberculous meningitis ,7. AdditAs one of the first, William Mestrezat collected data and presented the results of research on cerebrospinal fluid in many neurological diseases. His work in this field was considered a benchmark for many years ,8. The fCerebrospinal fluid is a clear, colorless liquid produced primarily in the choroid plexus of the ventricular system but is also by the interstitial space of the brain and the subarachnoid space ,11,12,132) and water (H2O) to carbonic acid (H2CO3) in a reversible manner. Then, H2CO3 dissociates into hydrogen ions (H+) and bicarbonate ions (HCO3−) [+ ions are transported from the inside of the cell to the cerebrospinal fluid by the sodium-hydrogen exchanger (NHE) transporter. The NHE transporter as an antiporter exchanges one H+ ion for one sodium (Na+) ion [+ ions from inside the cell to the cerebrospinal fluid is carried out by the sodium–potassium pump (ATPase Na+/K+), which exchanges three Na+ ions for two K+ ions [+/K+ ATPase pump also provides energy for other active ion exchanges needed to produce cerebrospinal fluid [+ ions from the inside of the cell to the cerebrospinal fluid takes place with the participation of the inward-rectifier potassium channel (Kir), which is gated by changes in the membrane potential of the cell [3− ions are transported to epithelial cells from the cerebrospinal fluid by the sodium bicarbonate co-transporter (NBCn1) [3− ions are transported from the epithelial cells into the blood by the anion exchange protein 2 (AE2) ion carrier protein (Cl−/HCO3− exchanger) [−) ions that have entered choroid plexus epithelial cells via AE2 are then transported to the cerebrospinal fluid via the Na+/K+/2Cl− , K+/Cl− co-transporter , and by inward-rectifying chloride channel (Clir) and volume-regulated anion channel (VRAC), which are gated by potential cell membrane changes [+ and Cl− ions from the epithelial cells of the choroid plexus into the blood [+ and HCO3− ions into the cell [Cerebrospinal fluid is produced by passive ultrafiltration of the fluid through the capillaries of the choroid plexus and by active transport of ions by the endothelial cells of the choroid plexus ,19. An i (HCO3−) ,16,18. INa+) ion . The tra K+ ions ,21,22. T (NBCn1) . NBCn1 e (NBCn1) . In the changer) . Chlorid changes . The pothe blood . In the the cell . It shouthe cell ,25.2O by aquaporin 1 (AQP1). Aquaporin channels are responsible for regulating the volume of the extracellular space, the circulation of the cerebrospinal fluid, and the absorption of interstitial fluid [2O can be transported independently of the osmotic pressure gradient. It has been shown that about half of the cerebrospinal fluid is produced by the co-transport of water and ions through the sodium potassium chloride co-transporter (NKCC1) channels located in the apical membrane of the choroid plexus epithelial cells [The influx of ions into the cerebrospinal fluid results in the presence of an osmotic pressure gradient, enabling the transport of Hal fluid ,21,26. Tal cells . Figure The cerebrospinal fluid flow consists of a combination of directed and pulsating flow from its production site to the place where it is reabsorbed ,15,21. CReabsorption of cerebrospinal fluid is not as complex as its production process; it occurs through the arachnoid granulations into the venous sinuses of the dura mater and from there it enters the blood . In addiThe choroid plexus controls cerebrospinal fluid secretion, which is innervated by the autonomic, cholinergic, adrenergic, serotonergic, and peptidergic nervous systems . Stimula+/K+. Administration of corticosteroids may reduce the activity of the ATPase Na+/K+, consequently reducing the production of cerebrospinal fluid [Additionally, the volume of cerebrospinal fluid can be regulated by using inhibitors/activators of the relevant membrane proteins of the choroid plexus epithelial cells. The above-mentioned regulation is closely related to the ATPase Naal fluid .The main component of cerebrospinal fluid is water ,30. TherThe main component of cerebrospinal fluid is water (99%), with the remaining part (1%) made up of protein, glucose, ions, vitamins, and neurotransmitters. The composition of cerebrospinal fluid is very similar to that of plasma, except for the difference in protein and ion concentrations ,27,30. TCerebrospinal fluid as a liquid surrounding the brain on all sides primarily protects it against shocks and the risk of damage arising from contact with the skull. The average weight of an adult human brain is about 1500 g, but, due to the presence of the surrounding cerebrospinal fluid and buoyancy, this weight is reduced by 10–15 times ,12,16,21The proper maintenance of CNS homeostasis is ensured by two barriers, the BBB and the blood–cerebrospinal fluid barrier (BCB). The BBB is an anatomical barrier responsible for separating circulating blood from the extracellular space of the brain. The main components of this barrier are endothelial cells of the brain capillaries, pericytes, and astrocytes ,36,37,38The most important elements of the BBB are the endothelial cells lining the inner layer of the capillary wall of the brain. These cells are highly specialized, their intercellular spaces being covered with a large number of expanded connections ,39,40. TAstrocytes are another building block of the BBB. They are mainly responsible for nutrition, neurotransmission, and excretion of metabolic products. Astrocytes are the link between the blood and the brain by connecting one end to capillaries of the brain and the other end to neurons. This neurovascular connection allows for the transmission of signals that regulate blood flow . The endThe last element of the BBB are pericytes, found in the brain as regulators of barrier functions and mediators of neuritis. Pericytes are located near the blood vessels, which facilitate the regulation of the immune and inflammatory response ,39,42. AThe BBB owes its functionality to the presence of specific tight junctions between epithelial cells—these are adherens junctions (AJs) and tight junctions (TJs). On the surfaces of the apical membranes of the endothelial cells of the capillaries of the brain, there are TJs ,44. They2+)-dependent transmembrane glycoproteins. Cadherins bind to beta-catenin and plakoglobin (P120), which then, via beta-catenin, alpha-catenin, vinculin, and radixin, stabilize AJs by binding to the cell cytoskeleton [The second type of connection, thanks to which the BBB can properly fulfill its function, is linked to AJs. They are located between the basement membrane and endothelial cells. They consist of cadherins, which are calcium  and the S100 protein, are used in routine laboratory practice to assess the integrity of the BBB. NSE exists in various dimeric isoforms and consists of α, β, and γ subunits. NSE γ is a glycolytic enzyme found in neurons and endocrine cells. An elevated concentration of NSE in the serum and cerebrospinal fluid is indicative of damage to the nervous tissue, which may result from stroke, epilepsy, hypoxia, or cancer ,50,51,52n damage ,54,55.Alb) [BCB, unlike BBB, is not assigned to a precise location, being functionally related to the choroid plexus. In functional terms, BCB is a series of mechanisms responsible for the diffusion of proteins from the blood to the cerebrospinal fluid. It is formed by epithelial cells of the choroid plexus of the four ventricles of the brain and subarachnoid epithelial structures directed into the cerebrospinal fluid space in the intracranial areas and the spine ,28,36,38Alb) ,56,57,58Alb) is used to assess BCB functionality. It expresses the ratio of the concentration of albumin in the cerebrospinal fluid to the concentration of albumin in the serum [Alb requires that the patient’s blood be drawn into a tube without anticoagulant to obtain serum and cerebrospinal fluid [Alb increases, indicating BCB dysfunction. There is no lower range for QAlb. The QAlb upper range is age dependent and should be calculated using the formula: QAlb = (age in years/15) + 4. However, the formula is only used for people aged 15–60. Physiologically, newborns have an elevated concentration of albumin in the cerebrospinal fluid, and thus an increased value of QAlb. Then, with every passing month, this value decreases and is at its lowest in the 4th month of life. From the 4th month, the value of QAlb increases, and, in children aged 15 years, it is at the level of 5.00 × 10−3 [Alb is determined using a graph showing the relationship between QAlb and age. For people over 60 years of age, the upper range is 8.00 × 10−3 [The albumin quotient  and cerebrospinal fluid (mg/dL) are different because the range of concentrations in these two materials differs. Units must be standardized when calculating Q by 10−3 .Alb (8–25 × 10−3) can be observed in diseases such as immune-mediated polyneuropathy and viral meningitis. A significant increase in QAlb > 25 × 10−3 may indicate purulent meningitis, acute neuroborreliosis, immune-mediated myelitis, or Guillain–Barré syndrome [A mild increase in Qsyndrome ,64.The collection of cerebrospinal fluid is an invasive procedure and may be associated with post-puncture syndrome ,66. The Contraindications associated with the lumbar puncture procedure include local skin infections, abnormalities of the skin or spine in the puncture area, sepsis, and increased intracranial pressure. Coagulation disorders and anticoagulant treatment also disqualify the patient from undergoing this procedure. Lumbar puncture is an invasive procedure and carries the risk of complications in the form of brain herniation. One of the most common complications of puncture is a headache caused by a decrease in pressure in the subarachnoid space ,65,70,74Other complications may include local bruising, nausea, bleeding, and discomfort associated with the procedure. Extremely dangerous is iatrogenic meningitis and paresis of the limbs resulting from the formation of a subdural hematoma. The lumbar puncture procedure may damage the blood vessels with the puncture needle. Contamination of the cerebrospinal fluid with blood is referred to as traumatic puncture (or traumatic tap) and makes it difficult to interpret the result of the laboratory examination of the cerebrospinal fluid ,66,69,74The collection of cerebrospinal fluid by suboccipital puncture is dangerous due to the collection site being close to the medulla oblongata; therefore, it is not routinely performed. Collection of cerebrospinal fluid from the lateral ventricles is performed in infants with unfused fontanelles or intraoperatively in adults through intraventricular drains. If the cerebrospinal fluid was collected by a method other than a lumbar puncture, this information should be included in the referral and the laboratory examination result ,51,79.Cerebrospinal fluid should not be aspirated as hypertension may increase the risk of hernia . To dateIn turn, Gastaldi et al.  suggesteAlb and Glucose Index, respectively [For cerebrospinal fluid collection polypropylene tubes with low protein binding capacity should be used. The use of laboratory plastic or glass may cause protein adhesion, which affects laboratory examination results ,82. Sterectively ,73,81,82ectively  if it isectively . The autectively .Although Paolo Mascagni was the first to describe the cerebral vascular lymphatic system at the end of the 18th century, his discovery was not widely accepted at the time . Thus, fFurther studies have shown that the meningeal lymphatic vessels play an important role in clearing macromolecules from the cerebrospinal fluid and interstitial fluid, transporting them to the deep cervical lymph nodes, and in transporting immune system cells from the CNS to these nodes ,89,90,91Studies conducted thus far suggest that reduced macromolecular drainage and impaired clearance of cerebrospinal fluid by meningeal lymphatic vessels may be the cause of the development of neuroinflammatory and neurodegenerative diseases ,90,92,93To summarize, impaired meningeal lymphatic vessel drainage can contribute to the accumulation of macromolecules, such as amyloid β and α-synuclein in the brain, as well as the removal of neurotropic viruses and tumor cells into cervical lymph nodes. In addition, disrupted meningeal lymphatic vessels can negatively influence the removal of red blood cells from cerebrospinal fluid. Promoting the expansion of functional meningeal lymphatic vessels can be beneficial in treating certain neurological conditions, such as virus infections or brain tumors.Alb, with normal cell counts [Cerebrospinal fluid laboratory examination is an important element in the diagnosis of CNS diseases, e.g., multiple sclerosis, encephalitis, meningitis, brain tumors, Creutzfeldt–Jakob disease, Alzheimer’s disease, and many others. An increase or decrease in various components of the cerebrospinal fluid, such as concentration of total protein, glucose, neurospecific proteins, and percentage of lymphocytes or neutrophils, may indicate the presence of disease or inflammation. In most cases, analysis of the cerebrospinal fluid allows for the correct diagnosis and implementation of appropriate treatment ,102. Forl counts . Evaluatl counts ,104. If l counts . Increasl counts .There are many more examples of the use of cerebrospinal fluid analysis in the diagnosis of CNS diseases. Undoubtedly, the examination of cerebrospinal fluid can help identify biomarkers that indicate the presence or severity of the disease and assess the effectiveness of treatment. In addition, it allows us to understand the pathogenesis and disease mechanisms, which is crucial in discovering new strategies of treatment and therapy for patients with CNS diseases. For this reason, research into the search for new biomarkers that will provide more detailed information on CNS diseases and allow for more effective diagnosis and treatment is extremely important.Research based on omics, which involves large-scale analysis of biomarkers by molecule types such as genomics, proteomics, and metabolomics, is a new direction in disease diagnosis and treatment . Cerebroapolipoprotein E4 (APOE4) allele as the most well-established and significant risk factor for Alzheimer’s disease [clusterin (CLU), sortilin-related receptor-1 (SORL1), complement component receptor 1 (CR1), ATP-binding cassette transporter A member 7 (ABCA7), fermitin family member 2 (FERMT2), major histocompatibility complex class II , bridging integrator 1 (BIN1), phosphatidylinositol-binding clathrin assembly molecule (PICALM), and aquaporin 4 (AQP4) [SNCA, PARK7, PRKN, RAB29, MAPT, BST1, GAK, LRRK2, and HLA-DRB5, among others [Recently, numerous omics research has focused on unraveling the genetic basis of diseases that impact the CNS, such as Alzheimer’s disease, Parkinson’s disease, stroke, multiple sclerosis, and others. This has included genome-wide association studies (GWAS) in particular ,113,114. disease . Other g4 (AQP4) ,116,117.g others ,111,112.APOE. The accuracy of the polygenic hazard score is supported by its correlation with other biomarkers such as cerebrospinal fluid amyloid β and tau protein levels [Studies have shown that many genetic variations are associated with diseases such as Alzheimer’s and Parkinson’s. As a result, researchers have proposed a polygenic hazard score that quantifies an individual’s age-specific genetic risk for these diseases by aggregating the risk across multiple genetic variants ,119. Thin levels ,118,120.LRRK2 G2019S mutations, the most common genetic cause of autosomal dominant Parkinson’s disease. By comparing cerebrospinal fluid proteomes with urinary proteome profiles, researchers have discovered more than 1000 common proteins, including lysosomal proteins, which could improve our understanding of Parkinson’s disease pathogenesis [The use of liquid chromatography–mass spectrometry (LC-MS) in analyzing the cerebrospinal fluid proteome is a powerful technique that enables the quantification of multiple proteins without bias . Yang etogenesis .Metabolomics is a recently developed method for analyzing the metabolites present in cerebrospinal fluid. Proper interpretation of the metabolite data obtained from this analysis, as well as understanding the resulting biochemical changes, is crucial for gaining insight into neuroinflammatory mechanisms, identifying biomarkers, predicting disease progression, and developing effective treatment strategies . Yan et For several decades, researchers have been working to develop an artificial cerebrospinal fluid as a means of reducing the use of clinical liquids such as normal saline and lactated Ringer’s solution in neurosurgery. These fluids can potentially cause brain damage, hence the need for a safer alternative ,131,132.Artificial cerebrospinal fluid is a transparent, cell-free liquid designed to mimic the composition of normal cerebrospinal fluid in terms of its electrolyte balance, glucose concentration, pH, and osmotic pressure. The advantage of artificial cerebrospinal fluid compared to irrigation fluids is primarily due to the pH value, which is similar to the pH of normal cerebrospinal fluid ,135.3− [Some units prepare their own artificial cerebrospinal fluid ,136, but3− ,138. Suc3− ,138. Pre3− . In rece2+ ions to prevent delayed vasoconstriction in patients with subarachnoid hemorrhage. Artificial cerebrospinal fluid modified with nanoparticles turned out to be useful in protecting the spinal cord against ischemia-reperfusion injury in the rat model [2+ and Mg2+, which play a key role in synaptic neurotransmission, but also with a small nanomolar concentration of Zn2+ ions mediating in the prevention of cognitive impairment [There are studies in the literature confirming that the use of artificial cerebrospinal fluid leads to less edema and less cytotoxicity in the parenchyma surrounding the rinsed surfaces ,139 and at model . Some repairment ,143. In pairment  indicatipairment .Cerebrospinal fluid is vital for protecting the CNS by providing support, absorbing shocks, and transporting nutrients and wastes. It plays a crucial role in diagnosing neurological conditions and delivering medication directly to the CNS through intrathecal drug administration. Cerebrospinal fluid examination helps identify biomarkers indicating disease presence or severity, evaluates treatment effectiveness, and enables understanding of pathogenesis and disease mechanisms. Therefore, research centered on searching for new biomarkers to provide more detailed information about CNS diseases is necessary to improve diagnosis and discover new treatment methods.


We hypothesised that change in a magnetic resonance imaging (MRI) biomarker, the apparent diffusion coefficient (ADC) after 14 days of treatment could be a proxy for tumour regression grade (TRG) on pathology. Measurement of the imaging biomarker was standardised across centres. We restricted measurements to liver metastases from colorectal cancer and ensured a standardised chemotherapy approach. We identified and eliminated significant measurement error due to MRI scanner performance. We excluded studies that failed to conform to the imaging protocol or where images contained movement artefact. We ensured stability of the scanners by periodic quality control testing and used a standard, widely used data analysis technique to derive the ADC. Despite these measures, our results showed no significant correlation between ADC and TRG or between ADC and percentage of viable tumour, percentage necrosis, percentage fibrosis or a tumour proliferation index. This may reflect the complex cellular architecture of tumours after treatment.Background: Tumour apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (MRI) is a putative pharmacodynamic/response biomarker but the relationship between drug-induced effects on the ADC and on the underlying pathology has not been adequately defined. Hypothesis: Changes in ADC during early chemotherapy reflect underlying histological markers of tumour response as measured by tumour regression grade (TRG). Methods: Twenty-six patients were enrolled in the study. Baseline, 14 days, and pre-surgery MRI were performed per study protocol. Surgical resection was performed in 23 of the enrolled patients; imaging-pathological correlation was obtained from 39 lesions from 21 patients. Results: There was no evidence of correlation between TRG and ADC changes at day 14 (study primary endpoint), and no significant correlation with other ADC metrics. In scans acquired one week prior to surgery, there was no significant correlation between ADC metrics and percentage of viable tumour, percentage necrosis, percentage fibrosis, or Ki67 index. Conclusions: Our hypothesis was not supported by the data. The lack of meaningful correlation between change in ADC and TRG is a robust finding which is not explained by variability or small sample size. Change in ADC is not a proxy for TRG in metastatic colorectal cancer. Diffusion-weighted magnetic resonance imaging (DW-MRI) provides quantitative biomarkers that are used to probe tumour microstructure based on restrictions to water proton diffusion from intra- and extra-cellular structures such as cell membranes and collagen fibres. Commonly used DW-MR protocols in the body allow derivation of an apparent diffusion coefficient (ADC), which reflects water movement over typically 10–40 µm during 10–100 ms; this predominantly represents diffusion in the extravascular extracellular space or in local capillary blood flow. Thus, ADC can be used as an indicator of pathogenic processes, or response to therapeutic interventions. As a response biomarker, ADC could potentially indicate tumour cell death following radiotherapy, oncolytic or cytotoxic therapy as increases in ADC result from loss of cell membrane integrity [The effectiveness of any predictive or response biomarker depends on several factors. First, the repeatability of the biomarker must be established in order to understand the magnitude of change that must be observed to be certain that it represents a true biological effect. Second, it is essential to understand, and compensate for, aspects of biomarker estimation which may cause variations in biomarker measurements and biomarker reproducibility. Third, it is important to confirm that the putative biomarker truly reflects the biological/physiological process which it is believed to demonstrate . The valA number of small prospective studies describe the use of ADC in assessing response of colorectal liver metastases compared to standard Response Evaluation Criteria In Solid Tumours (RECIST) criteria. These studies failed to detect correlation between changes in ADC and lesion size change after 14 days of treatment , and notMulticentre assessment of ADC has previously been challenging. Variations in imaging sequence implementation across scanning platforms, modified acquisition techniques designed to compensate for physiological motion, and variation in analysis techniques ,7 affectThis was a prospective, multicentre, single-arm imaging trial listed on clinical trials.gov (NCT02355353). All patients gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the ethics committees of the individual institutions (EORTC 1423). Patients with histologically confirmed clinical stage IV metastatic colorectal cancer (mCRC) with metachronous or synchronous liver metastases who were candidates for neoadjuvant therapy were eligible. Three pre-operative treatment regimens were considered acceptable to facilitate recruitment: chemotherapy alone, chemotherapy + anti-angiogenic agent, or chemotherapy + monoclonal antibody. Twenty-six patients  aged 45–82 years (mean 64.85 ± 9.12 years) were recruited, gave written, informed consent, and started the study treatment.The design of the study is shown in Metastatic lesions were identified on the baseline MR scan. All individual metastases, greater than 1 cm in diameter were identified and the hepatic lobe from which the lesion was thought to arise was noted. Each lesion was marked on the original images and given a unique identification number. These annotated images were subsequently used for lesion identification by both the image analysis and surgical teams.The primary objective was the correlation between the percentage of ADC change at day 14 relative to baseline and tumour regression grade (TRG) in the surgical resection specimen.To measure the variability of test–retest ADC measurements at baselineTo correlate pre-operative (post-treatment) ADC measurement and TRGTo correlate pre-operative (post-treatment) ADC measurement and tumour tissue cellularity/density, necrosis, and proliferation (Ki-67)Secondary objectives were the following:Scanner QC tests were performed at each centre before the centre was allowed to recruit. A diffusion phantom was constructed and supplied to each centre ; detailsCentres and scanner types included are presented in The QC guidelines were based on pooled group performance for each metric on the initial QC  scan froThe central scanning protocol consisted of standardized T1- and T2-weighted axial images for anatomical localization together with a geometrically matched diffusion weighted imaging sequence. Image acquisition protocols are shown in No changes were allowed in field-of-view, pixel size, acquisition matrix, b-values, number of slices, fat suppression technique, diffusion gradient mode, slice gap, or number of signal acquisitions. Scans which demonstrated any such deviations were excluded from the study.early and ∆ADCearly respectively) and between baseline and the pre-operative scan (∆TVlate and ∆ADClate respectively).Parametric maps of ADC were calculated voxelwise for the whole data volume using a mono-exponential fit model implemented in the ADC plugin in Osirix MD . All metAt surgery, tissue was collected from all resected lesions. The lesion was identified according to the code attributed on the original pre-surgical scans. Haematoxylin and eosin (H&E) stained slides were used to provide data on tissue cellularity.Pathological response was independently determined on a lesion-by-lesion basis at a central reference laboratory. This was carried out independently by two experienced histopathologists (CJ and MU-N) and discrepancies reconciled by consensus discussion and agreement. The pathological response rate was graded for five tumour response groups using the criteria established by Rubbia-Brandt . The proAnalysis of Ki-67 IHC stained slides provided data on tumour proliferation. The Ki-67 status was expressed as the percentage of Ki-67 positive nuclei to all tumour nuclei.early defined on ADCmean and ADCmax. The primary endpoint measures for pathology were TRG by Rubbia-Brandt criteria. Percentage of viable tumour and necrosis, proliferative activity (Ki-67 index), and changes in tumour volume were secondary endpoints. In order to demonstrate with 95% confidence interval (one sided) that the correlation between the imaging biomarker change and the pathological response is <−0.5 (H0: rho ≥ −0.5) with 90% power if the true correlation is −0.8 (H1: rho < −0.5), 31 lesions were needed.Co-primary endpoints for imaging were ΔADCearly, and ∆ADClate) and TRG was also examined using Spearman rank correlation. A sensitivity analysis to include the dependency of lesions from the same patient was performed with a repeated measures model using the standardized ranked variables. The one-sided type I error was fixed at 1% for all secondary and exploratory analyses. When relevant, equivalent two-sided 98% confidence intervals were reported. The statistical package used was SAS 9.4 (STAT 14.3).The relationship between imaging parameters (ADCmean and ADCmax) and histological features  were examined using Spearman rank correlation with Fisher transformation. The relationship between baseline  showed less than 5% deviation through the phantom quality control process (details in Single-rater reproducibility of tumour volume showed a mean difference in percentage tumour volume of (0.4 ± 7.9)% with 95% confidence limits of ±13.2%. This variation was driven largely by two very small lesions with high reproducibility errors: when these were removed the 95% confidence limit width became ±7.4%. Inter-rater reproducibility showed a mean difference in tumour volume of (0.48 ± 8.3)% with 95% confidence interval ±14.6%. When the two small lesions were removed this became ±8.2%. The group CoV between test and retest mean ADC for observer A was 8.8% ± 3.4%. For observer B, the CoV for mean ADC was 7.6% ± 2.1%.Patient recruitment occurred at 8 of the 10 centres. A total of 29 patients were registered for the study of which two were ineligible. One further patient declined chemotherapy and 26 were therefore entered into the trial. Eighteen of the 26 patients received chemotherapy alone, seven received a combination of chemotherapy plus another drug  and one patient commenced chemotherapy but panitumumab was added after one cycle. Statistical analysis was performed on all patients together and separately on the chemotherapy only cohort.The patient group consisted of 14 men and 12 women with a median age of 64.5 years (range: 45–82 years). The chemotherapy-only patient cohort consisted of 10 men and 8 women, with a median age of 64.5 years (range: 45–82 years). The primary diagnosis was colon cancer in 16/26 and rectal cancer in 10/26 cases. The histological grade and TNM staging at first diagnosis are shown in Surgical resection was eventually performed in 23 patients . The majority of the patients had more than one lesion resected: however, for one patient the day 14 DW-MRI was not available and for another patient no surgical specimen was available for histopathology. Therefore, in total, there were 46 evaluable lesions from 21 patients for the primary objective.3 at baseline , was unchanged after 14 days ranging from 0.3–506.1 cm3 , and decreased prior to surgery ranging from 0–254.1 cm3 . Tumour volume distribution was skewed towards the right, principally by a single extremely large lesion.Baseline scanning included 82 lesions. The number of measured lesions decreased with time. Tumour volume ranged from 0.3–501.2 cmBaseline measurements of mean and maximum ADC are shown in −3 mm2/s with a range of 0.7–2.7 × 10−3 mm2/s. The ADCmax and ADCmean increased for some patients between baseline and day 14, while for others it decreased. Overall, for all patients, ADCmean increased at day 14 with ∆ADCearly of 4.3% and a range of −38.3% to 94.8%. In the chemotherapy-only cohort ADCmean increased at day 14 with ∆ADCearly of 4.9% and a range of −26.5 to 94.8%. ADC values at day 14 showed no significant difference from baseline (p = 0.94). Values of ∆ADCmeanearly and ∆ADCmeanlate are shown in Baseline ADCmean had a median value of 1.0 × 10early and ∆ADCmeanlate are shown in For patients undergoing surgery (n = 23), values of ∆ADCmeanTwenty-seven of 48 lesions were graded as TRG4, 7 as TRG3,12 as TRG2 and 1 as TRG1. In one case the lesion was too small to grade. There was no difference between TRG in the chemotherapy-only and combination therapy groups. There was very wide variation in lesion surface area, fibrosis, necrosis, and the total surface area of viable tumour cells .p = 1.0) between TRG and ∆ADCmeanearly (study primary objective). In scans acquired one week prior to surgery, there was no significant correlation between ADCmax or ADCmean and percentage of viable tumour, percentage necrosis, percentage fibrosis, or Ki-67 index (There was no evidence of significant correlation (67 index .Our hypothesis that an increase in ADC after 14 days of neoadjuvant chemotherapy and measured immediately before tumour resection would reflect underlying histological features of tumour response as measured by TRG was not supported by the data. At a pathophysiological level, a relationship between ADC and percentage tumour necrosis is to be expected. As free water molecular motion quantified by the ADC is affected by the structure of the tumour microenvironment, it is expected that in response to therapy, ensuing cell death will lead to loss of cellular integrity with consequent increase in diffusion. ADC therefore has been widely proposed as an early response biomarker for chemo- and radiotherapy ,14. Our The stability and repeatability of ADC measurements in this multicentre setting, which critically affects the performance of a biomarker , should Other factors which can affect repeatability and contribute to measurement error are the lesion segmentation process and the tumour volume being segmented. The 2D methods result in more variability of the derived biomarker because of slice selection bias , whereasWe made no attempt in the current study to compensate for the effects of physical motion on the estimation of ADC except for excluding patients with subjective evidence of image degradation in the quality control review. As ADC is estimated by curve fitting using single pixel values of images acquired with varying strengths of gradient, physiological motion during the acquisition can cause significant misregistration between images and can introduce error into estimates of ADC respiratory triggering or the use of navigator echo techniques can mitigate motion effects when compared to free-breathing studies . SimilarOur study has limitations: the sample size was small despite the prevalence of liver metastases in colorectal disease. This was because of the need to specifically include patients suitable for metastatectomy who consented to undergoing neoadjuvant chemotherapy. The strict criteria which also excluded the use of certain neoadjuvant agents such as anti-angiogenic agents and monoclonal antibodies because of potential confounding effects on pathological response  also negWe demonstrated that it is feasible to conduct a rigorous, quality controlled multicentre study using ADC within a clinical trial setting; when applied in clinical practice this should enable personalised therapy. Nevertheless, we did not demonstrate any significant relationship between early changes in ADC induced by therapy and TRG and we found there is no relationship between tumour ADC measured in the post-therapy setting and common histological features. We believe that this is likely to reflect, at least in part, the complex structure of the tumour micro-environment following therapy.


Funding statement. The section “the XL Famous Traditional Chinese Medicine Inheritance Studio from the Traditional Chinese Medicine Bureau of Guangdong Province (Grant No. 201805)” is incorrect. It should be “the scientific research project of Traditional Chinese Medicine Bureau of Guangdong Province (20201092).” The correct Funding statement appears below.In the published article, there was an error in the “This research was funded by grants from the “Double First-Class” And High-level University Discipline Collaborative Innovation Team Project of Guangzhou University of Chinese Medicine (Grant No.2021XK16), the Guangdong Provincial Department of Education Innovation Team Project (Grant No.2018KCXTD007), the Scientific Research Project of Guangdong Provincial Bureau of Traditional Chinese Medicine (Grant No.20212056), the Key-Area Research and Development Program of Guangdong Province (Grant No. 2020B1111100002), the National Natural Science Foundation of China (Grant Nos.81973814 and 81904132), the Natural Science Foundation of Guangdong Province (Grant No. 2017A030310129), the Natural Science Foundation of Guangdong Province (Grant No. 2020A1515010589), the scientific research project of Traditional Chinese Medicine Bureau of Guangdong Province (20201092), the Construction Project of Respiratory Department National Clinical Medical Research Center (Grant No. 2110200309), 2018 Guangzhou University of Chinese Medicine National University Student Innovation and Entrepreneurship Training Project (Grant No. 201810572038), 2020 National College Student Innovation and Entrepreneurship Training Project of Guangzhou University of Chinese Medicine (Grant No. 202010572001), the Student Learning Team Incubation Project of Innovation Academy from The First Affiliated Hospital of Guangzhou University of Chinese Medicine (Grant No. 2018XXTD003), and the Technology Research of COVID-19 Treatment and Prevention and Special Project of Traditional Chinese Medicine Application-Research on the platform construction for the prevention and treatment of viral infectious diseases with traditional Chinese medicine (Grant No. 2020KJCXKTYJ-130).”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.