Synovial Fluid Proteomics and Serum Metabolomics Reveal Molecular and Metabolic Changes in Osteoarthritis

Research Article

Synovial Fluid Proteomics and Serum Metabolomics Reveal Molecular and Metabolic Changes in Osteoarthritis

  • Vishal Chandra 1
  • Tashfeen Ashraf 2
  • Pramod Yadav 1,3*
  • Vikas Raghuvanshi 1,4

*Corresponding Author: Pramod Yadav, Department of AFAF, Amity University Uttar Pradesh, Noida Campus, 201313, India.

Citation: Vishal Chandra, Tashfeen Ashraf, Pramod Yadav, Vikas Raghuvanshi, (2024), Synovial Fluid Proteomics and Serum Metabolomics Reveal Molecular and Metabolic Changes in Osteoarthritis, Clinical Research and Clinical Trials, 9(2); DOI:10.31579/2693-4779/167

Copyright: © 2024, Pramod Yadav. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: 29 October 2023 | Accepted: 25 November 2023 | Published: 08 January 2024

Keywords: metabolomics; mass spectrometry of synovial fluid; biomarkers; joint disease; cartilage degeneration

Abstract

Background: Osteoarthritis (OA) is a common joint disorder with a complex and multifactorial pathogenesis. Proteomics analysis using two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) enables high-throughput identification of differentially expressed proteins related to OA. However, the etiology, pathophysiology, and early diagnostic markers of OA are still poorly understood. Methods: Synovial fluid protein biomarkers were compared between OA patients and healthy controls. It was fractionated using DEAE cellulose and Sephadex G-200 columns, followed by SDS‒PAGE and 2D-PAGE for visualization and identification. Mass spectrometry and Mascot were used for protein analysis, and serum metabolite profiles were also investigated using 1D 1H CPMG NMR spectra. Multivariate data analysis, including PCA and PLS-DA, was performed to detect metabolic differences between groups. 

Results: Proteomics analysis revealed differential expression of synovial fluid proteins, such as serine protease inhibitors, complement components, and apolipoproteins, which may be involved in inflammation and cartilage breakdown. Additionally, serum metabolite profiles differed significantly between OA patients and controls, involving amino acid, lipid, glucose, and energy metabolism. The pathway analysis indicated disruption of the metabolic pathways associated with these metabolites. Conclusions: This study provides insights into the molecular and metabolic changes in OA. Protein biomarkers and serum metabolite alterations enhance the understanding of OA pathogenesis and offer potential opportunities for early diagnosis and disease management. Further validation and translation of these findings into clinical applications are needed for improved OA detection and intervention strategies.

Highlights

-  Serum metabolite profiles reveal metabolic alterations in OA patients.

-  Pathway analysis shows disrupted metabolic pathways in OA patients.

-  Protein biomarkers and metabolites enhance the understanding of OA pathogenesis.

-  Potential diagnostic and prognostic markers for OA detection and management.

Introduction

Osteoarthritis (OA) is a degenerative joint disease that affects the articular cartilage, and its characteristics are increased friction, wear between bones, pain, swelling, stiffness and reduced mobility [1]. Among these, pain is a common symptom of OA, but its origin is unclear since cartilage lacks nociceptors. Morning stiffness is another symptom, but it lasts less than 30 minutes, and patients may also experience joint instability or locking [2,3]. According to the WHO, OA is expected to be the fourth leading cause of knee disability by 2024 [4]. Globally, more than 100 million people suffer from OA, and it has a higher prevalence in women than men [5]. The prevalence of knee OA increases with age and varies across regions, ranging from 7.5% in China [6] to 25% in northern Pakistan [7]. In India, OA is the second most prevalent rheumatologic problem, with a prevalence of 22% to 39%, and affects 60.6% of the urban population and 5.78% of the rural population [8]. Among people aged 65 years and above, OA accounts for 50% of all disability diseases [9]. The pathogenesis of OA is complex and multifactorial, involving the interaction of cartilage, subchondral bone, periosteum, joint capsule, and synovial fluid [10]. Physical examination is essential for diagnosis, and plain radiography can confirm OA in some cases, but advanced imaging techniques such as magnetic resonance imaging (MRI) are required for accurate diagnosis, especially if meniscal injury is suspected. However, these techniques are not affordable for many patients, resulting in underdiagnosis of OA. Despite considerable progress in OA research, its pathogenesis, etiology and progression remain poorly understood. Studies have reported abnormalities in the immune response and immune cells of OA patients, such as altered T-cell subsets. These abnormalities may play a role in the pathogenesis of OA and modulate the inflammatory response in the synovial membrane (SM), leading to cartilage degradation [11]. Despite extensive research with multiple approaches, our understanding of OA etiology and pathophysiology and our ability to diagnose it at an early stage are limited [12]. The present study was undertaken to investigate the comparative analysis of protein biomarkers occurring in the synovial fluid of patients and healthy controls.

Methodology

Inclusion and exclusion criteria of control and subject

We selected control subjects free of any clinical or radiological signs of joint disease, comorbidities, obesity, hypersensitivity, or cardiovascular disease. We used the Kellgren and Lawrence (K-L) score, the WOMAC score, the VAS score, and the American College of Rheumatology (ACR) classification to screen and evaluate OA patients. Only patients who met six or more criteria were included. Patients had knee pain (asymmetrical) lasting more than six months, stiffness (less than 30 minutes), swelling, cripitus, tenderness on the medical side of the joint, X-ray (Grade II-78 and Grade III-22), normal ligament stability, decreased motion, duration of symptoms (3.3±1.49 years), range of movements (0-140/42± 20.2), VAS pain on movement (4.7±1.4 cm) and WOMAC score of patients (difficulty 31.0±8.1; pain 9.2±2.2; stiffness 4.2±1.3 and total 44.2±9.8). We excluded patients with infectious diseases such as diabetes mellitus, hypertension, thyroid dysfunction, neurological disorders, cancer, or other forms of arthritis. We also excluded patients with early OA (<2>). The current study was approved by the Institutional Ethical Committee (CSJMU/BSBT/BT/EC-20), and all participants provided written informed consent.

Synovial fluid protein analysis

Synovial fluid was obtained from patients and healthy controls by an orthopedic doctor and diluted with 50 mM Tris-HCl buffer (pH 8). The diluted samples were stored at 4°C and applied to a DEAE cellulose column with a linear gradient of 0-500 mM NaCl (250 ml) at a flow rate of 84 ml/h. The fractions were collected and reapplied to a Sephadex G-200 column equilibrated with Tris-Cl buffer (50 mM and pH 7.4) and NaCl (100 mM) at a 45 ml/h flow rate. The eluted proteins were precipitated with ammonium sulfate, dissolved in a buffer with protease inhibitors, and used for SDS‒PAGE and 2D-PAGE [13–16]. For the first dimension in 2D-PAGE, the protein concentration was determined by the Bradford method. Then, 200 µg of protein was mixed with 5 µl of 10% SDS and 5.3 µl of 1 M DTT, boiled at 100°C for 5 minutes, and placed on ice. Then, 100-120 µl of rehydration buffer (with 0.5 g of total protein extraction buffer, 0.5 ml of total protein extraction diluent, 50 µl of DTT, 100 µl of protease inhibitors, and 0.2% ampholytes) was added and loaded onto an IPG strip for active rehydration overnight. After 11-16 hours of active rehydration, the strip was removed, wiped off with tissue paper, and placed on the power pack with the correct orientation of electrodes (+/-). The strips were transferred to the top of 12

Results

Protein expression analysis by 2D-PAGE and MS/MS

The protein spots from the OA profile digested with trypsin were expunged from the 2D gel and analysed by MALDI-MS/MS. Many peptides and proteins were identified by searching the MascotTM database (see Figure. 1),


 

 

AccessionProteinModifications/functionpIMW
[kDa]
#Alt.
Protein
ScoresSC [%]RMS90
[ppm]
AACT_HUMANAlpha-l-antichymotrypsin sapiensOxidation (inhibitor)5.347.61339.6 (M:339.6)16.540.27
ANT3_HUMANAntithrombin-IIINonvitamin K-dependent protease6.352.6156.2 (M:56.2)2.639.85
AIBG_HUMANAlpha-lB-glycoproteinUpregulated in adenocarcinoma-unknown function5.654.2121.1 (M:21.1)1.641.8
APOA1_HUMANApolipoprotein A-ICholesterol metabolism5.630.81172 (M:172.0)22.523.66
AIBG_HUMANAlpha-lB-glycoproteinCarbamidomethyl/Upregulated in adenocarcinoma-unknown function5.654.21705.7 (M:705.7)38.29.87
CO9_HUMANComplement component C9 C4b-binding protein alphaComplement cascade5.463.1150.3 (M:50.3)2.139.23
C4BPA_HUMANchainComplement cascade7.267115.1 (M:15.1)1.840.78
CO3_HUMANComplement C3Oxidation/Complement cascade61871313.7 (M:313.7)4.124.23
CSN2_HUMANCOP9 signalosome complex subunit 2Ubiquitin regulator5.451.6117.0 (M:17.0)2.3763.59
EFCB7HUMANEF-hand calcium-binding
domain-containing protein 7
Carbamidomethy Ucytoplasmic calcium sensor671.9131.6 (M:31.6)1.644.1
FIBA_HUMANFibrinogen alpha chainAct as DAMPs5.794.9182.0 (M:82.0)3.140.02
HBB_HUMANHemoglobin subunit betaOxidation/blood pigment6.7165187.8 (M:187.8)28.614.73
HEMO_HUMANHemopexinCarbamidomethyl, Oxidation/inflammation
induced acute phase protein
6.551.61381.8 (M:381.8)32.739.92
HRG_HUMANHistidine-rich glycoproteinCarbamidomethyl/roles in immunity, coagulation7.159.51169.3 (M:169.3)10.139.27
IGHA1_HUMANIg alpha-1 chain C regionCarbamidomethyl/immunity6.137.62235.4 (M:235.4)21.840.36
KV311_HUMANIg kappa chain V-III region IARC/BL41immunity6.214.1180.6 (M:80.6)12.523.77
IGHG1_HUMANIg gamma-1 chain C regionCarbamidomethyl/immunity8.536.1261.5 (M:61.5)7.923.62
LV_l02_HUMANIg lambda chain V-I region HAImmunity9.111.9256.3 (M:56.3)18.824.64
TRFM_HUMANMelanotransferrinCarbamidomethyl/Role in melanoma cell proliferation and tumorigenesis5.680.2141.6 (M:41.6)1.8780.36
OSGI2_HUMANOxidative stress-induced growth inhibitor 2Oxidation/apoptotic regulator756.6116.2 (M:16.2)1.61076.69
THRB_HUMANProthrombinBlood clotting5.670131.5 (M:31.5)1.67.97
KS6A3_HUMANRibosomal protein S6 kinase alpha 3Oxidation/Mediates cell survival6.483.7117.4 (M:17.4)1.231.89
RMD2_HUMANRegulator of microtubule dynamics protein 2Role in signaling6.147.4116.5 (M:16.5)4.64.1
RABXS_HUMANRab5 GDP/GTP exchange factorInvolved in signaling6.479.3117.2 (M:17.2)1.8632.58
RB27B_HUMANRas-related protein Rab-27BInvolved in vesicular fusion and trafficking5.424.6115.1 (M:15.1)5774.92
ARRS_HUMANS-arrestinRole in retinal photoreceptorcells6.145.1116.4 (M:16.4)3.248.05
TRFE_HUMANSerotransferrinOxidation/uptake of transferring bound iron6.87714161.6 (M:4161.6)63.810.29
TMM78_HUMANTransmembrane protein 78-4.915.2118.1 (M:18.1)5.91229.9
VTDB_HUMANVitamin D binding proteinBone metabolism5.452.9119.5 (M:19.5)2.310.76


 

[(PE: protein existence, SV: sequence version, MW [kDa], pI: isoelectric point, Score: 

Mascot score, SC: sequence coverage, RMS90 [ppm]: root mean square (RMS.)]

  1.  and proteins were further classified according to the pathways in which they have major roles (see Annexture 2). Annex 1 shows 29 differentially expressed proteins with a score of more than 15. No disease duration-dependent difference in the expression profile was observed. Mass spectrometric analysis indicated changes in the abundance of complement


 

  1.  Annexture 2. List of OA disease-associated proteins and their classification.


 

 

Serine protease inhibitors/signalling proteins

Bone metabolism/

pathway regulators

Inflammation and immunologic cascadeOxidative stressCholesterol metabolism
Alpha 1Vitamin D bindingAlpha 1B glycoproteinHemopexinApolipoprotein A
antichymotrypsinproteinApolipoprotein A1TransmembraneEF hand
Antithrombin IIIZinc finger and BTBFibrinogen alpha chainprotein78calcium binding domain
Hemopexindomain protein 45Rab5 GDP/GTP exchangeOxidative 
Prothrombin factorstress-induced 
Serotransferrin S-arrestingrowth 
Melanotransferrin Complement C3inhibitor 2 
COP9 signalosome Complement component C9  
complex subunit 2 C4 binding protein α chain  


 

components C3 and C4b and the immunoglobulin constant region. These proteins may play a role in OA pathogenesis; however, no direct disease-specific proteins were detected in this study. 

Serum metabolite expression analysis by 1D 1H CPMG NMR

 

  1. 2D-PAGE analysis of OA patients. A) Control; B) and C) OA patient profiles.


 

The spectra (Fig. 3) displayed 1H NMR signals mainly from small metabolites with intense signals from lipoproteins, phospholipids,

unsaturated lipids, choline metabolites, N-acetyl glycoproteins, glucose, lactate and amino acids. No major differences between the OA and control groups were observed by visual comparison. Hence, multivariate data analysis was performed on the NMR spectra to reveal the serum metabolic alterations caused by OA. The serum metabolic patterns of 10 grade IIIII OA patients and sex-matched normal controls were analysed. The study subjects were selected to reduce the confounding variables (see Annexure 3). Fig. 3 shows that the OA group was clearly discriminated from the control group along the PC1 direction, indicating distinct characteristics of OA serum. This method also detected outliers outside the 95% confidence region of the PCA model. We then applied the supervised clustering method PLS-DA to examine the subtle metabolic variations among the groups. The quality of 

each model was assessed by the parameters R2 and Q2, which are shown in the respective score plots in Figure 3(B). The model quality parameters R2 and Q2 were significantly high (R2, Q2 > 0.7), indicating satisfactory fit and good predictive power of the PLS-DA models (constructed from CPMG spectra). The PLS-DA score plots also showed that the OA and control groups were well clustered and separated, reflecting significant differences in the biochemical composition profiles of serum metabolites in OA patients and normal controls. The metabolites responsible for the discrimination were identified using the VIP and p < 0>

  1. Annexture 2. List of OA disease-associated proteins and their classification.


 

Serine protease inhibitors/signalling proteins

Bone metabolism/

pathway regulators

Inflammation and immunologic cascadeOxidative stressCholesterol metabolism
Alpha 1Vitamin D bindingAlpha 1B glycoproteinHemopexinApolipoprotein A
antichymotrypsinproteinApolipoprotein A1TransmembraneEF hand
Antithrombin IIIZinc finger and BTBFibrinogen alpha chainprotein78calcium binding domain
Hemopexindomain protein 45Rab5 GDP/GTP exchangeOxidative 
Prothrombin factorstress-induced 
Serotransferrin S-arrestingrowth 
Melanotransferrin Complement C3inhibitor 2 
COP9 signalosome Complement component C9  
complex subunit 2 C4 binding protein α chain  


 

3. [The terms ‘up’ and ‘down’ denote elevated and reduced metabolite levels in OA patients compared to normal controls. 4.(AUC: Area under curve (receiver operating characteristic curve), VIP: Variable importance in projection (for 

 

5. quantitative estimation of discriminatory power of each individual feature).


 

 

  1. 2D-PCA. (A) Partial least square discriminant analysis (PLS-DA) (B) score plots.


 

  1. [CPMG spectra showing clear statistical separation between OA (represented by blue triangles) and normal control (NC) samples (represented by black squares). Each circle and triangle represent one subject. The validation parameters (R2 and Q2) corresponding to the PLS-DA model are also displayed in their score plots]


 

  1.  
  2. Stack plot of cumulative 1D 1H CPMG NMR spectra (A) from δ4.6–δ0.7 and (B) δ8.5–δ5.1 ppm) obtained for sera of OA patients (red) and normal controls (blue).

 


 

Heatmaps Figure. 4 shows the heatmaps for different metabolites that distinguish the OA group from the control group (upregulated and downregulated metabolites are shown in red and cyan, respectively). Consistent with our serological data, we found high serum creatinine and a low HDL/LDL ratio in OA by NMR analysis. OA is typically associated with dyslipidemia and has high serum creatinine and low uric acid, as identified by serological analysis. Using a nonparametric Mann‒Whitney test, we quantified the differential abundance of metabolites and found that most of them were statistically significant (p < 0>


 

 


 

3.2.2: ROC curves 

The area under the ROC curve reflects the discriminatory ability (0.5 indicates no discrimination; 1 indicates perfect discrimination). The AUC values ranged from 0.95 to 0.55 (see Figure. 5), indicating that these metabolites could be potential biomarkers for the clinical evaluation and surveillance of such patients. Figure 5 depicts representative ROC curves for some of the serum metabolites that exhibited significant changes in OA patients and their corresponding box plots (from the univariate analysis).


 

 

Figure 6.  ROC curves along with their respective box plots.

 


 

[Respective box plots of the significant metabolites that decreased or increased in the OA patients compared to the control group derived from the CPMG 1H NMR spectra. Boxes denote interquartile ranges, lines denote medians, and whiskers denote 10th and 90th percentiles.]

3.2.3. Metabolic pathway by ORA

Fig. 6 summarizes the pathway analysis and MSEA in MetaboAnalyst results. Five important metabolic pathways (protein biosynthesis, amino acid metabolism, glucose-energy metabolism) were found to be disturbed. The metabolic pathways associated with the identified combinations of metabolites are biased due to limited metabolites detected by NMR in the serum.


 

 

Figure 2.A diagram of a pathway impact by ORA.


 

[The analysis was performed by using a pathway library restricted to Homo sapiens, and p values for ORA represent hypergeometric tests. Test p value (vertical axis, colour intensity) and impact factor (horizontal axis, circle size)].

Discussion

4.1. Proteomics profile analysis by mass spectrometry

This study proposed that some proteins were overexpressed in OA patients, but none of these proteins were directly implicated in the pathophysiology of the disease (see Annexure 3). We identified several proteins, such as serine protease inhibitors, high levels of ATIII, and proteins related to lipid transport or protein binding, such as apolipoproteins, immunoglobulins, transmembrane proteins and transcriptional proteins. These proteins are involved in cartilage degradation or protein synthesis. Olsen et al. reported that the levels of APO-A1 in the synovial fluid of OA patients are higher due to diffusion and production by chondrocytes and FLSs [26]. Our results confirmed the role of APO-A1 in inflammation with increased expression of fibrinogen protein in OA and confirmed that these proteins can trigger TLR-4-dependent macrophage production of inflammatory cytokines and growth factors. This study reports high expression and activation of complement in OA joints. It also identified the proinflammatory complement components C3, C4b, and C9. C9 components from MAC were aberrantly expressed in OA, and C3 and C4b were higher in the early stage of OA. Hemopexin (HPX) is an acute phase protein that suppresses the adhesion of leukocytes and the release of cytokines from macrophages. Its high level suggests its role in OA. We also identified proteins involved in extracellular matrix, cartilage, and bone metabolism. Rab5 GDP/GTP exchange factor expression supports the role of the Ras superfamily in OA progression.

4.2. Metabolite analysis by NMR

The results of this study indicate that early metabolic changes in OA can be detected in serum by NMR. According to a study, degenerative joint disease can affect the synovium, as it becomes hypoxic [27]. This is also observed due to increased lactate concentration. This study found an increased creatinine concentration that indicates altered metabolism in early OA. Similar results have been reported for the serum metabolite profile in a sheep model of OA [28]. We observed increased glutamine and glutamate concentrations in the serum of OA patients. Glutamine confers chondrocyte resistance to heat stress and NO-mediated apoptosis [29]. Hence, glutamine elevation may reflect chondrocyte adaptation to various stressors during disease progression. Choline augmentation might indicate lipid catabolism from articular cartilage and leakage of its products into the bloodstream due to synovial membrane permeability enhancement. Alternatively, increased choline could result from the breakdown of Hoffa’s pad or phospholipids in the joint [30]. We also found reduced leucine and histidine in the serum of OA patients. Comparison of spectral profiles of controls and patients reveals that cartilage breakdown continues with increased glycerol and hydroxybutyrate. Glycerol synthesis indicates triglyceride degradation in various tissues. Moreover, the decreased HDL/LDL ratio and PUFAs reflect the impact of free radical generation through lipid peroxidation, leading to high oxidative stress and inflammation [31].

Conclusion

Proteomics analysis using 2D-PAGE coupled with mass spectrometry revealed differentially expressed proteins involved in inflammation, oxidative stress, and the immune response, suggesting a complex interplay of factors in OA pathogenesis. NMR-based metabolomics analysis identified altered metabolic patterns in the serum of OA patients, indicating hypoxia, inflammation, and lipid metabolism disruption. Increased lactate and creatinine levels suggest tissue hypoxia and muscle breakdown near the affected joint. Alterations in amino acids, lipoproteins, and glucose-energy metabolism indicate disrupted metabolic pathways in OA patients. The integration of proteomics and metabolomics data provided a comprehensive view of the disease, highlighting potential targets for further investigation. The identified proteins and metabolites could serve as candidates for future diagnostic or prognostic biomarkers for OA. Further studies are needed to validate these findings and improve our understanding of OA pathophysiology and early detection.

Abbreviation

 

OA-Osteoarthritis
MS-Mass Spectrometry
2DE-Two-Dimensional Gel Electrophoresis
SDS‒PAGE-Sodium Dodecyl Sulfate‒Polyacrylamide Gel Electrophoresis
NMR-Nuclear Magnetic Resonance
PCA-Principal Component Analysis
PLS-DA-Partial Least Squares-Discriminant Analysis
WHO-World Health Organization
K-L-Kellgren and Lawrence
WOMAC-Western Ontario and McMaster Universities Arthritis Index
VAS-Visual Analog Scale
ACR-American College of Rheumatology
DEAE-Diethylaminomethyl
SM-Synovial Membrane
MRI-Magnetic Resonance Imaging
RA-Rheumatoid Arthritis
VIP-Variable Importance in Projection
AUC-Area Under Curve
FDR-False Discovery Rate
HDL-High-Density Lipoproteins
LDL-Low-Density Lipoproteins
PUFA-Polyunsaturated Fatty Acids
ORA-Over-Representation Analysis
DAMPs-Damage-Associated Molecular Patterns
TLR-4-Toll-like Receptor 4

Declaration(s) Competing interests: The authors report no conflicts of interest.

Author 1 declared no conflict of interest.

Author 2 declared no conflict of interest.

Author 3 declared no conflict of interest.

Author 4 declared no conflict of interest.

Funding

This research was unfunded by any public, commercial, or not-for-profit agencies

Ethical Approval and Consent to Participate

The study adhered to the ethical standards of India and internationally, with approval from the Institutional Ethical Committee (CSJMU/BSBT/BT/EC-20) and written informed consent from all patients, including controls and OA subjects.

Guarantor

The article’s full responsibility lies with PY, who is the corresponding author and the third author in the list.

Authors' contributions

Dr. VC was responsible for manuscript conceptualization, writing - original draft, ethical approvals, consent, and sample collection. VR participated in writing - review & editing. PY contributed to manuscript writing, formatting, revision and communication with all authors. Dr. TA supervised all authors and wrote, reviewed and edited the final manuscript.

Acknowledgements

The authors thank the Institute of Biosciences and Biotechnology, Chhatrapati Shahu Ji Maharaj University, Kanpur - 208024, India, for providing the laboratory facilities and the Department of the Community Health Centre, Ganesh Shankar Vidyarthi Memorial Medical College (GSVM) Medical College, Kanpur – 208002, India, for recruiting the controls and subjects.

Availability of data and materials

Data and materials are available upon request.

Consent for publication

All authors consented to manuscript publication.

References

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"We recently published an article entitled “Influence of beta-Cyclodextrins upon the Degradation of Carbofuran Derivatives under Alkaline Conditions" in the Journal of “Pesticides and Biofertilizers” to show that the cyclodextrins protect the carbamates increasing their half-life time in the presence of basic conditions This will be very helpful to understand carbofuran behaviour in the analytical, agro-environmental and food areas. We greatly appreciated the interaction with the editor and the editorial team; we were particularly well accompanied during the course of the revision process, since all various steps towards publication were short and without delay".

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Jesus Simal-Gandara

I would like to express my gratitude towards you process of article review and submission. I found this to be very fair and expedient. Your follow up has been excellent. I have many publications in national and international journal and your process has been one of the best so far. Keep up the great work.

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Douglas Miyazaki

We are grateful for this opportunity to provide a glowing recommendation to the Journal of Psychiatry and Psychotherapy. We found that the editorial team were very supportive, helpful, kept us abreast of timelines and over all very professional in nature. The peer review process was rigorous, efficient and constructive that really enhanced our article submission. The experience with this journal remains one of our best ever and we look forward to providing future submissions in the near future.

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Dr Griffith

I am very pleased to serve as EBM of the journal, I hope many years of my experience in stem cells can help the journal from one way or another. As we know, stem cells hold great potential for regenerative medicine, which are mostly used to promote the repair response of diseased, dysfunctional or injured tissue using stem cells or their derivatives. I think Stem Cell Research and Therapeutics International is a great platform to publish and share the understanding towards the biology and translational or clinical application of stem cells.

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Dr Tong Ming Liu

I would like to give my testimony in the support I have got by the peer review process and to support the editorial office where they were of asset to support young author like me to be encouraged to publish their work in your respected journal and globalize and share knowledge across the globe. I really give my great gratitude to your journal and the peer review including the editorial office.

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Husain Taha Radhi

I am delighted to publish our manuscript entitled "A Perspective on Cocaine Induced Stroke - Its Mechanisms and Management" in the Journal of Neuroscience and Neurological Surgery. The peer review process, support from the editorial office, and quality of the journal are excellent. The manuscripts published are of high quality and of excellent scientific value. I recommend this journal very much to colleagues.

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S Munshi

Dr.Tania Muñoz, My experience as researcher and author of a review article in The Journal Clinical Cardiology and Interventions has been very enriching and stimulating. The editorial team is excellent, performs its work with absolute responsibility and delivery. They are proactive, dynamic and receptive to all proposals. Supporting at all times the vast universe of authors who choose them as an option for publication. The team of review specialists, members of the editorial board, are brilliant professionals, with remarkable performance in medical research and scientific methodology. Together they form a frontline team that consolidates the JCCI as a magnificent option for the publication and review of high-level medical articles and broad collective interest. I am honored to be able to share my review article and open to receive all your comments.

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Tania Munoz

“The peer review process of JPMHC is quick and effective. Authors are benefited by good and professional reviewers with huge experience in the field of psychology and mental health. The support from the editorial office is very professional. People to contact to are friendly and happy to help and assist any query authors might have. Quality of the Journal is scientific and publishes ground-breaking research on mental health that is useful for other professionals in the field”.

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George Varvatsoulias

Dear editorial department: On behalf of our team, I hereby certify the reliability and superiority of the International Journal of Clinical Case Reports and Reviews in the peer review process, editorial support, and journal quality. Firstly, the peer review process of the International Journal of Clinical Case Reports and Reviews is rigorous, fair, transparent, fast, and of high quality. The editorial department invites experts from relevant fields as anonymous reviewers to review all submitted manuscripts. These experts have rich academic backgrounds and experience, and can accurately evaluate the academic quality, originality, and suitability of manuscripts. The editorial department is committed to ensuring the rigor of the peer review process, while also making every effort to ensure a fast review cycle to meet the needs of authors and the academic community. Secondly, the editorial team of the International Journal of Clinical Case Reports and Reviews is composed of a group of senior scholars and professionals with rich experience and professional knowledge in related fields. The editorial department is committed to assisting authors in improving their manuscripts, ensuring their academic accuracy, clarity, and completeness. Editors actively collaborate with authors, providing useful suggestions and feedback to promote the improvement and development of the manuscript. We believe that the support of the editorial department is one of the key factors in ensuring the quality of the journal. Finally, the International Journal of Clinical Case Reports and Reviews is renowned for its high- quality articles and strict academic standards. The editorial department is committed to publishing innovative and academically valuable research results to promote the development and progress of related fields. The International Journal of Clinical Case Reports and Reviews is reasonably priced and ensures excellent service and quality ratio, allowing authors to obtain high-level academic publishing opportunities in an affordable manner. I hereby solemnly declare that the International Journal of Clinical Case Reports and Reviews has a high level of credibility and superiority in terms of peer review process, editorial support, reasonable fees, and journal quality. Sincerely, Rui Tao.

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Rui Tao

Clinical Cardiology and Cardiovascular Interventions I testity the covering of the peer review process, support from the editorial office, and quality of the journal.

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Khurram Arshad

Clinical Cardiology and Cardiovascular Interventions, we deeply appreciate the interest shown in our work and its publication. It has been a true pleasure to collaborate with you. The peer review process, as well as the support provided by the editorial office, have been exceptional, and the quality of the journal is very high, which was a determining factor in our decision to publish with you.

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Gomez Barriga Maria Dolores

The peer reviewers process is quick and effective, the supports from editorial office is excellent, the quality of journal is high. I would like to collabroate with Internatioanl journal of Clinical Case Reports and Reviews journal clinically in the future time.

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Lin Shaw Chin

Clinical Cardiology and Cardiovascular Interventions, I would like to express my sincerest gratitude for the trust placed in our team for the publication in your journal. It has been a true pleasure to collaborate with you on this project. I am pleased to inform you that both the peer review process and the attention from the editorial coordination have been excellent. Your team has worked with dedication and professionalism to ensure that your publication meets the highest standards of quality. We are confident that this collaboration will result in mutual success, and we are eager to see the fruits of this shared effort.

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Maria Dolores Gomez Barriga