Prediction of Anastomotic Leakage in Esophageal Cancer Surgery: A Multimodal Machine Learning Model Integrating Imaging and Clinical Data.

RATIONALE AND OBJECTIVES: Surgery in combination with chemo/radiotherapy is the standard treatment for locally advanced esophageal cancer. Even after the introduction of minimally invasive techniques, esophagectomy carries significant morbidity and mortality. One of the most common and feared complications of esophagectomy is anastomotic leakage (AL). Our work aimed to develop a multimodal machine-learning model combining CT-derived and clinical data for predicting AL following esophagectomy for esophageal cancer. MATERIAL AND METHODS: A total of 471 patients were prospectively included (Jan 2010-Dec 2022). Preoperative computed tomography (CT) was used to evaluate celia trunk stenosis and vessel calcification. Clinical variables, including demographics, disease stage, operation details, postoperative CRP, and stage, were combined with CT data to build a model for AL prediction. Data was split into 80%:20% for training and testing, and an XGBoost model was developed with 10-fold cross-validation and early stopping. ROC curves and respective areas under the curve (AUC), sensitivity, specificity, PPV, NPV, and F1-scores were calculated. RESULTS: A total of 117 patients (24.8%) exhibited post-operative AL. The XGboost model achieved an AUC of 79.2% (95%CI 69%-89.4%) with a specificity of 77.46%, a sensitivity of 65.22%, PPV of 48.39%, NPV of 87.3%, and F1-score of 56%. Shapley Additive exPlanation analysis showed the effect of individual variables on the result of the model. Decision curve analysis showed that the model was particularly beneficial for threshold probabilities between 15% and 48%. CONCLUSION: A clinically relevant multimodal model can predict AL, which is especially valuable in cases with low clinical probability of AL.

Perspectives for the Use of Umbilical Cord Blood in Transplantation and Beyond: Initiatives for an Advanced and Sustainable Public Banking Program in Greece.

The umbilical cord blood (UCB) donated in public UCB banks is a source of hematopoietic stem cells (HSC) alternative to bone marrow for allogeneic HSC transplantation (HSCT). However, the high rejection rate of the donated units due to the strict acceptance criteria and the wide application of the haploidentical HSCT have resulted in significant limitation of the use of UCB and difficulties in the economic sustainability of the public UCB banks. There is an ongoing effort within the UCB community to optimize the use of UCB in the field of HSCT and a parallel interest in exploring the use of UCB for applications beyond HSCT i.e., in the fields of cell therapy, regenerative medicine and specialized transfusion medicine. In this report, we describe the mode of operation of the three public UCB banks in Greece as an example of an orchestrated effort to develop a viable UCB banking system by (a) prioritizing the enrichment of the national inventory by high-quality UCB units from populations with rare human leukocyte antigens (HLA), and (b) deploying novel sustainable applications of UCB beyond HSCT, through national and international collaborations. The Greek paradigm of the public UCB network may become an example for countries, particularly with high HLA heterogeneity, with public UCB banks facing sustainability difficulties and adds value to the international efforts aiming to sustainably expand the public UCB banking system.

Convolutional neural networks for the differentiation between benign and malignant renal tumors with a multicenter international computed tomography dataset.

OBJECTIVES: To use convolutional neural networks (CNNs) for the differentiation between benign and malignant renal tumors using contrast-enhanced CT images of a multi-institutional, multi-vendor, and multicenter CT dataset. METHODS: A total of 264 histologically confirmed renal tumors were included, from US and Swedish centers. Images were augmented and divided randomly 70%:30% for algorithm training and testing. Three CNNs (InceptionV3, Inception-ResNetV2, VGG-16) were pretrained with transfer learning and fine-tuned with our dataset to distinguish between malignant and benign tumors. The ensemble consensus decision of the three networks was also recorded. Performance of each network was assessed with receiver operating characteristics (ROC) curves and their area under the curve (AUC-ROC). Saliency maps were created to demonstrate the attention of the highest performing CNN. RESULTS: Inception-ResNetV2 achieved the highest AUC of 0.918 (95% CI 0.873-0.963), whereas VGG-16 achieved an AUC of 0.813 (95% CI 0.752-0.874). InceptionV3 and ensemble achieved the same performance with an AUC of 0.894 (95% CI 0.844-0.943). Saliency maps indicated that Inception-ResNetV2 decisions are based on the characteristics of the tumor while in most tumors considering the characteristics of the interface between the tumor and the surrounding renal parenchyma. CONCLUSION: Deep learning based on a diverse multicenter international dataset can enable accurate differentiation between benign and malignant renal tumors. CRITICAL RELEVANCE STATEMENT: Convolutional neural networks trained on a diverse CT dataset can accurately differentiate between benign and malignant renal tumors. KEY POINTS: • Differentiation between benign and malignant tumors based on CT is extremely challenging. • Inception-ResNetV2 trained on a diverse dataset achieved excellent differentiation between tumor types. • Deep learning can be used to distinguish between benign and malignant renal tumors.

A pilot radiometabolomics integration study for the characterization of renal oncocytic neoplasia.

Differentiating benign renal oncocytic tumors and malignant renal cell carcinoma (RCC) on imaging and histopathology is a critical problem that presents an everyday clinical challenge. This manuscript aims to demonstrate a novel methodology integrating metabolomics with radiomics features (RF) to differentiate between benign oncocytic neoplasia and malignant renal tumors. For this purpose, thirty-three renal tumors (14 renal oncocytic tumors and 19 RCC) were prospectively collected and histopathologically characterised. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) was used to extract metabolomics data, while RF were extracted from CT scans of the same tumors. Statistical integration was used to generate multilevel network communities of -omics features. Metabolites and RF critical for the differentiation between the two groups (delta centrality > 0.1) were used for pathway enrichment analysis and machine learning classifier (XGboost) development. Receiver operating characteristics (ROC) curves and areas under the curve (AUC) were used to assess classifier performance. Radiometabolomics analysis demonstrated differential network node configuration between benign and malignant renal tumors. Fourteen nodes (6 RF and 8 metabolites) were crucial in distinguishing between the two groups. The combined radiometabolomics model achieved an AUC of 86.4%, whereas metabolomics-only and radiomics-only classifiers achieved AUC of 72.7% and 68.2%, respectively. Analysis of significant metabolite nodes identified three distinct tumour clusters (malignant, benign, and mixed) and differentially enriched metabolic pathways. In conclusion, radiometabolomics integration has been presented as an approach to evaluate disease entities. In our case study, the method identified RF and metabolites important in differentiating between benign oncocytic neoplasia and malignant renal tumors, highlighting pathways differentially expressed between the two groups. Key metabolites and RF identified by radiometabolomics can be used to improve the identification and differentiation between renal neoplasms.

Machine Learning Integrating 99mTc Sestamibi SPECT/CT and Radiomics Data Achieves Optimal Characterization of Renal Oncocytic Tumors.

The increasing evidence of oncocytic renal tumors positive in 99mTc Sestamibi Single Photon Emission Tomography/Computed Tomography (SPECT/CT) examination calls for the development of diagnostic tools to differentiate these tumors from more aggressive forms. This study combined radiomics analysis with the uptake of 99mTc Sestamibi on SPECT/CT to differentiate benign renal oncocytic neoplasms from renal cell carcinoma. A total of 57 renal tumors were prospectively collected. Histopathological analysis and radiomics data extraction were performed. XGBoost classifiers were trained using the radiomics features alone and combined with the results from the visual evaluation of 99mTc Sestamibi SPECT/CT examination. The combined SPECT/radiomics model achieved higher accuracy (95%) with an area under the curve (AUC) of 98.3% (95% CI 93.7-100%) than the radiomics-only model (71.67%) with an AUC of 75% (95% CI 49.7-100%) and visual evaluation of 99mTc Sestamibi SPECT/CT alone (90.8%) with an AUC of 90.8% (95%CI 82.5-99.1%). The positive predictive values of SPECT/radiomics, radiomics-only, and 99mTc Sestamibi SPECT/CT-only models were 100%, 85.71%, and 85%, respectively, whereas the negative predictive values were 85.71%, 55.56%, and 94.6%, respectively. Feature importance analysis revealed that 99mTc Sestamibi uptake was the most influential attribute in the combined model. This study highlights the potential of combining radiomics analysis with 99mTc Sestamibi SPECT/CT to improve the preoperative characterization of benign renal oncocytic neoplasms. The proposed SPECT/radiomics classifier outperformed the visual evaluation of 99mTc Sestamibii SPECT/CT and the radiomics-only model, demonstrating that the integration of 99mTc Sestamibi SPECT/CT and radiomics data provides improved diagnostic performance, with minimal false positive and false negative results.

Radiomics Analysis for Multiple Myeloma: A Systematic Review with Radiomics Quality Scoring.

Multiple myeloma (MM) is one of the most common hematological malignancies affecting the bone marrow. Radiomics analysis has been employed in the literature in an attempt to evaluate the bone marrow of MM patients. This manuscript aimed to systematically review radiomics research on MM while employing a radiomics quality score (RQS) to accurately assess research quality in the field. A systematic search was performed on Web of Science, PubMed, and Scopus. The selected manuscripts were evaluated (data extraction and RQS scoring) by three independent readers (R1, R2, and R3) with experience in radiomics analysis. A total of 23 studies with 2682 patients were included, and the median RQS was 10 for R1 (IQR 5.5-12) and R3 (IQR 8.3-12) and 11 (IQR 7.5-12.5) for R2. RQS was not significantly correlated with any of the assessed bibliometric data (impact factor, quartile, year of publication, and imaging modality) (p > 0.05). Our results demonstrated the low quality of published radiomics research in MM, similarly to other fields of radiomics research, highlighting the need to tighten publication standards.

Systematic review with radiomics quality score of cholangiocarcinoma: an EuSoMII Radiomics Auditing Group Initiative.

OBJECTIVES: To systematically review current research applications of radiomics in patients with cholangiocarcinoma and to assess the quality of CT and MRI radiomics studies. METHODS: A systematic search was conducted on PubMed/Medline, Web of Science, and Scopus databases to identify original studies assessing radiomics of cholangiocarcinoma on CT and/or MRI. Three readers with different experience levels independently assessed quality of the studies using the radiomics quality score (RQS). Subgroup analyses were performed according to journal type, year of publication, quartile and impact factor (from the Journal Citation Report database), type of cholangiocarcinoma, imaging modality, and number of patients. RESULTS: A total of 38 original studies including 6242 patients (median 134 patients) were selected. The median RQS was 9 (corresponding to 25.0% of the total RQS; IQR 1-13) for reader 1, 8 (22.2%, IQR 3-12) for reader 2, and 10 (27.8%; IQR 5-14) for reader 3. The inter-reader agreement was good with an ICC of 0.75 (95% CI 0.62-0.85) for the total RQS. All studies were retrospective and none of them had phantom assessment, imaging at multiple time points, nor performed cost-effectiveness analysis. The RQS was significantly higher in studies published in journals with impact factor > 4 (median 11 vs. 4, p = 0.048 for reader 1) and including more than 100 patients (median 11.5 vs. 0.5, p < 0.001 for reader 1). CONCLUSIONS: Quality of radiomics studies on cholangiocarcinoma is insufficient based on the radiomics quality score. Future research should consider prospective studies with a standardized methodology, validation in multi-institutional external cohorts, and open science data.

Deep Learning for the Differential Diagnosis between Transient Osteoporosis and Avascular Necrosis of the Hip.

Differential diagnosis between avascular necrosis (AVN) and transient osteoporosis of the hip (TOH) can be complicated even for experienced MSK radiologists. Our study attempted to use MR images in order to develop a deep learning methodology with the use of transfer learning and a convolutional neural network (CNN) ensemble, for the accurate differentiation between the two diseases. An augmented dataset of 210 hips with TOH and 210 hips with AVN was used to finetune three ImageNet-trained CNNs (VGG-16, InceptionResNetV2, and InceptionV3). An ensemble decision was reached in a hard-voting manner by selecting the outcome voted by at least two of the CNNs. Inception-ResNet-V2 achieved the highest AUC (97.62%) similar to the model ensemble, followed by InceptionV3 (AUC of 96.82%) and VGG-16 (AUC 96.03%). Precision for the diagnosis of AVN and recall for the detection of TOH were higher in the model ensemble compared to Inception-ResNet-V2. Ensemble performance was significantly higher than that of an MSK radiologist and a fellow (P < 0.001). Deep learning was highly successful in distinguishing TOH from AVN, with a potential to aid treatment decisions and lead to the avoidance of unnecessary surgery.

Machine learning identifies factors related to early joint space narrowing in dysplastic and non-dysplastic hips.

OBJECTIVES: To utilise machine learning, unsupervised clustering and multivariate modelling in order to predict severe early joint space narrowing (JSN) from anatomical hip parameters while identifying factors related to joint space width (JSW) in dysplastic and non-dysplastic hips. METHODS: A total of 507 hip CT examinations of patients 20-55 years old were retrospectively examined, and JSW, center-edge (CE) angle, alpha angle, anterior acetabular sector angle (AASA), and neck-shaft angle (NSA) were recorded. Dysplasia and severe JSN were defined with CE angle < 25o and JSW< 2 mm, respectively. A random forest classifier was developed to predict severe JSN based on anatomical and demographical data. Multivariate linear regression and two-step unsupervised clustering were performed to identify factors linked to JSW. RESULTS: In dysplastic hips, lateral or anterior undercoverage alone was not correlated to JSN. AASA (p < 0.005) and CE angle (p < 0.032) were the only factors significantly correlated with JSN in dysplastic hips. In non-dysplastic hips, JSW was inversely correlated to CE angle, AASA, and age and positively correlated to NSA (p < 0.001). A random forest classifier predicted severe JSN (AUC 69.9%, 95%CI 47.9-91.8%). TwoStep cluster modelling identified two distinct patient clusters one with low and one with normal JSW and different anatomical characteristics. CONCLUSION: Machine learning predicted severe JSN and identified population characteristics related to normal and abnormal joint space width. Dysplasia in one plane was found to be insufficient to cause JSN, highlighting the need for hip anatomy assessment on multiple planes. KEY POINTS: • Neither anterior nor lateral acetabular dysplasia was sufficient to independently reduce joint space width in a multivariate linear regression model of dysplastic hips. • A random forest classifier was developed based on measurements and demographic parameters from 507 hip joints, achieving an area under the curve of 69.9% in the external validation set, in predicting severe joint space narrowing based on anatomical hip parameters and age. • Unsupervised TwoStep cluster analysis revealed two distinct population groups, one with low and one with normal joint space width, characterised by differences in hip morphology.

Compression neuropathies of the forearm: anatomy, clinical features and management.

The upper limb consists of four major parts: a girdle formed by the clavicle and scapula, the arm, the forearm and the hand. Peripheral nerve lesions of the upper limb are divided into lesions of the brachial plexus or the nerves arising from it. Lesions of the nerves arising from the brachial plexus are further divided into upper (proximal) or lower (distal) lesions based on their location. Peripheral nerves in the forearm can be compressed in various locations and by a wide range of pathologies. A thorough understanding of the anatomy and clinical presentations of these compression neuropathies can lead to prompt diagnosis and management, preventing possible permanent damage. This article discusses the aetiology, anatomy, clinical presentation and surgical management of compressive neuropathies of the upper limb.

The level of bifurcation of peroneal artery and its implications for posterolateral approach to the ankle: a CT angiography study.

PURPOSE: This study aims to provide data, with the use of computed tomography angiography, regarding the level of bifurcation of the peroneal artery to the anterior perforating branch and the lateral calcaneal branch, in relation to the osseous anatomic structures of the tibial plafond, the medial malleolus and the lateral malleolus. METHODS: The study included patients who underwent diagnostic computed tomography angiography of the lower extremities. Measurements were performed in two-dimensional reconstructions and included the perpendicular distance from peroneal artery bifurcation into anterior perforating branch and lateral calcaneal branch to the lowest level of tibial plafond (D1), medial malleolus (D2) and lateral malleolus (D3). The distances were also normalized to the length of the tibia. RESULTS: Sixty patients and a total of 115 limbs were enrolled in this study. The mean distance ± standard deviation from peroneal artery bifurcation to tibial plafond (D1) was 4.33 ± 1.12 cm (normalized 0.12 ± 0.03) (range 2.54-8.26 cm), to medial malleolus (D2) was 5.53 ± 1.18 cm (normalized 0.16 ± 0.03) (range 3.27-9.5 cm) and to lateral malleolus (D3) was 6.53 ± 1.17 cm (normalized 0.18 ± 0.03) (range 4.71-10.2 cm), respectively. There was no significant difference between right and left limb measurements (p > 0.05). Females presented lower, but not statistically significant (p > 0.05), D1, D2 and D3 measurements compared to males. CONCLUSION: The bifurcation of the peroneal artery takes place at lower level compared to previously published studies and consequently extreme caution should be exercised when performing the posterolateral approach to the ankle. This study adds to the understanding of the relevant vascular anatomy of the region and assists in performing the posterolateral approach to the ankle with safety.

US-guided high-volume injection for Achilles tendinopathy.

Achilles tendinopathy is a common overuse condition affecting the adult population. The incidence is on the rise because of greater participation of people in recreational or competitive sporting activities. Chronic Achilles tendinopathy occurs most commonly in the tendon's mid-portion, and it is challenging to manage, leading to significant patient morbidity. Despite conservative management many patients still require surgical intervention. The mechanism underlying pain is not entirely understood; however, high-resolution color Doppler ultrasound has shown that neovascularisation could be involved. Minimally-invasive treatments for chronic Achilles tendinopathy may prevent the need for surgery when conservative methods have failed. Ultrasound provides an option to guide therapeutic interventions accurately, so that treatment is delivered to the desired site of pathology. High-volume image-guided injection is a relatively new technique where a high volume of liquid is injected between the anterior aspect of the Achilles tendon and the Kager's fat pad, used to strip away the neovascularity and disrupt the nerve ingrowth seen in chronic cases of Achilles tendinopathy. High-volume image-guided injection has shown promising results in terms of reducing pain and improving function in patients where conservative measures have failed. This review aims to describe the fundamental technical factors, and investigate the efficacy of high-volume image-guided injection with reference to the available literature.

Ultrasound-guided treatment of Morton's neuroma.

Morton's neuroma is a painful lesion of the interdigital nerve, usually at the third intermetatarsal space, associated with fibrotic changes in the nerve, microvascular degeneration, and deregulation of sympathetic innervation. Patients usually present with burning or sharp metatarsalgia at the dorsal or plantar aspect of the foot. The management of Morton's neuroma starts with conservative measures, usually with limited efficacy, including orthotics and anti-inflammatory medication. When conservative treatment fails, a series of minimally invasive ultrasound-guided procedures can be employed as second-line treatments prior to surgery. Such procedures include infiltration of the area with a corticosteroid and local anesthetic, chemical neurolysis with alcohol or radiofrequency thermal neurolysis. Ultrasound aids in the accurate diagnosis of Morton's neuroma and guides the aforementioned treatment, so that significant and potentially long-lasting pain reduction can be achieved. In cases of initial treatment failure, the procedure can be repeated, usually leading to the complete remission of symptoms. Current data shows that minimally invasive treatments can significantly reduce the need for subsequent surgery in patients with persistent Morton's neuroma unresponsive to conservative measures. The purpose of this review is to present current data on the application of ultrasound for the diagnosis and treatment of Morton's neuroma, with emphasis on the outcomes of ultrasound-guided treatments.

Ultrasound-guided percutaneous irrigation of calcific tendinopathy: redefining predictors of treatment outcome.

OBJECTIVES: To identify prognostic factors affecting the clinical outcome in patients treated with rotator cuff ultrasound-guided percutaneous irrigation of calcific tendinopathy (US-PICT), by evaluating the degree of calcium removal, the size and consistency of calcific deposits, and baseline level of shoulder pain and functionality. METHODS: From January 2017 to December 2019, 79 patients (23 males, 56 females; mean age, 45.7 years) who underwent US-PICT were prospectively enrolled. The calcifications' location, consistency, and size were evaluated. For US-PICT, local anesthesia, lavage of calcific material, and intrabursal steroid injection were performed. The degree of calcium removal was graded as total/partial. Shoulder pain and functionality were assessed with the visual analogue scale (VAS) in all and Constant score (CS) in a subset of patients, respectively, at 4 time-points. Mann-Whitney U test, Fisher's test, and linear and binary logistic regression were utilized for analysis. RESULTS: Pain improvement correlated with the presence of larger calcifications and lower baseline VAS score, at 1 week (p = 0.001, p < 0.001, respectively) and 1 year (p < 0.001, p = 0.002, respectively). Improved functionality correlated with total calcification retrieval, higher baseline CS, and fluid/soft calcific consistency at 1 week (p = 0.013, p = 0.003, p = 0.019, respectively). Increased calcification size, cystic appearance, and lower baseline VAS scores independently predicted complete pain resolution at 1 year. CONCLUSION: Large calcifications and low-grade pain at baseline correlated with short- and long-term pain improvement. The degree of calcium removal did not impact pain or functional improvement beyond 1 week. Increased calcification size, cystic appearance, and low-grade baseline pain predicted complete pain recovery at 1 year. KEY POINTS: • The presence of larger calcifications and lower-grade baseline pain appear to correlate with pain improvement at 1 week and 1 year after ultrasound-guided irrigation of rotator cuff calcific tendinopathy (US-PICT). • Total calcification retrieval, less affected baseline shoulder functionality, and presence of fluid/soft consistency of calcific deposits appear to correlate with improved shoulder functionality at 1 week post-treatment. • Baseline pain intensity and calcifications' morphologic characteristics, but not the degree of calcium retrieval, represent predictors of complete pain recovery at 1 year after US-PICT.

Osteogenic differentiation of bone marrow mesenchymal stem cells on chitosan/gelatin scaffolds: gene expression profile and mechanical analysis.

In the present study we explore the extracellular matrix (ECM) produced by human bone marrow mesenchymal stem/stromal cells (BM-MSCs) induced to undergo osteogenic differentiation within porous chitosan/gelatin (CS:Gel) scaffolds by investigating their multiple gene expression profile and mechanical behavior. Initially, the efficiency of the BM-MSCs osteogenic differentiation within the constructs was confirmed by the significant rise in the expression of the osteogenesis associated genes DLX5, RUNX2, ALP and OSC. In line with these findings, OSC and Col1A1 protein expression was also detected in BM-MSCs on the CS:Gel scaffolds at day 14 of osteogenic differentiation. We then profiled, for the first time, the expression of 84 cell adhesion and ECM molecules using PCR arrays. The arrays, which were conducted at day 14 of osteogenic differentiation, demonstrated that 49 genes including collagens, integrins, laminins, ECM proteases, catenins, thrombospondins, ECM protease inhibitors and cell-cell adhesion molecules were differentially expressed in BM-MSCs seeded on scaffolds compared to tissue culture polystyrene control. Moreover, we performed dynamic mechanical analysis of the cell-loaded scaffolds on days 0, 7 and 14 to investigate the correlation between the biological results and the mechanical behavior of the constructs. Our data demonstrate a significant increase in the stiffness of the constructs with storage modulus values of 2 MPa on day 7, compared to 0.5 MPa on day 0, following a drop of the stiffness at 0.8 MPa on day 14, that may be attributed to the significant increase of specific ECM protease gene expression such as MMP1, MMP9, MMP11 and MMP16 at this time period.

Multiomics characterization of mesenchymal stromal cells cultured in monolayer and as aggregates.

Mesenchymal stromal cells (MSCs) have failed to consistently demonstrate their therapeutic efficacy in clinical trials, due in part to variability in culture conditions used for their production. Of various culture conditions used for MSC production, aggregate culture has been shown to improve secretory capacity (a putative mechanism of action in vivo) compared with standard monolayer culture. The purpose of this study was to perform multiomics characterization of MSCs cultured in monolayer and as aggregates to identify aspects of cell physiology that differ between these culture conditions to begin to understand cellular-level changes that might be related to secretory capacity. Targeted secretome characterization was performed on multiple batches of MSC-conditioned media, while nontargeted proteome and metabolome characterization was performed and integrated to identify cellular processes differentially regulated between culture conditions. Secretome characterization revealed a reduction in MSC batch variability when cultured as aggregates. Proteome and metabolome characterization showed upregulation of multiple protein and lipid metabolic pathways, downregulation of several cytoskeletal processes, and differential regulation of extracellular matrix synthesis. Integration of proteome and metabolome characterization revealed individual lipid metabolites and vesicle-trafficking proteins as key features for discriminating between culture conditions. Overall, this study identifies several aspects of MSC physiology that are altered by aggregate culture. Further exploration of these processes and pathways is needed to determine their potential role in regulating cell secretory capacity.

Comparison of human isogeneic Wharton's jelly MSCs and iPSC-derived MSCs reveals differentiation-dependent metabolic responses to IFNG stimulation.

Variability among donors, non-standardized methods for isolation, and characterization contribute to mesenchymal stem/stromal cell (MSC) heterogeneity. Induced pluripotent stem cell (iPSCs)-derived MSCs would circumvent many of current issues and enable large-scale production of standardized cellular therapy. To explore differences between native MSCs (nMSCs) and iPSC-derived MSCs (iMSCs), we developed isogeneic lines from Wharton's jelly (WJ) from the umbilical cords of two donors (#12 and #13) under xeno-free conditions. Next, we reprogrammed them into iPSCs (iPSC12 and iPSC13) and subsequently differentiated them back into iMSCs (iMSC12 and iMSC13) using two different protocols, which we named ARG and TEX. We assessed their differentiation capability, transcriptome, immunomodulatory potential, and interferon-γ (IFNG)-induced changes in metabolome. Our data demonstrated that although both differentiation protocols yield iMSCs similar to their parental nMSCs, there are substantial differences. The ARG protocol resulted in iMSCs with a strong immunomodulatory potential and lower plasticity and proliferation rate, whereas the TEX protocol raised iMSCs with a higher proliferation rate, better differentiation potential, though weak immunomodulatory response. Our data suggest that, following a careful selection and screening of donors, nMSCs from umbilical's cord WJ can be easily reprogrammed into iPSCs, providing an unlimited source of material for differentiation into iMSCs. However, the differentiation protocol should be chosen depending on their clinical use.

Oxidized alginate hydrogels with the GHK peptide enhance cord blood mesenchymal stem cell osteogenesis: A paradigm for metabolomics-based evaluation of biomaterial design.

Oxidized alginate hydrogels are appealing alternatives to natural alginate due to their favourable biodegradability profiles and capacity to self-crosslink with amine containing molecules facilitating functionalization with extracellular matrix cues, which enable modulation of stem cell fate, achieve highly viable 3-D cultures, and promote cell growth. Stem cell metabolism is at the core of cellular fate (proliferation, differentiation, death) and metabolomics provides global metabolic signatures representative of cellular status, being able to accurately identify the quality of stem cell differentiation. Herein, umbilical cord blood mesenchymal stem cells (UCB MSCs) were encapsulated in novel oxidized alginate hydrogels functionalized with the glycine-histidine-lysine (GHK) peptide and differentiated towards the osteoblastic lineage. The ADA-GHK hydrogels significantly improved osteogenic differentiation compared to gelatin-containing control hydrogels, as demonstrated by gene expression, alkaline phosphatase activity and bone extracellular matrix deposition. Metabolomics revealed the high degree of metabolic heterogeneity in the gelatin-containing control hydrogels, captured the enhanced osteogenic differentiation in the ADA-GHK hydrogels, confirmed the similar metabolism between differentiated cells and primary osteoblasts, and elucidated the metabolic mechanism responsible for the function of GHK. Our results suggest a novel paradigm for metabolomics-guided biomaterial design and robust stem cell bioprocessing. STATEMENT OF SIGNIFICANCE: Producing high quality engineered bone grafts is important for the treatment of critical sized bone defects. Robust and sensitive techniques are required for quality assessment of tissue-engineered constructs, which result to the selection of optimal biomaterials for bone graft development. Herein, we present a new use of metabolomics signatures in guiding the development of novel oxidised alginate-based hydrogels with umbilical cord blood mesenchymal stem cells and the glycine-histidine-lysine peptide, demonstrating that GHK induces stem cell osteogenic differentiation. Metabolomics signatures captured the enhanced osteogenesis in GHK hydrogels, confirmed the metabolic similarity between differentiated cells and primary osteoblasts, and elucidated the metabolic mechanism responsible for the function of GHK. In conclusion, our results suggest a new paradigm of metabolomics-driven design of biomaterials.