Biology subjects

Saeed, A.

Publications and source records attributed to Saeed, A..

16 recordsLinked to original sources

bioRxiv2026

Efficacy of SGLT2 Inhibitors in Pulmonary Arterial Hypertension: A Systematic Review and Meta-Analysis of Preclinical Studies

BackgroundPulmonary arterial hypertension (PAH) is a progressive disease marked by vascular remodeling, elevated pulmonary pressures, and right ventricular failure. Current therapies are mainly vasodilatory, underscoring the need for treatments targeting additional pathways. Sodium-glucose cotransporter-2 (SGLT2) inhibitors, initially used for diabetes, have demonstrated cardiovascular benefits. AimsThis systematic review and meta-analysis evaluated the effects of SGLT2 inhibitors in animal models of PAH, focusing on pulmonary hemodynamics and right ventricular function. MethodsPubMed, Embase, Web of Science, and Scopus were searched for preclinical studies reporting mean pulmonary artery pressure (mPAP), right ventricular systolic pressure (RVSP), right ventricular hypertrophy index (RV/LV+S), tricuspid annular plane systolic excursion (TAPSE), or pulmonary artery acceleration time (PAAT). Random-effects meta-analyses were performed using R. ResultsNine studies were included. SGLT2 inhibitors were significantly associated with lower mPAP (WMD -9.79 mmHg), RVSP (WMD -14.81 mmHg), and RV/LV+S (WMD -0.10). They were also associated with higher indices of right ventricular function, including TAPSE (WMD 0.53 mm) and PAAT (WMD 6.39 ms). ConclusionIn preclinical models of PAH, SGLT2 inhibitor treatment was associated with favorable hemodynamic and structural parameters. Further research is needed to clarify their translational potential and long-term safety.

pharmacology and toxicology↗

bioRxiv2026

BioGraphX-RNA: A Universal Physicochemical Graph Encoding for Interpretable RNA Subcellular Localization Prediction

RNA subcellular localization is a critical determinant of cellular function. However, current computational approaches often operate as "black boxes," overlooking the complex interplay among sequence, structure, and physicochemical interactions that govern RNA localization. Building upon the BioGraphX framework originally developed for proteins, we introduce BioGraphX-RNA, a universal physico-chemical graph-encoding framework that provides a structure-informed encoding by translating primary nucleotide sequences into multi-scale interaction graphs using explicit biophysical rules. When combined with frozen RiNALMo embeddings via an interpretable gated fusion layer, BioGraphX-RNA achieves competitive performance with DeepLocRNA and uniquely quantifies the relative contribution of sequence versus structure for each RNA. On human datasets, the gated fusion model attains macro-AUROC values of 0.7575 {+/-} 0.0054 (mRNA), 0.9228 {+/-} 0.0137 (miRNA), and 0.5600 {+/-} 0.0191 (lncRNA). For miRNA, the graph-only model alone reaches 0.9396 {+/-} 0.0045, out-performing both the RiNALMo language model and a RNAfold partition-function graph (0.9139 {+/-} 0.0138), validating the structure-informed proxy hypothesis. In a blind cross-species prediction task on mouse data, the model shows limited zero-shot transfer, indicating that biophysical graph features do not improve cross-species generalization. Gating analysis reveals RNA-type-specific modality reliance, with miRNA exhibiting a near-equilibrium balance between sequence and structure. SHAP-based interpretation suggests potential correlates such as patterned GC content for nuclear retention and structural accessibility for exosome targeting. These advances are achieved with only 2.05 million trainable parameters, aligning with Green AI principles. BioGraphX-RNA demonstrates that explicitly integrating biophysical constraints into graph-based encodings enables accurate and interpretable predictions for structured RNAs, advancing structure-aware RNA biology and laying a foundation for precision medicine.

bioinformatics↗

bioRxiv2026

BioGraphX: Bridging the Sequence-Structure Gap via PhysicochemicalGraph Encoding for Explainable Subcellular Localization Prediction

Computational approaches for protein subcellular localization prediction are important for understanding cellular mechanisms and developing treatments for complex diseases. However, a critical limitation of current methods is their lack of interpretability: while they can predict where a protein localizes, they fail to explain why the protein is assigned to a specific location. Moreover, understanding protein behavior traditionally requires knowledge of three-dimensional structure, which is a costly and time-consuming process. Here, we propose BioGraphX, a novel encoding framework that constructs protein interaction graphs directly from protein sequences using biochemical rules. This approach provides a constraint-based structural proxy directly from sequence, reducing the dependency on experimentally determined three-dimensional structures. Building upon this representation, BioGraphX-Net demonstrates superior performance on the DeepLoc 2.0 benchmark by integrating ESM-2 embeddings with the proposed features via a gating mechanism. Gating analysis shows that although ESM-2 embeddings provide strong contributions, BioGraphX features function as high-precision filters. SHAP analysis reveals feature importance patterns consistent with a sophisticated biophysical logic: sequence signals act as universal exclusion filters, while organelle-specific combinations of biophysical features enable precise compartment discrimination. Notably, Frustration features help resolve targeting ambiguities in complex compartments, reflecting evolutionary constraints while preventing mislocalization from sequence mimicry. It has the additional advantage of promoting Green AI in bioinformatics, achieving performance comparable to the state-of-the-art while maintaining a minimal parameter count of 13.46 million. In summary, BioGraphX not only provides accurate predictions but also offers new insights into the language of life.

bioinformatics↗

bioRxiv2025

Clinical and molecular characterisation of primary refractoriness to atezolizumab plus bevacizumab in patients with unresectable hepatocellular carcinoma.

BackgroundDespite improved outcomes with atezolizumab plus bevacizumab (A+B) in hepatocellular carcinoma (HCC), primary refractoriness (PRef), characterised by early progression or short-lived disease stabilisation following treatment, remains a significant and poorly understood clinical challenge. MethodsWe analysed 1296 patients with HCC and Child-Pugh A liver cirrhosis treated with frontline A+B (AB-real) and validated findings in 645 trial participants recruited to IMbrave150 and GO30140. PRef was defined by Society for the Immunotherapy of Cancer (SITC) criteria as progressive disease in the first 6 months after treatment initiation. Patients who achieved complete response, partial response or stable disease for [≥] 6 months were classified as responders. We performed a multi-parametric analysis of pre-treatment tumour tissue including machine learning-based quantification of tumour-infiltrating lymphocytes, imaging mass cytometry and RNA sequencing (RNAseq) to evaluate differences in the tumour microenvironment (TME) of PRef versus responding patients. We employed conditional inference tree analyses to provide a hierarchical organisation of determinants of PRef. ResultsAmong 677 AB-real and 378 trial patients evaluable by SITC criteria, PRef identified inferior median OS in comparison with responding patients (AB-real: 7.3 vs. 31.5 months, HR 3.7, 95%CI 2.8-8.5, p<0.001; Trials: 10.8 vs. NR, HR 4.6, 95%CI 3.3-6.3, p<0.001). PRef patients exhibited higher baseline systemic inflammation (neutrophil-to-lymphocyte ratio, NLR [≥]3), a distinctively immunosuppressive TME enriched in CD163+ tumour-associated macrophages and a higher Treg/Teff ratio. RNAseq of tumour tissue demonstrated lower intrinsic immunogenicity in PRef samples, characterised by repressed IFN-{gamma} and Teff signatures, with elevated myeloid infiltration. Conditional inference tree analysis identified IFN-{gamma} signature downregulation combined with NLR [≥]3 as the strongest contributor of PRef. ConclusionsPRef to A+B identifies a distinct biological entity characterised by unopposed systemic inflammation, myeloid cell infiltration and T-cell depletion. Targeting myeloid-mediated immunosuppression, particularly in patients with low IFN-{gamma} signature expression and elevated NLR might enhance responsiveness to A+B. HighlightsO_LIPrimary refractoriness to atezolizumab plus bevacizumab in hepatocellular carcinoma, as defined by SITC criteria, is associated with poor clinical outcomes. C_LIO_LITumour microenvironment profiling reveals an immunosuppressive phenotype characterized by high myeloid infiltration, reduced interferon-{gamma} signalling, and T-cell depletion. C_LIO_LIThe combination of systemic inflammation and low IFN-{gamma} signature expression strongly predicts primary refractoriness and may inform therapeutic decision-making. C_LI

cancer biology↗

bioRxiv2025

Deconvoluting single-cell transcriptomics reveals cellular programs regulated by cell-cell communication in colorectal cancer

Cells within a tissue microenvironment communicate through intricate cell-cell communication (CCC) networks. In this meta-analysis of eight single-cell cohorts encompassing 153 patients and 279 samples, we advance the understanding of CCC networks in colorectal cancers through a novel analytical framework. Employing hierarchical topic modeling, we identify gene expression modules (GEMs) that mirror single-cell signaling states, crucial for deciphering the complexity of intercellular interactions. By applying causal discovery methods, we systematically uncover GEMs likely regulated by ligand-receptor signaling and cross-cell-type communication. This analysis reveals cross-cell-type CCC programs, marked by highly correlated GEMs across various cell types, shedding light on the intricate CCC networks within the tumor microenvironment. Spatial transcriptomics further validate these findings by demonstrating the co-localization of GEMs within CCC programs in distinct spatial domains, emphasizing the spatial dynamics of tumor intercellular communication. Our interactive website (http://44.192.10.166:3838/) and analytical framework equip researchers with powerful tools to explore these complex mechanisms, potentially uncovering novel drug targets and refining strategies for precision immunotherapies. This comprehensive study not only presents a detailed catalog of CCC networks driven by ligand-receptor interactions in colorectal cancer but also highlights the significance of integrating multi-sample and patient data to unravel the molecular underpinnings of cancer communication pathways.

bioinformatics↗

bioRxiv2024

Current transcriptome database and biomarker discovery for immunotherapy by immune checkpoint blockade

Immune checkpoint blockade (ICB) has revolutionized the current immuno-oncology and significantly improved clinical outcome for cancer treatment. Despite the advancement in clinics, only a small subset of patients derives immune response to the ICB therapy. Therefore, a robust predictive biomarker that identifies potential candidate becomes increasingly crucial in delivering this technology to the public. In this review, we first discuss the biomarkers that focus on tumor genome, tumor microenvironment and tumor-host interaction. Then, we compare existing databases for biomarker discovery for ICB response. We also present IOhub - an interactive web portal that incorporates 36 bulk and 10 single-cell transcriptome datasets for benchmark analysis of the current biomarkers. Finally, we highlight the trending interest in antibody drug conjugate and combination treatment and their use in precision immuno-oncology.

bioinformatics↗

bioRxiv2024

Treatment and reprocessing of textile dyeing wastewater by using the electrocoagulation treatment process

This study electrocoagulated textile effluent to remove dyes. The wastewater reuse method was used to study three reactive dyes: C.I. Reactive Red 221, Blue 19, and Yellow 145. Laboratory wastewater was electrocoagulated. Standard wastewater had three pH values. (4, 7, 10). Electrocoagulation removes volatile dye colors well. The best results were 98% within 15-20 minutes for 1% C.I. Reactive Red 221. After 20 minutes, 1% shade C.I. Reactive Blue 19 and Yellow 145 color removal efficacy is 96%. Electrocoagulation treatment of dyeing effluent is greatly affected by pH. Electrocoagulation efficacy was lowest at pH 4. When pH was highest, removal efficacy was best. Dyeing wastewater removal efficiency improved when pH was changed from 7 to 10. Discolored wash-off cloth batches were rubbed dry and wet. The normal and electro-coagulant treated wash-off batches had wash fastness and rubbing values of 4 to 5 in dry crocking. The C.I. Reactive Dyes (Red 221, Yellow 145, and Blue 19) standard fabrics and treated wash-off with electro-coagulated lot showed 3 to 4 wet rubbing, almost like the standard fabric, but no shade changes at this concentration. All three reactive dyes had color values. Because alkaline pH removes dyes best, color difference values of Batch C (fabric treated by pH 10 wash-off) were within the approved range of 0.38 to 1.50 of all dyes and shades (5%,3%,1%). Batch A values between 2.44 and 13.48 were outside the allowed range (< 1). Batch B (fabric treated by pH 7 wash-off) values fell between Batch A and Batch C.

ecology↗

bioRxiv2024

The emergence of Fluoroquinolone resistant and Extended-spectrum beta-lactamase-producing Salmonella spp. isolated from Poultry in Pakistan

The rise of antimicrobial-resistant and Extended Spectrum Beta Lactamases producing Salmonella strains in poultry is a severe health threat worldwide, particularly in developing countries like Pakistan. The current study aimed to investigate the isolation and identification of Cefotaxime and Ciprofloxacin-Resistant Salmonella strains originating from poultry. During this study, 78 (26.0%) Salmonella strains were isolated from 300 diverse poultry samples. The isolated 78 Salmonella strains were identified as S. pullorum, S. gallinarum, S. enteritidis, S. enterica, S. paratyphi, S. typhimurium, S. typhi, S. arizonae, and 19% other Salmonella spp. by API 20E method. The antibiotic susceptibility profile showed that 61% of MDR Salmonella strains were isolated from diverse poultry samples. MDR rates were high in serovars S. enterica, S. typhimurium, S. enteritidis, S. arizonae, and S. gallinarum. Co-resistant to cefotaxime and ciprofloxacin in 56.4% of Salmonella strains was observed. Among 44 phenotypically ESBL-positive Salmonella strains, 36 (81.8%) carried bla CTX-M and 38 (86%) carried bla CTX-M-1. A High incidence rate of bla CTX-M and bla-CTX-M-1 was observed among S. enteritidis (19% and 21%), S. enterica (11% and 16%), S. typhimurium (13% and16%) and S. typhi (3% and 5%). Among 29 phenotypically MBL-positive Salmonella strains, 13 (44.8%) carried bla VIM and 6 (20.6%) carried bla IMP. The 67% prevalence of gyr A was observed in fluoroquinolone-resistant Salmonella strains. The most prevalent fluoroquinolone strains were S. enteritidis (19%), S. typhimurium (19%), S. typhi (13%), and S. gallinarum (12%). Fluoroquinolone-resistant, MBL, and ESBL-producing Salmonella strains from poultry are a matter of great concern for both livestock and public health, demonstrating the dissemination risk of these microorganisms through the food chain.

microbiology↗

bioRxiv2023

The rural urban divide, insights from immuno-genetic profiles and implications for health

Population disparities in health and disease, has been observed, and amply documented. While often attributable to genetic underpinnings, such disparities, extends beyond population genetic predisposition to include environmental and geographic determinants most pronouncedly the division between rural and urban lifestyles. Under such influences, genes and gene products may become affected by epigenetic factors, microbial modifiers including infections and the body microbiome that ultimately shapes the outcome of complex milieu of protein networks. Retrospective, demographic, genotype, and expression data of two rural populations from eastern Sudan were analysed for genotype, allele frequency distribution, Hardy Weinberg Equilibrium and expression profiles using an array panel of Th1, Th2 and Th3 genes in a subset of rural population sample against matched urban control. Differences between urban and rural samples were observed in the departure from HWE with excess of heterozygosity in the rural sample. In the Th1, Th2 and Th3 array, cytokines were consistently overexpressed in the rural as compared to urban cohort and was replicated in 7 selected genes that are associated with chronic diseases amongst urban dwellers in contrast to rural village inhabitants. IgE levels as feature of parasitic infections is one other difference to include in that dichotomy. Gene expression appears to be more exposing to an overall outcome of genetic variations, including the interaction with environmental influences within and outside the body. Here, it may be gathered from the contrast in the expression patterns between the rural and urban samples. The presence of signals of natural selection in genes that are key to certain biological functions as CD40L and FasL, and the sharp contrast between urban and rural populations in gene variants distribution and expression patterns may provide important clues towards understanding the disparity between human communities in non-communicable diseases of lifestyle as well as some of the emerging infectious diseases.

immunology↗

bioRxiv2023

SpliceMutr enables pan-cancer analysis of splicing-derived neoantigen burden in tumors

Aberrant alternative splicing can generate neoantigens, which can themselves stimulate immune responses and surveillance. Previous methods for quantifying splicing-derived neoantigens are limited by independent references and potential batch effects. Here, we introduce SpliceMutr, a bioinformatics approach and pipeline for identifying splicing derived neoantigens from paired tumor normal data. SpliceMutr facilitates the identification of tumor-specific antigenic splice variants, predicts MHC-binding affinity, and estimates splicing antigenicity scores per gene. By applying this tool to genomic data from The Cancer Genome Atlas (TCGA), we generate splicing-derived neoantigens and neoantigenicity scores per sample and across all cancer types and find numerous correlations between splicing antigenicity and well-established biomarkers of anti-tumor immunity. Notably, carriers of mutations within splicing machinery genes have higher splicing antigenicity, which provides support for our approach. Further analysis of splicing antigenicity in cohorts of melanoma patients treated with mono- or combined immune checkpoint inhibition suggest that the abundance of splicing antigens is reduced post-treatment from baseline in patients who progress, likely because of an immunoediting process. We also observe increased splicing antigenicity in responders to immunotherapy, which may relate to an increased capacity to mount an immune response to splicing-derived antigens. This new computational tool provides novel analytical capabilities for splicing antigenicity and is openly available for further immuno-oncologic analysis.

cancer biology↗

bioRxiv2023

Microevolution and phylogenomic characterization with perspectives in the 2022-2023 outbreak of child Respiratory Syncytial Virus type A

A communal respiratory syncytial virus (RSV) causes mild to severe illness, predominantly in older adults, or people with certain chronic medical conditions, and in particular, in young children. Symptoms may include runny nose, cough, fever, and difficulty breathing. In most cases, the infection is mild and resolves on its own, but in some cases, it can lead to more serious illness such as bronchiolitis or pneumonia. The RSV genome codes for ten proteins, NS1, NS2, N, P, M, SH, G, F, M2 and L. We aimed to identify the RSV geographical distribution and transmission pattern using site parsimonious frequencies, and investigate hotspot regions across the complete RSV genomes. These results indicated that RSV strains circulating in South and North America are not mixed to the European samples, however, genomes reported from Australia are the direct decedents of European samples. Samples reported from the United Kingdom were found diverse. Further, this report provides a comprehensive mutational analysis of all the individual RSV genes and in particular the 32 hotspot substituting regions circulating across the globe in RSV type A samples. This is the first comprehensive analysis of RSV type A that features mutational frequencies across the whole genome providing more clues for epidemiological control and drug development.

evolutionary biology↗

bioRxiv2022

Addressing Structural Mentoring Barriers in Postdoctoral Training: A Qualitative Study

BackgroundStructural mentoring barriers are policies, practices, and cultural norms that collectively disadvantage marginalized groups and perpetuate disparities in mentoring. While these mentoring barriers can be found early in the training pathway, failure to address or overcome these barriers at the postdoctoral training stage has a direct impact on faculty diversity and national efforts to retain underrepresented groups in research careers. MethodsTo better understand the mentoring barriers faced by postdoctoral trainees, and possible ways to address them, a diverse sample of postdoctoral scholars ("postdocs") from across the United States were asked to participate in focus groups to discuss their training experiences. We conducted five 90-minute focus groups with 32 biomedical postdocs, including 20 (63%) women and 15 (47%) individuals from underrepresented racial/ethnic groups (URG). Participants were well-represented across years of training, and 65% were at least somewhat likely to pursue a research-intensive faculty career, similar to previously reported national averages. ResultsA social ecological framework was used to examine both the upstream and downstream manifestations of structural mentoring barriers, as well as mentor barriers, overall. Themes were categorized on four broad levels: Individual (attitudes, beliefs, knowledge, or behaviors that inform mentoring barriers), Interpersonal (mentoring barriers arising from dyadic, peer, or network relationships), Institutional (departmental, institutional, organizational mentoring barriers), or Systemic (mentoring barriers originating from policies or broad social and cultural norms). Notable structural barriers included (1) academic politics and scientific hierarchy, (2) inequalities resulting from mentor prestige, (3) the (over) reliance on one mentor, (4) the lack of formal training for academic and non-academic careers, and (5) the lack of institutional diversity and institutional mentor training. These structural barriers foster mentoring practices and behaviors that lead to poor work-life balance, poor communication, and research career attrition. To overcome these barriers, postdocs strongly encouraged developing a network or team of mentors and recommended institutional interventions that create more comprehensive professional development, mentorship, and belonging. ConclusionsFor postdoctoral scientists, structural mentoring barriers can permeate down to institutional, interpersonal, and individual levels, impeding a successful transition to an independent research career. It has become clear that large-scale changes in mentoring must come from addressing the policies, practices, and cultural norms that perpetuate poor mentoring. This work provides strong evidence for promoting mentorship networks and cultivating a "mentoring milieu" that fosters a supportive community and a strong culture of mentorship at all levels.

scientific communication and education↗

bioRxiv2022

Structural and Functional Characterization of Novel Phosphotyrosine Phosphatase Protein from Drosophila Melanogaster (Pupal Retina)

A novel pair of protein Tyrosine Phosphatases in Drosophila Melanogaster (pupal retina) has been identified. Phosphotyrosyl protein phosphatases (PTPs) are structurally diverse enzymes increasingly recognized having fundamental role in cellular processes including effects on metabolism, cell proliferation and differentiation. This study presents comparative homology modeling of low molecular weight phosphotyrosine protein phosphatase (PTPs) from Drosophila melanogaster (Dr-PTPs) and their complexation with potent inhibitor HEPES. The 3D structure was predicted based on sequence homology with bovine heart low molecular weight PTPs (Bh-PTPs). The sequence homology is approximately 50% identical to each other and to low molecular weight protein tyrosine phosphatases (PTPs) in other species. Comparison of the 3D structures of Bh-PTPs and Dr-PTPs (primo-2) reveals a remarkable similarity having a four stranded central parallel {beta} sheet with flanking helices on both sides, showing two right-handed {beta}--{beta} motifs. The inhibitor shows similar binding features as seen in other PTPs. The study also highlights the key catalytic residues important for target recognition and PTPs activation. The structure guided studies of both proteins clearly reveal a common mechanism of action, inhibitor binding at the active site and will expected to contribute towards the basic understanding of functional association of this enzyme with other molecules.

biochemistry↗

bioRxiv2020

Virome-wide serological profiling reveals association of herpesviruses with obesity

The relationship between viral infection and obesity has been known for several decades but epidemiological data related to obesity is limited to only a few viral pathogens. To identify associations between viral infections and obesity, a high-throughput virome-wide serological profiling tool, VirScan, was used to measure antibody responses to a wide range of viruses. Serum specimens from 457 Qatari adults (lean=184;obese=273) and 231 Qatari children (lean=111;obese=120) were assessed by VirScan. Pediatric specimens were simultaneously tested by conventional serology for several herpesviruses to validate VirScan results. Viral association with obesity was determined by calculation of odds ratio (OR) and p-values from Fisher test, and by multivariate regression analysis to adjust for age and gender, with Bonferroni correction for multiple testing. Comprehensive serological profiling of Qatari adult population with VirScan revealed positive and negative associations (p<0.05) of antibody responses to members of Herpesviridae and Picornaviridae families, respectively, with obesity. After adjusting p-values for multiple comparisons, only herpes simplex virus 1 (HSV-1) and Rhinovirus A were positively (OR=3.3; 95%CI 2.15-4.99; p=2.787E-08) and negatively (OR=0.4; 95%CI 0.26-0.65; p=1.175E-03) associated with obesity. At the peptide level, higher prevalence of antibodies against several peptide epitopes of HSV-1/2 was positively (OR=2.35-3.82; p[≤]3.981E-05) associated with obesity. No such associations were seen at the species or peptide levels in the pediatric population. By multivariate regression analysis, HSV-1 was independently associated with obesity irrespective of age and gender. These findings are in agreement with limited data on the adipogenic properties of HSV-1 observed in vitro. ImportanceThe state of Qatar has one of the highest rates of obesity and associated morbidities in the world. Although obesity is predominantly caused by the intake of high calorie diet and reduced physical activities, other factors including infections with certain viruses have been reported. Among these viruses, human adenoviruses were widely studied but epidemiological data for other viruses in relation to human obesity are limited. Here, we studied the association of obesity in Qatari adults and children with a wide range of viral pathogens using VirScan, a virome-wide serological profiling tool. Our results indicate significant association HSV-1 with obesity in the adult population only. Furthermore, we have identified a set of HSV peptides as candidate obesogenic factors for future studies.

microbiology↗

bioRxiv2019

Customizable, engineered substrates for rapid screening of cellular cues

Biophysical cues robustly direct cell responses and are thus important tools for in vitro and translational biomedical applications. High throughput platforms exploring substrates with varying physical properties are therefore valuable, however, currently existing platforms are limited in throughput, the biomaterials used, the capability to segregate between different cues and the assessment of dynamic cellular responses. Here we present a multiwell array (3x8) using a substrate engineered with patterns that present topography or rigidity cues welded to a bottomless plate with a 96-well format. Both the patterns on the engineered substrate and the well plate format can be easily customized, permitting systematic and efficient screening of biophysical cues. Here, we demonstrate three multiwell arrays patterned with a variety of topographical and mechanical cues (nano-grooves, soft pillars and nano pillars) tested with three different cell types. Using the multiwell array, we were able to measure cell functionality using analytical modalities such as live microscopy, qPCR and fluorescent immunochemistry. Cardiomyocytes cultured on 5{micro}m grooves showed less variation in electrophysiology and contractile function. Nanopillars with 127 nm height, 100 nm diameter and 300 nm pitch showed improved chondrogenic maintenance from matrix deposition and chondrogenic gene expression. High aspect ratio pillars with an elastic shear modulus of 16 kPa mimicking the cortical bone altered cell adhesion, morphology, and increased expression of osteogenic genes. We have demonstrated the bespoke, controlled and high-throughput properties of the multiwell array that are currently unparalleled in the field today.

bioengineering↗

bioRxiv2019

Nanotopography reveals metabolites that maintain the immunosuppressive phenotype of mesenchymal stem cells

Mesenchymal stem cells (MSCs) are multipotent stem cells that are immunosuppressive and thus of considerable therapeutic potential in transplant operations. However, MSCs rapidly differentiate once in culture, making their large-scale expansion for use in immunosuppressive therapies challenging. Although the differentiation mechanisms of MSCs have been extensively investigated using materials, little is known about how materials can modulate paracrine activities of MSCs. Here, we show for the first time that nanotopography can control the immunomodulatory capacity of MSCs through decreased intracellular tension increasing oxidative glycolysis. We also use the nanotopography to identify bioactive metabolites that modulate intracellular tension, growth and immunomodulatory phenotype of MSCs in standard culture. Our findings show a novel route to support large-scale expansion of functional MSCs for therapeutic purposes

bioengineering↗