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Shen, M.

Publications and source records attributed to Shen, M..

At least 55 records · Page 3Linked to original sources

A novel combination of CDK4/6 and PI3K inhibitors exhibits highly synergistic activity and translational potential in Ewing sarcoma.

Ewing sarcoma is a highly aggressive solid malignancy affecting children and young adults. Ewing sarcoma is driven primarily by EWSR1::FLI1, a fusion oncoprotein that has been notoriously difficult to target with traditional pharmacologic agents. There are numerous examples of preclinical promising combinations of small molecules that are never tested in pediatric clinical trials because agents fail to reach the market due to limited efficacy for common adult cancers. Moreover, the effectiveness of single-agent therapies for cancer treatment is often limited. To address these limitations, we selected 28 compounds that were largely FDA approved or in late stages of clinical development and known to regulate important pathways in Ewing sarcoma. We performed a drug screen in Ewing sarcoma cell lines with 180 combinations of tyrosine kinase inhibitors, cell cycle inhibitors, and conventional chemotherapy. The results of the screen revealed that a PI3K inhibitor, copanlisib, combined with a CDK4/6 inhibitor, ribociclib, exhibited strong synergistic anti-Ewing sarcoma activity. Using proteomic methods such as a reverse-phase protein array and western immunoblotting, we demonstrated that this combination induced a downregulation of the PI3K/AKT pathway as well as proteins involved in cell cycle regulation. We further confirmed these in vitro data using bulk RNA-sequencing. To evaluate the phenotypic effect of the PI3K/CDK4/6 inhibition in Ewing sarcoma lines, we performed apoptosis and cell cycle analyses using flow cytometry and demonstrated that ribociclib primarily induced a G0/G1 arrest with minimal effect on Ewing cell viability but significantly enhanced the apoptotic effect of copanlisib treatment. In a xenograft model of Ewing sarcoma, we demonstrated that the combination therapy significantly prolonged survival compared to treatment with either vehicle or single-agent therapy alone. Our findings identify a new candidate therapy combination for Ewing sarcoma using FDA-approved drugs and provide a resource of additional potential synergistic combinations for future validation. Statement of translational relevanceTreatment of patients with newly diagnosed Ewing sarcoma involves intensive multi- agent chemotherapy, radiation, and surgery, often leading to long-term toxicities. Children with relapsed or metastatic disease experience poor outcomes with five-year overall survival rates of only 15 to 30 percent. Therefore, new therapeutic approaches are urgently needed. Our drug screen revealed several promising combinations with synergistic anti-Ewing sarcoma activity including the PI3K inhibitor copanlisib with the CDK4/6 inhibitor ribociclib. This combination also significantly improved survival in a mouse xenograft model of Ewing sarcoma compared to treatment with vehicle or either drug alone. Pre-clinical validation of a combination therapy composed of two FDA- approved drugs nominates this combination for early phase trials for patients with with relapsed or refractory Ewing sarcoma, a group of patients greatly in need of new therapeutic opportunities. The data generated by our drug screen may also be used as a resource to identify other promising combinations for future validation as Ewing sarcoma therapies.

cancer biology↗

Reinforcement learning guides single-cell sequencing in decoding lineage and cell fate decisions

The rapid development of single-cell sequencing offers an unparalleled opportunity to delineate the heterogeneity of individual cells. However, current methods struggle to pinpoint the states of cell fate decisions. In this study, we introduce a novel approach called Single-cell Reinforcement Learning (scRL), which integrates reinforcement learning into single-cell data analysis using an actor-critic architecture. Among existing dimensionality reduction methods, we identified one with the best interpretability. Based on this latent space and combined with our scRL algorithm, we assessed the intensity of fate decisions at the single-cell level. Extensive evaluations demonstrate that scRL outperforms existing techniques, as well as their variants and alternative approaches, in assessing cell fate decisions. Moreover, scRL offers an alternative method for evaluating the intensity of cell lineage differentiation which shows competitive interpretability as well. The superiority of scRL in assessing fate decisions is confirmed across several types of single-cell datasets.

bioinformatics↗

Systematic identification of secondary bile acid production genes in global microbiome

Microbial metabolism of bile acids (BAs) is crucial for maintaining homeostasis in vertebrate hosts and environments. Although certain organisms involved in BA metabolism have been identified, a global, comprehensive elucidation of the microbes, metabolic enzymes, and BA remains incomplete. To bridge this gap, we employed hidden Markov models to systematically search in a large-scale and high-quality search library comprising 28,813 RefSeq multi-kingdom microbial complete genomes, which enabled us to construct a secondary bile acid (SBA)-production gene catalog. This catalog greatly expanded the distribution of SBA-production genes across 11 phyla, encompassing bacteria, archaea and fungi, and extended to 14 habitats spanning hosts and environmental contexts. Furthermore, we highlighted the associations between SBAs and gastrointestinal and hepatic disorders, including inflammatory bowel disease, colorectal cancer and nonalcoholic fatty liver disease, further elucidating disease-specific alterations in SBA-production genes. Additionally, we proposed the pig as a particularly suitable animal model for investigating SBA production in humans, given its closely aligned SBA-production gene composition. This gene catalog provides a comprehensive and reliable foundation on microbial BA metabolism for future studies, offering new insights into the microbial contributions to health and disease.

genomics↗

Genetic screening and metabolomics identify glial adenosine metabolism as a therapeutic target in Parkinson's disease

Neuronal alpha-synucleinopathies, including Parkinson's disease (PD) and dementia with Lewy bodies (DLB), lack disease-modifying therapies. We developed a Drosophila model for identifying novel glial-based therapeutic targets for alpha-synucleinopathies. In this model, human alpha-synuclein is expressed in neurons and individual genes are independently knocked down in glia. We performed a forward genetic screen, knocking down the entire Drosophila kinome in glia in alpha-synuclein expressing flies. Among the top hits were five genes (Ak1, Ak6, Adk1, Adk2, and awd) involved in adenosine metabolism. Knockdown of each gene increased brain adenosine levels, improved locomotor dysfunction, reduced alpha-synuclein oligomer levels, and rescued neurodegeneration. We determined that the mechanism of neuroprotection requires adenosine signaling through the neuronal adenosine receptor (AdoR) in Drosophila. These experiments support glial adenosine as a novel therapeutic target in PD.

neuroscience↗

Transplantation of exogenous mitochondria mitigates myocardial dysfunction after cardiac arrest

The incidence of post-cardiac arrest myocardial dysfunction (PAMD) is high, and there is currently no effective treatment available. This study aims to investigate the protective effects of exogenous mitochondrial transplantation. Exogenous mitochondrial transplantation can enhance myocardial function and improve the survival rate. Mechanistic studies suggest that mitochondrial transplantation can limit impairment in mitochondrial morphology, augment the activity of mitochondrial complexes II and IV, and raise ATP level. As well, mitochondrial therapy ameliorated oxidative stress imbalance, reduced myocardial injury, and thus improved PAMD after cardiopulmonary resuscitation (CPR).

systems biology↗

A comprehensive collection of pain and addiction targets and compounds library for high throughput screening and AI-driven drug discovery

As part of the NIH Helping to End Addiction Long-term (HEAL) Initiative, the National Center for Advancing Translational Sciences (NCATS) is dedicated to the development of new pharmacological tools and investigational drugs for managing and treating pain, as well as the prevention and treatment of opioid misuse and addiction. In line with these objectives, we created a comprehensive, annotated small molecule library including drugs, probes, and tool compounds that act on published pain and addiction-relevant targets. Nearly 3,000 small molecules associated with approximately 200 known and hypothesized HEAL targets have been assembled, curated, and annotated in one collection. Physical samples of the library compounds have been acquired and plated in 1536-well format, enabling rapid and efficient high throughput screen (HTS) against a wide range of assays. The creation of the HEAL Targets and Compounds Library, coupled with an integrated computational platform for AI-driven machine learning (ML), structural modeling, and virtual screening (VS), provides a valuable source for strategic drug repurposing, innovative profiling, and hypothesis testing of novel targets related to pain and opioid use disorder (OUD). The library is available to investigators for screening pain and OUD-relevant phenotypes.

bioinformatics↗

Lipid Nanoparticle-Associated Inflammation is Triggered by Sensing of Endosomal Damage: Engineering Endosomal Escape without Side Effects

Lipid nanoparticles (LNPs) have emerged as the dominant platform for RNA delivery, based on their success in the COVID-19 vaccines and late-stage clinical studies in other indications. However, we and others have shown that LNPs induce severe inflammation, and massively aggravate pre-existing inflammation. Here, using structure-function screening of lipids and analyses of signaling pathways, we elucidate the mechanisms of LNP-associated inflammation and demonstrate solutions. We show that LNPs hallmark feature, endosomal escape, which is necessary for RNA expression, also directly triggers inflammation by causing endosomal membrane damage. Large, irreparable, endosomal holes are recognized by cytosolic proteins called galectins, which bind to sugars on the inner endosomal membrane and then regulate downstream inflammation. We find that inhibition of galectins abrogates LNP-associated inflammation, both in vitro and in vivo. We show that rapidly biodegradable ionizable lipids can preferentially create endosomal holes that are smaller in size and reparable by the endosomal sorting complex required for transport (ESCRT) pathway. Ionizable lipids producing such ESCRT-recruiting endosomal holes can produce high expression from cargo mRNA with minimal inflammation. Finally, we show that both routes to non-inflammatory LNPs, either galectin inhibition or ESCRT-recruiting ionizable lipids, are compatible with therapeutic mRNAs that ameliorate inflammation in disease models. LNPs without galectin inhibition or biodegradable ionizable lipids lead to severe exacerbation of inflammation in these models. In summary, endosomal escape induces endosomal membrane damage that can lead to inflammation. However, the inflammation can be controlled by inhibiting galectins (large hole detectors) or by using biodegradable lipids, which create smaller holes that are reparable by the ESCRT pathway. These strategies should lead to generally safer LNPs that can be used to treat inflammatory diseases.

bioengineering↗

Efficient Generation of Human Pluripotent Stem Cells from Frozen Cord Tissue via Chemical Reprogramming

Chemical reprogramming presents an innovative approach for generating induced pluripotent stem cells (iPSCs), bypassing the genetic instability and safe concern associated with viral vector approach. We describe a novel, efficient chemical method for reprogramming human umbilical cord tissue-derived mesenchymal stem cells (MSCs) into induced pluripotent stem cells (iPSCs). Compared to previous sources like adipose tissue and skin, frozen umbilical cord tissue offers an abundant, non-invasive, long-term storable, and ethically sound cell source. Our findings not only showcase the feasibility and safety of utilizing chemical reprogramming on cells from frozen umbilical cords but also underscore its potential in regenerative medicine, especially for developing safer and more effective therapies for cardiovascular diseases.

cell biology↗

Machine Learned Classification of Ligand Intrinsic Activities at Human μ-Opioid Receptor

Opioids are small-molecule agonists of {micro}-opioid receptor ({micro}OR), while reversal agents such as naloxone are antagonists of {micro}OR. Here we developed machine learning (ML) models to classify the intrinsic activities of ligands at the human {micro}OR based on the SMILE strings and two-dimensional molecular descriptors. We first manually curated a database of 983 small molecules with measured Emax values at the human {micro}OR. Analysis of the chemical space allowed identification of dominant scaffolds and structurally similar agonists and antagonists. Decision tree models and directed message passing neural networks (MPNNs) were then trained to classify agonistic and antagonistic ligands. The hold-out test AUCs (areas under the receiver operator curves) of the extra-tree (ET) and MPNN models are 91.5 {+/-} 3.9% and 91.8 {+/-} 4.4%, respectively. To overcome the challenge of small dataset, a student-teacher learning method called tri-training with disagreement was tested using an unlabeled dataset comprised of 15,816 ligands of human, mouse, or rat {micro}OR,{kappa} OR, or{delta} OR. We found that the tri-training scheme was able to increase the hold-out AUC of MPNN to as high as 95.7%. Our work demonstrates the feasibility of developing ML models to accurately predict the intrinsic activities of {micro}OR ligands, even with limited data. We envisage potential applications of these models in evaluating uncharacterized substances for public safety risks and discovering new therapeutic agents to counteract opioid overdoses. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/588485v2_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1bf13f7org.highwire.dtl.DTLVardef@1b7f04aorg.highwire.dtl.DTLVardef@1009569org.highwire.dtl.DTLVardef@1515139_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Nanoporous PEGDA ink for High-Resolution Additive Manufacturing of Scaffolds for Organ-on-a-Chip

Polydimethylsiloxane (PDMS), commonly used in organ-on-a-chip (OoC) systems, faces limitations in replicating complex geometries, hindering its effectiveness in creating 3D OoC models. In contrast, poly(ethylene glycol)diacrylate (PEGDA-250), favored for its fabrication ease and resistance to small molecule absorption, is increasingly used for 3D printing microfluidic devices. However, applications in cell culture have been limited due to poor cell adhesion. Here, we introduce a nanoporous PEGDA ink (P-PEGDA) designed to enhance cell adhesion. P-PEGDA is formulated with a porogen, photopolymerized, followed by the porogen removal. Utilizing P-PEGDA, complex microstructures and membranes as thin as 27 {micro}m were 3D-printed. Porogen concentrations from 10-30% were tested yielding constructs with increasing porosity and oxygen permeability surpassing PDMS, without compromising printing resolution. Tests across four cell lines showed >80% cell viability, with a notable 77-fold increase in MDA-MB-231 cell coverage on the porous scaffolds. Finally, we introduce an OoC model comprising a gyroid scaffold with a central opening filled with a cancer spheroid. This setup, after a 14-day co-culture, demonstrated significant endothelial sprouting and integration within the spheroid. The P-PEGDA formulation is suitable for high-resolution 3D printing of constructs for 3D cell culture and OoC owing to its printability, gas permeability, biocompatibility, and cell adhesion.

bioengineering↗

Study on genetic differentiation of Schistosome japonicum intermediate hosts Oncomelania hupensis robertsoni in hilly regions of China: using the complete mitochondrial genome

ObjectiveOncomelania hupensis robertsoni is the only intermediate host of Schistosoma japonicum in western China, its genetic differentiation directly impacts the susceptibility of Schistosoma japonicum. This study aimed to sequence the complete mitochondrial genome of Oncomelania hupensis robertsoni Yunnan strain and analyze the genetic differentiation of Oncomelania hupensis robertsoni in hilly regions of China. MethodsSamples were from 14 administrative villages in Yunnan Province of China, with 30 Oncomelania hupensis per village, and the complete mitochondrial genome was sequenced. Additional, we retrieved 14 other region Oncomelania hupensis of complete mitochondrial sequences from GenBank, and a comprehensive analysis of the genetic differentiation of Oncomelania hupensis robertsoni was conducted by constructing phylogenetic trees, calculating genetic distances, and analyzing homogeneity. ResultsA total of 26 complete mitochondrial sequences were determined. The length of genome ranged from 15,181 to 15,187 bp, and the base composition of the genome was A+T (67.5%) and G+C content (32.5%). This genome encoded 37 genes, including 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and a non-coding region rich in A+T. Using the Philippines genotypes as outgroup, the phylogenetic trees and homology analysis confirmed the existence of two distinct phylogroups, Oncomelania hupensis robertsoni and the remaining 9 provincial genotypes. Oncomelania hupensis robertsoni is subdivided into Oncomelania hupensis robertsoni Yunnan strain and Sichuan strain, with a genetic distance of 0.0834. Oncomelania hupensis robertsoni Yunnan strain is subdivided into two subbranches, "Yunnan North" and "Yunnan South", with a genetic distance of 0.0216, and the samples exhibited over 97% homology. ConclusionOncomelania hupensis robertsoni Yunnan strain exhibits a higher level of genetic homology and clear north-south differentiation, the distribution characteristics were closely associated with watershed distribution. This work reported the first mitochondrial genome of Oncomelania hupensis robertsoni Yunnan strain, which could be used as an important reference genome for Oncomelania hupensis, and also provide a theoretical basis for explaining the distribution pattern of Oncomelania hupensis robertsoni and control of schistosomiasis. Author SummaryOncomelania hupensis (O. hupensis) is the only intermediate host of Schistosoma japonicum (S. japonicum), O. hupensis residing in different geographical regions display morphological differences and genetic variations, along with varying susceptibility to S. japonicum. In this study, we sequenced 26 complete mitochondrial genome of O. hupensis robertsoni Yunnan strain (O. h. r. Yunnan strain), the length of genome ranged from 15,181 to 15,187 bp, and the base composition of the genome was A+T (67.5%) and G+C content (32.5%). This genome encoded 37 genes, including 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and a non-coding region rich in A+T. Additional, we retrieved 14 other region O. hupensis of complete mitochondrial sequences from GenBank. The phylogenetic trees and homology analysis confirmed that O. hupensis robertsoni is subdivided into Yunnan strain and Sichuan strain, and O. h. r. Yunnan strain is subdivided into two subbranches, "Yunnan North" and "Yunnan South", the samples exhibited over 97% homology. This work reported the first mitochondrial genome of O. h. r. Yunnan strain, which could be used as an important reference genome for O. hupensis, and also provide a molecular biology-based theoretical foundation for understanding the genetic differentiation of O. hupensis.

genomics↗

Murine uterine gland branching is necessary for gland function in implantation

Uterine glands are branched, tubular structures whose secretions are essential for pregnancy success. It is known that pre-implantation glandular expression of leukemia inhibitory factor (LIF) is crucial for embryo implantation, however contribution of uterine gland structure to gland secretions such as LIF is not known. Here we use mice deficient in estrogen receptor 1 (ESR1) signaling to uncover the role of ESR1 signaling in gland branching and the role of a branched structure in LIF secretion and embryo implantation. We observed that deletion of ESR1 in neonatal uterine epithelium, stroma and muscle using the progesterone receptor PgrCre causes a block in uterine gland development at the gland bud stage. Embryonic epithelial deletion of ESR1 using a mullerian duct Cre line - Pax2Cre, displays gland bud elongation but a failure in gland branching. Surprisingly, adult uterine epithelial deletion of ESR1 using the lactoferrin-Cre (LtfCre) displays normally branched uterine glands. Intriguingly, unbranched glands from Pax2Cre Esr1flox/flox uteri fail to express glandular pre-implantation Lif, preventing implantation chamber formation and embryo alignment along the uterine mesometrial-antimesometrial axis. In contrast, branched glands from LtfCre Esr1flox/flox uteri display reduced expression of glandular Lif resulting in delayed implantation chamber formation and embryo-uterine axes alignment but deliver a normal number of pups. Finally, pre-pubertal unbranched glands in control mice express Lif in the luminal epithelium but fail to express Lif in the glandular epithelium even in the presence of estrogen. These data strongly suggest that branched glands are necessary for pre-implantation glandular Lif expression for implantation success. Our study is the first to identify a relationship between the branched structure and secretory function of uterine glands and provides a framework for understanding how uterine gland structure-function contributes to pregnancy success.

developmental biology↗

Interrogating Proteome-wide Cysteine Ligandabilities: Crystallography Meets Chemoproteomics Through Machine Learning

Machine learning (ML) identification of covalently ligandable sites may accelerate targeted covalent inhibitor design and help expand the druggable proteome space. Here we report the rigorous development and validation of the tree-based models and convolutional neural networks (CNNs) trained on a newly curated database (LigCys3D) of over 1,000 liganded cysteines in nearly 800 proteins represented by over 10,000 three-dimensional structures in the protein data bank. The unseen tests yielded 94% and 93% AUCs (area under the receiver operating characteristic curve) for the tree models and CNNs, respectively. Based on the AlphaFold2 predicted structures, the ML models recapitulated the newly liganded cysteines in the PDB with over 90% recall values. To assist the community of covalent drug discoveries, we report the predicted ligandable cysteines in 392 human kinases and their locations in the sequence-aligned kinase structure including the PH and SH2 domains. Furthermore, we disseminate a searchable online database LigCys3D (https://ligcys.computchem.org/) and a web prediction server DeepCys (https://deepcys.computchem.org/), both of which will be continuously updated and improved by including newly published experimental data. The present work represents a first step towards the ML-led integration of big genome data and structure models to annotate the human proteome space for the next-generation covalent drug discoveries.

bioinformatics↗

Improving the Circularization Efficiency, Stability and Translatability of Circular RNA by circDesign

Synthetic circular RNA (circRNA) has emerged as a promising platform for vaccine and therapeutic development, featuring its uniqueness in a closed-loop structure, cap-independent translation mechanism, and prolonged expression. However, the rational design of a circRNA sequence to jointly improve its stability and protein coding potential remains challenging. In this study, we present circDesign, an efficient algorithm to achieve the optimal design of circRNA by ensuring optimized folding of each segment, which leads to enhanced circularization efficiency, stability, and translatability. Using rabies virus glycoprotein (RABV-G) as the model antigen, we demonstrated that circDesign-generated circRNAs exhibited higher stability and protein translation efficiency in vitro and in vivo compared to other codon adaptation index (CAI)-optimized sequences, thus leading to enhanced in vivo immunogenicity. Ribosome and polysome profiling further revealed that an intact internal ribosome entry site (IRES) structure is critical for efficient translation. By intentionally disrupting the IRES motifs, we observed that the resulting circRNA sequences had lower translatability compared to circDesign-generated sequences. Taken together, our circular RNA design algorithm provides a general strategy to leverage the capability of circRNA as next-generation vaccines or therapeutics.

bioengineering↗

Dearth of smoking-induced mutations in oncogene-driven non-small-cell lung cancer despite smoking exposure

Non-small cell lung cancers (NSCLCs) in non-smokers are mostly driven by mutations in the oncogenes EGFR, ERBB2, and MET, and fusions involving ALK and RET. We term these "non-smoking-related oncogenes" (NSROs). In addition to occurring in non-smokers, NSRO-driven tumors also occur in smokers, and the clonal architecture and genomic landscape of these tumors remain unknown. We investigated genomic and transcriptomic alterations in 173 tumor sectors from 48 patients with NSRO-driven or typical-smoking NSCLCs. NSRO-driven NSCLCs in smokers and non-smokers have similar genomic landscapes. Surprisingly, even in patients with prominent smoking histories, the mutational signature caused by tobacco smoking was essentially absent in NSRO-driven NSCLCs. However, NSRO-driven NSCLCs in smokers had higher transcriptomic activities related to regulation of the cell cycle, suggesting that smoking still affects tumor phenotype independently of genomic alterations. Statement of significanceThis study highlights the lack of genomic scars caused by smoking in NSCLCs driven by non-smoking-related oncogenes regardless of smoking history. The impact of smoking on these tumors is mainly non-genomic. The transcriptomic features of NSCLCs associated with smoking may help in the development of therapeutic approaches.

cancer biology↗

Structural insights into Rad18 targeting by the SLF1 BRCT domains

Rad18 interacts with the SMC5/6 localization factor 1 (SLF1) to recruit the SMC5/6 complex to DNA damage sites for repair. The mechanism of the specific Rad18 recognition by SLF1 is unclear. Here, we present crystal structure of the tandem BRCT repeat (tBRCT) in SLF1 (SLF1tBRCT) bound with the interacting Rad18 peptide. Our structure and biochemical studies demonstrate that SLF1tBRCT interacts with two phosphoserines and adjacent residues in Rad18 for high affinity and specificity Rad18 recognition. We found that SLF1tBRCT utilizes mechanisms common among tBRCTs as well as unique ones for Rad18 binding, the latter include interactions with an -helical structure in Rad18 that has not been observed in other tBRCT-bound ligand proteins. Our work provides structural insights into Rad18 targeting by SLF1 and expands the understanding of BRCT-mediated complex assembly.

biochemistry↗

High-Resolution Additive Manufacturing of a Biodegradable Elastomer with a Low-Cost LCD 3D Printer

Artificial organs and organs-on-a-chip are of great clinical and scientific interest and have recently been made by additive manufacturing, but depend on, and benefit from, biocompatible, biodegradable, and soft materials. Poly(octamethylene maleate (anhydride) citrate (POMaC) meets these criteria and has gained popularity, and as in principle, it can be photocured and is amenable to vat-photopolymerization (VP) 3D printing, but only low-resolution structures have been produced so fa. Here, we introduce a VP-POMaC ink and demonstrate 3D printing of high resolution (80 {micro}m) and complex 3D structures using low-cost ([~]US$300) liquid-crystal display (LCD) printers. The ink includes POMaC, a diluent and porogen additive to reduce viscosity within the range of VP, and a crosslinker to speed up reaction kinetics. The mechanical properties of the cured ink were tuned to match the elastic moduli of different tissues simply by varying the porogen concentration. The biocompatibility was assessed by cell culture which yielded 80% viability and the potential for tissue engineering illustrated with a 3D printed gyroid seeded with cells. VP-POMaC and low-cost LCD printers make the additive manufacturing of high resolution, elastomeric, and biodegradable constructs widely accessible, paving the way for a myriad of applications in tissue engineering, implants, organ-on-a-chip, wearables, and soft robotics.

bioengineering↗

Digital Manufacturing of Functional Ready-to-Use Microfluidic Systems

Digital manufacturing (DM) strives for the seamless manufacture of a functional device from a digital file. DM holds great potential for microfluidics, but requirements for embedded conduits and high resolution beyond the capability of common manufacturing equipment, and microfluidic systems dependence on peripherals (e.g. connections, power supply, computer), have limited its adoption. Microfluidic capillaric circuits (CCs) are structurally-encoded, self-contained microfluidic systems that operate and self-fill thanks to precisely tailored hydrophilicity. CCs were heretofore hydrophilized in a plasma chamber, but which only produces transient hydrophilicity, lacks reproducibility, and limits CC design to open surface channels sealed with a tape. Here we introduce the additive DM of monolithic, fully functional and intrinsically hydrophilic CCs. CCs were 3D printed with commonly available light engine-based 3D printers using polyethylene(glycol)diacrylate-based ink co-polymerized with hydrophilic acrylic acid crosslinkers and optimized for hydrophilicity and printability. A new, robust capillary valve design and embedded conduits with circular cross-sections that prevent bubble trapping are presented, and complex interwoven circuit architectures created, and their use illustrated with an immunoassay. Finally, the need for external paper capillary pumps is eliminated by directly embedding the capillary pump in the chip as a porous gyroid structure, realizing fully functional, monolithic CCs. Thence, a computer-aided design file can be made into a CC by commonly available 3D printers in less than 30 minutes enabling low-cost, distributed, DM of fully functional ready-to-use microfluidic systems.

bioengineering↗