FRET Sensor-Modified Synthetic Hydrogels for Real-Time Monitoring of Cell-Derived Matrix Metalloproteinase Activity using Fluorescence Lifetime Imaging.

Matrix remodeling plays central roles in a range of physiological and pathological processes and is driven predominantly by the activity of matrix metalloproteinases (MMPs), which degrade extracellular matrix (ECM) proteins. Our understanding of how MMPs regulate cell and tissue dynamics is often incomplete as in vivo approaches are lacking and many in vitro strategies cannot provide high-resolution, quantitative measures of enzyme activity in situ within tissue-like 3D microenvironments. Here, we incorporate a Förster resonance energy transfer (FRET) sensor of MMP activity into fully synthetic hydrogels that mimic many properties of the native ECM. We then use fluorescence lifetime imaging to provide a real-time, fluorophore concentration-independent quantification of MMP activity, establishing a highly accurate, readily adaptable platform for studying MMP dynamics in situ. MCF7 human breast cancer cells encapsulated within hydrogels highlight the detection of MMP activity both locally, at the sub-micron level, and within the bulk hydrogel. Our versatile platform may find use in a range of biological studies to explore questions in the dynamics of cancer metastasis, development, and tissue repair by providing high-resolution, quantitative and in situ readouts of local MMP activity within native tissue-like environments.

Climate Change Shrinks and Fragments Salmon Habitats in a Snow-Dependent Region.

Climate change threatens biodiversity through global alteration of habitats, but efficient conservation responses are often hindered by imprecise downscaling of impacts. Besides thermal effects, warming also drives important ancillary environmental changes, such as when river hydrology evolves in response to climate forcing. Earlier snowmelt runoff and summer flow declines are broadly manifested in snow-dependent regions and relevant to socioeconomically important cold-water fishes. Here, we mechanistically quantify how climate-induced summer flow declines during historical and future periods cause complex local changes in Chinook salmon (Oncorhynchus tshawytscha) habitats for juveniles and spawning adults. Changes consisted of large reductions in useable habitat area and connectivity between the main channel and adjacent off-channel habitats. These reductions decrease the capacity of freshwater habitats to support historical salmon abundances and could pose risks to population persistence in some areas.

DC-SCRIPT affects mammary organoids branching morphogenesis by modulating the FGFR1-pERK signaling axis.

Loss of expression of the transcription regulator DC-SCRIPT (Zfp366) is a prominent prognostic event in estrogen receptor-positive breast cancer patients. Studying the inherent link between breast morphogenesis and tumorigenesis, we recently reported that DC-SCRIPT affects normal mammary branching morphogenesis and mammary epithelium homeostasis. Here we investigated the molecular mechanism involved in DC-SCRIPT mediated regulation of FGF2 induced mammary branching morphogenesis in a 3D organoid culture system. Our data show that the delayed mammary organoid branching observed in DC-SCRIPT-/- organoids cannot be compensated for by increasing FGF2 levels. Interestingly, FGFR1, the dominant FGF2 receptor, was expressed at a significantly lower level in basal epithelial cells of DC-SCRIPT deficient organoids relative to wildtype organoids. A potential link between DC-SCRIPT and FGFR1 was further supported by the predicted locations of the DC-SCRIPT DNA binding motif at the Fgfr1 gene. Moreover, ERK1/2 phosphorylation downstream of the FGFR1 pathway was decreased in basal epithelial cells of DC-SCRIPT deficient organoids. Altogether, this study shows a relationship between DC-SCRIPT and FGFR1 related pERK signaling in modulating the branching morphogenesis of mammary organoids in vitro.

Linking multi-media modeling with machine learning to assess and predict lake Chlorophyll a concentrations.

Eutrophication and excessive algal growth pose a threat on aquatic organisms and the health of the public, environment, and the economy. Understanding what drives excessive algal growth can inform mitigation measures and aid in advance planning to minimize impacts. We demonstrate how simulated data from weather, hydrological, and agroecosystem numerical prediction models can be combined with machine learning (ML) to assess and predict Chlorophyll a (Chl a) concentrations, a proxy for lake eutrophication and algal biomass. The study area is Lake Erie for a 16-year period, 2002-2017. A total of 20 environmental variables from linked and coupled physical models are used as input features to train the ML model with Chl a observations from 16 measuring stations. Included are meteorological variables from the Weather Research and Forecasting (WRF) model, hydrological variables from the Variable Infiltration Capacity (VIC) model, and agricultural management practice variables from the Environmental Policy Integrated Climate (EPIC) agroecosystem model. The consolidation of these variables is conducive to a successful prediction of Chl a. Aside from the synergistic effects that weather, hydrology, and fertilizers have on eutrophication and excessive algal growth, we found that the application of different forms of both P and N fertilizers are highly ranked for the prediction of Chl a concentration. The developed ML model successfully predicts Chl a with a coefficient of determination of 0.81, bias of -0.12 µg/l and RMSE of 4.97 µg/l. The developed ML-based modeling approach can be used for impact assessment of agriculture practices in a changing climate that affect Chl a concentrations in Lake Erie.

DC-SCRIPT deficiency delays mouse mammary gland development and branching morphogenesis.

Mammary glands are unique organs in which major adaptive changes occur in morphogenesis and development after birth. Breast cancer is the most common cancer and a major cause of mortality in females worldwide. We have previously identified the loss of expression of the transcription regulator DC-SCRIPT (Zfp366) as a prominent prognostic event in estrogen receptor positive breast cancer patients. DC-SCRIPT affects multiple transcriptional events in breast cancer cells, including estrogen and progesterone receptor-mediated transcription, and promotes CDKN2B-related cell cycle arrest. As loss of DC-SCRIPT expression appears an early event in breast cancer development, we here investigated the role of DC-SCRIPT in mammary gland development using wild-type and DC-SCRIPT knockout mice. Mice lacking DC-SCRIPT exhibited severe breeding problems and showed significant growth delay relative to littermate wild-type mice. Subsequent analysis revealed that DC-SCRIPT was expressed in mouse mammary epithelium and that DC-SCRIPT deficiency delayed mammary gland morphogenesis in vivo. Finally, analysis of 3D mammary gland organoid cultures confirmed that loss of DC-SCRIPT dramatically delayed mammary organoid branching in vitro. The study shows for the first time that DC-SCRIPT deficiency delays mammary gland morphogenesis in vivo and in vitro. These data define DC-SCRIPT as a novel modulator of mammary gland development.

Antibiotic drug tigecycline reduces neuroblastoma cells proliferation by inhibiting Akt activation in vitro and in vivo.

As the first member of glycylcycline bacteriostatic agents, tigecycline is approved as a novel expanded-spectrum antibiotic, which is clinically available. However, accumulating evidence indicated that tigecycline was provided with the potential application in cancer therapy. In this paper, tigecycline was shown to exert an anti-proliferative effect on neuroblastoma cell lines. Furthermore, it was found that tigecycline induced G1-phase cell cycle arrest instead of apoptosis by means of Akt pathway inhibition. In neuroblastoma cell lines, the Akt activator insulin-like growth factor-1 (hereafter referred to as IGF-1) reversed tigecycline-induced cell cycle arrest. Besides, tigecycline inhibited colony formation and suppressed neuroblastoma cells xenograft formation and growth. After tigecycline treatment in vivo, the Akt pathway inhibition was confirmed as well. Collectively, our data provided strong evidences that tigecycline inhibited neuroblastoma cells growth and proliferation through the Akt pathway inhibition in vitro and in vivo. In addition, these results were supported by previous studies concerning the application of tigecycline in human tumors treatment, suggesting that tigecycline might act as a potential candidate agent for neuroblastoma treatment.

Antibiotic drug tigecycline inhibited cell proliferation and induced autophagy in gastric cancer cells.

Tigecycline acts as a glycylcycline class bacteriostatic agent, and actively resists a series of bacteria, specifically drug fast bacteria. However, accumulating evidence showed that tetracycline and their derivatives such as doxycycline and minocycline have anti-cancer properties, which are out of their broader antimicrobial activity. We found that tigecycline dramatically inhibited gastric cancer cell proliferation and provided an evidence that tigecycline induced autophagy but not apoptosis in human gastric cancer cells. Further experiments demonstrated that AMPK pathway was activated accompanied with the suppression of its downstream targets including mTOR and p70S6K, and ultimately induced cell autophagy and inhibited cell growth. So our data suggested that tigecycline might act as a candidate agent for pre-clinical evaluation in treatment of patients suffering from gastric cancer.

Association of single-nucleotide polymorphisms in a metabotropic glutamate receptor GRM3 gene subunit to alcohol-dependent male subjects.

AIMS: The purpose of this study was to investigate the association between the metabotropic glutamate receptor 3 (GRM3) subunit gene and alcohol dependence by the single-nucleotide polymorphisms (SNPs). METHODS: Two hundred and forty-eight male alcohol-dependent patients and 235 male control subjects were recruited. Ten SNPs in the GRM3 region were studied, and genotyping of SNPs was performed by ligase detection reactions. RESULTS: We found highly significant differences in allele and genotype frequencies of rs6465084 between the alcohol-dependent and control group, with the greater frequency of A allele of SNP rs6465084 in alcohol-dependent group. We also found significant differences of haplotype frequencies in five combinations (including TAATATT, CAGTATT, TCGTATT, CAATAGC, TAATATC) in the linkage disequilibrium constructed by seven SNPs between the groups. CONCLUSION: Our results supplied the first evidence that the polymorphism of GRM3 gene associates with the morbidity of alcohol dependence in human being, which may support a new potential target for alcoholism treatment.

Production of Neuroepithelial Organoids from Human-Induced Pluripotent Stem Cells for Mimicking Early Neural Tube Development.

Organoids have emerged as robust tools for unravelling the mechanisms that underly tissue development. They also serve as important in vitro systems for studying fundamentals of stem cell behavior and for building advanced disease models. During early development, a crucial step in the formation of the central nervous system is patterning of the neural tube dorsal-ventral (DV) axis. Here we describe a simple and rapid culture protocol to produce human neuroepithelial (NE) cysts and DV-patterned organoids from single human-induced pluripotent stem cells (hiPSCs). Rather than being embedded within a matrix, hiPSCs undergo a 5-day differentiation process in medium containing soluble extracellular matrix and are allowed to self-organize into 3D cysts with defined central lumen structures that express early neuroepithelial markers. Moreover, upon stimulation with sonic hedgehog proteins and all-trans retinoic acid, NE cysts further develop into NE organoids with DV patterning. This rapid generation of patterned NE organoids using simple culture conditions enables mimicking, monitoring, and longitudinal manipulation of NE cell behavior. This straightforward culture system makes NE organoids a tractable model for studying neural stem cell self-organization and early neural tube developmental events.

PMANet: a time series forecasting model for Chinese stock price prediction.

Forecasting stock movements is a crucial research endeavor in finance, aiding traders in making informed decisions for enhanced profitability. Utilizing actual stock prices and correlating factors from the Wind platform presents a potent yet intricate forecasting approach. While previous methodologies have explored this avenue, they encounter challenges including limited comprehension of interrelations among stock data elements, diminished accuracy in extensive series, and struggles with anomaly points. This paper introduces an advanced hybrid model for stock price prediction, termed PMANet. PMANet is founded on Multi-scale Timing Feature Attention, amalgamating Multi-scale Timing Feature Convolution and Ant Particle Swarm Optimization. The model elevates the understanding of dependencies and interrelations within stock data sequences through Probabilistic Positional Attention. Furthermore, the Encoder incorporates Multi-scale Timing Feature Convolution, augmenting the model's capacity to discern multi-scale and significant features while adeptly managing lengthy input sequences. Additionally, the model's proficiency in addressing anomaly points in stock sequences is enhanced by substituting the optimizer with Ant Particle Swarm Optimization. To ascertain the model's efficacy and applicability, we conducted an empirical study using stocks from four pivotal industries in China. The experimental outcomes demonstrate that PMANet is both feasible and versatile in its predictive capability, yielding forecasts closely aligned with actual values, thereby fulfilling application requirements more effectively.

Can generative AI replace immunofluorescent staining processes? A comparison study of synthetically generated cellpainting images from brightfield.

Cell imaging assays utilising fluorescence stains are essential for observing sub-cellular organelles and their responses to perturbations. Immunofluorescent staining process is routinely in labs, however the recent innovations in generative AI is challenging the idea of wet lab immunofluorescence (IF) staining. This is especially true when the availability and cost of specific fluorescence dyes is a problem to some labs. Furthermore, staining process takes time and leads to inter-intra-technician and hinders downstream image and data analysis, and the reusability of image data for other projects. Recent studies showed the use of generated synthetic IF images from brightfield (BF) images using generative AI algorithms in the literature. Therefore, in this study, we benchmark and compare five models from three types of IF generation backbones-CNN, GAN, and diffusion models-using a publicly available dataset. This paper not only serves as a comparative study to determine the best-performing model but also proposes a comprehensive analysis pipeline for evaluating the efficacy of generators in IF image synthesis. We highlighted the potential of deep learning-based generators for IF image synthesis, while also discussed potential issues and future research directions. Although generative AI shows promise in simplifying cell phenotyping using only BF images with IF staining, further research and validations are needed to address the key challenges of model generalisability, batch effects, feature relevance and computational costs.

A New Approach to Predict Tributary Phosphorus Loads Using Machine Learning- and Physics-Based Modeling Systems.

Tributary phosphorus (P) loads are one of the main drivers of eutrophication problems in freshwater lakes. Being able to predict P loads can aid in understanding subsequent load patterns and elucidate potential degraded water quality conditions in downstream surface waters. We demonstrate the development and performance of an integrated multimedia modeling system that uses machine learning (ML) to assess and predict monthly total P (TP) and dissolved reactive P (DRP) loads. Meteorological variables from the Weather Research and Forecasting (WRF) Model, hydrologic variables from the Variable Infiltration Capacity model, and agricultural management practice variables from the Environmental Policy Integrated Climate agroecosystem model are utilized to train the ML models to predict P loads. Our study presents a new modeling methodology using as testbeds the Maumee, Sandusky, Portage, and Raisin watersheds, which discharge into Lake Erie and contribute to significant P loads to the lake. Two models were built, one for TP loads using 10 environmental variables and one for DRP loads using nine environmental variables. Both models ranked streamflow as the most important predictive variable. In comparison with observations, TP and DRP loads were predicted very well temporally and spatially. Modeling results of TP loads are within the ranges of those obtained from other studies and on some occasions more accurate. Modeling results of DRP loads exceed performance measures from other studies. We explore the ability of both ML-based models to further improve as more data become available over time. This integrated multimedia approach is recommended for studying other freshwater systems and water quality variables using available decadal data from physics-based model simulations.

Effect of metabotropic glutamate receptor 3 genotype on N-acetylaspartate levels and neurocognition in non-smoking, active alcoholics.

BACKGROUND: We studied the effects of single nucleotide polymorphisms (SNPs) in the metabotropic glutamate receptor 3 (GRM3) gene on brain N-acetylaspartate (NAA) concentrations and executive function (EF) skills in non-smoking, active alcoholics, and evaluated associations between these variables. METHODS: SNPs (rs6465084, rs1468412, and rs2299225) in GRM3 were genotyped in 49 male, non-smoking, alcohol-dependent patients and 45 healthy control subjects using ligase detection reactions. NAA/creatine (Cr) ratios in left prefrontal gray matter (GM) and white matter (WM), left parietal GM, left parietal WM, and cerebellar vermis regions were measured by Proton 1 H Magnetic resonance spectroscopy (MRS). EF was measured by the Wisconsin Card Sorting Test (WCST). RESULTS: Compared to controls, alcoholics had lower NAA/Cr ratios in prefrontal GM and WM regions and performed more poorly on all EF tests (P < 0.001). Alcoholics with the A/A genotype for SNP rs6465084 had lower NAA/Cr ratios in prefrontal GM and WM regions and had poorer EF skills than alcoholics who were G-carriers for this SNP (P < 0.01). Non-alcoholics with the A/A genotype for rs6465084 also had lower NAA/Cr levels in prefrontal GM and made more random errors in the WCST than G-carriers (P < 0.01). The A/A genotype group for SNP rs6465084 was significantly different from the G carriers for the variables of NAA/Cr ratios and WCST scores in both alcoholics and controls (P < 0.05). Alcoholics who were T-carriers for rs1468412 had lower NAA/Cr ratios in prefrontal GM and showed poorer EF skills (P < 0.05). No effects of rs2299225 genotype on NAA/Cr or executive skills were observed. NAA/Cr in left prefrontal regions correlated with certain parameters of EF testing in both alcoholics and controls (P < 0.05), but the significance of this correlation among alcoholics disappeared after adjustment for the effects of genotype. CONCLUSIONS: Our results provide evidence that glutamate system dysfunction may play a role in the prefrontal functional abnormalities seen in alcohol dependence. It is possible that certain GRM3 SNP genotypes (the A/A genotype of rs6465084 and the T allele of rs1468412) may further lower NAA/Cr levels and EF skills in addition to the effect of alcohol.

3D Interfacial and Spatiotemporal Regulation of Human Neuroepithelial Organoids.

Neuroepithelial (NE) organoids with dorsal-ventral patterning provide a useful three-dimensional (3D) in vitro model to interrogate neural tube formation during early development of the central nervous system. Understanding the fundamental processes behind the cellular self-organization in NE organoids holds the key to the engineering of organoids with higher, more in vivo-like complexity. However, little is known about the cellular regulation driving the NE development, especially in the presence of interfacial cues from the microenvironment. Here a simple 3D culture system that allows generation and manipulation of NE organoids from human-induced pluripotent stem cells (hiPSCs), displaying developmental phases of hiPSC differentiation and self-aggregation, first into NE cysts with lumen structure and then toward NE organoids with floor-plate patterning, is established. Longitudinal inhibition reveals distinct and dynamic roles of actomyosin contractility and yes-associated protein (YAP) signaling in governing these phases. By growing NE organoids on culture chips containing anisotropic surfaces or confining microniches, it is further demonstrated that interfacial cues can sensitively exert dimension-dependent influence on luminal cyst and organoid morphology, successful floor-plate patterning, as well as cytoskeletal regulation and YAP activity. This study therefore sheds new light on how organoid and tissue architecture can be steered through intracellular and extracellular means.

HDAC1-Mediated MicroRNA-124-5p Regulates NPY to Affect Learning and Memory Abilities in Rats with Depression.

Researches pivoting on histone deacetylases (HDACs) in depression have been excessively conducted, but not much on HDAC1. Therein, the present study is launched to disclose the mechanism of HDAC1/microRNA (miR)-124-5p/neuropeptide Y (NPY) axis in depression. Sprague Dawley rats were stimulated by chronic unpredictable mild stress to establish depression models. Depressed rats were injected with inhibited HDAC1 or suppressed miR-124-5p to explore their roles in body weight, learning and memory abilities, oxidative stress and inflammation in serum and neurotransmitter expression in hippocampal tissues. MiR-124-5p, HDAC1 and NPY expression in the hippocampus were tested. The interactions of miR-124-5p, HDAC1 and NPY expression were also confirmed. Higher miR-124-5p and HDAC1 and lower NPY expression levels were found in the hippocampus of depressed rats. Inhibited miR-124-5p or suppressed HDAC1 attenuated learning and memory abilities and increased body weight of depressed rats. Knockdown of miR-124-5p or inhibition of HDAC1 suppressed oxidative stress and inflammation and promoted neurotransmitter expression of depressed rats. HDAC1 mediated miR-124-5p to regulate NPY. Knockdown of NPY abolished the protective effects of inhibited miR-124-5p on depressed rats. Our study illustrates that suppression of either miR-124-5p or HDAC1 up-regulates NPY to improve memory and learning abilities in depressed mice, which may update the existed knowledge of depression and provide a novel reference for treatment of depression.

Association of Migraine with Its Comorbidities and Food Specific Immunoglobulin G Antibodies and Inflammatory Cytokines: Cross-Sectional Clinical Research.

PURPOSE: The relationship between food allergy caused by food specific IgG antibodies and migraine has received increased attention in recent years. Here, we aimed to evaluate the effects of food specific IgG antibodies on headache, gastrointestinal symptoms, anxiety, depression, sleep disorders, dermatosis, and serum inflammatory cytokines in migraine patients, and to quantitatively assess the effect of IgG levels on the severity of headache and its comorbidities. METHODS: Of 89 migraine patients, those who had one or more food specific IgG antibodies ≥50 U/mL were classified into the IgG positive group, which was then further divided into subgroups based on differing numbers of food allergens. All other subjects were classified into the IgG negative group. We compared the frequency and severity of migraine, anxiety, depression, sleep disorders, dermatosis, and inflammatory cytokines between groups. A regression model was performed to further assess the effect of overall positive IgG concentration and the mediation effect of inflammatory cytokines. RESULTS: Participants in the positive IgG group (n = 67) were more likely to have longer time elapsed since diagnosis, more frequent and severe migraine, a higher risk of developing anxiety and gastrointestinal symptoms, along with higher IL-6 and TNF-α. Subgroups with more food allergens generally had worse conditions as well. After adjusting for the inflammatory cytokines, the effect of IgG was reduced. CONCLUSION: Migraine patients with positive food specific IgG antibodies had worse migraine, anxiety, and gastrointestinal symptoms. Inflammatory cytokines partially mediate the causal pathway between food specific IgG antibodies, migraine, and migraine comorbidities.

Probiotics alleviate depressive behavior in chronic unpredictable mild stress rat models by remodeling intestinal flora.

OBJECTIVE: To explore the effects of probiotics on depressive behavior in a chronic unpredictable mild stress (CUMS) rat model by remodeling intestinal flora. METHODS: Twenty-four male SD rats aged 6-8 weeks were randomly divided into four groups: control group, depression group (CUMS), depression+paroxetine group (Paro) and depression+probiotics group (Pro). Sucrose preference, open field and forced swimming tests were used to assess depression-like behavior in rats. ELISA was used to detect the levels of adrenocorticotropic hormone (ACTH), and corticosterone, norepinephrine and 5-hydroxytryptamine in rat serum. Real-time PCR was used to determine the changes of Lactobacillus, Bifidobacterium, Enterococcus faecalis and Escherichia coli in rat cecum. RESULTS: Compared with the control group, CUMS led to significant decreases of body weight, total traveled distance, duration in central area, immobility time, norepinephrine and 5-hydroxytryptamine contents in hippocampal tissues, as well as Lactobacillus and Bifidobacterium in the cecum. It also resulted in marked increases of the contents of E. faecalis and E. coli in the cecum, ACTH and corticosterone contents in the serum of rats. Paroxetine and probiotic treatment each diminished or prevented these changes. CONCLUSION: By remodeling intestinal flora, probiotics can reduce the CUMS-induced depressive behavior of rats, increase the levels of norepinephrine and 5-hydroxytryptamine, and inhibit the expression of ACTH and corticosterone. Significantly, the effect of both paroxetine and probiotic on microorganisms is similar.

Some (Fish Might) Like It Hot: Habitat Quality and Fish Growth from Past to Future Climates.

Current expectation is that projected climate change may have adverse effects on fish habitats and survival. The analysis leading to these concerns is typically done at large scale with limited possibility to quantify the local biological response and compare with previous conditions. Our research investigated the effects of recorded climate conditions on Chinook salmon (Oncorhynchus tshawytscha) spawning and rearing habitats and growth responses to the local climate and compared those conditions to predicted responses to a climate change. The study site was a 7 km long reach of Bear Valley Creek, an important spawning stream for this US Endangered Species Act listed species, in the Pacific Northwest of United States. We used 2D numerical modeling supported by accurate, high-resolution survey data to calculate flow hydraulics at various discharges from base to bankfull flows. For past and future conditions, computed flow hydraulics were combined with habitat suitability indices (SI) to compute spawning and rearing habitat suitability. Information on habitat suitability along with fish density and stream water temperature informed a growth model to quantify the potential fish size, an index of survival rates and fitness. Our results indicate that yearly-averaged rearing habitat quality remains similar to historic, but the timing of high- and low-quality habitat periods shift within the calendar year. Future spawning habitat quality may be significantly reduced during the seasonal period to which Chinook have currently adapted their spawning behavior. The growth model indicates an increase in anticipated size of Chinook salmon for predicted future climate conditions due to water temperature increase. Consequently, future climate conditions may have a substantial negative impact on spawning and limited impact on rearing conditions due to flow reduction and thus quality and extent of available habitat. However, the expected warmer stream water temperatures may benefit rearing, because of increased fish size in these high elevation streams.

Multivalent Sgc8c-aptamer decorated polymer scaffolds for leukemia targeting.

T-cell acute lymphoblastic leukemia causes a disproportional amount of immature white blood cells in the patients' bone marrow. The significant undesired side effects associated with traditional chemotherapy treatment prompted us to study a more effective treatment strategy. We decorated polyisocyanopeptide scaffolds with the selective leukemia cell binding aptamer sgc8c and found that the polymers inhibit proliferation by G0/G1-phase arrest, serving as an opportunity for future therapeutic strategies.

Polyisocyanide Hydrogels as a Tunable Platform for Mammary Gland Organoid Formation.

In the last decade, organoid technology has developed as a primary research tool in basic biological and clinical research. The reliance on poorly defined animal-derived extracellular matrix, however, severely limits its application in regenerative and translational medicine. Here, a well-defined, synthetic biomimetic matrix based on polyisocyanide (PIC) hydrogels that support efficient and reproducible formation of mammary gland organoids (MGOs) in vitro is presented. Only decorated with the adhesive peptide RGD for cell binding, PIC hydrogels allow MGO formation from mammary fragments or from purified single mammary epithelial cells. The cystic organoids maintain their capacity to branch for over two months, which is a fundamental and complex feature during mammary gland development. It is found that small variations in the 3D matrix give rise to large changes in the MGO: the ratio of the main cell types in the MGO is controlled by the cell-gel interactions via the cell binding peptide density, whereas gel stiffness controls colony formation efficiency, which is indicative of the progenitor density. Simple hydrogel modifications will allow for future introduction and customization of new biophysical and biochemical parameters, making the PIC platform an ideal matrix for in depth studies into organ development and for application in disease models.