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Studies on the stem cell niche and the efficacy of cancer therapeutics require complex multicellular structures and interactions between different cell types and extracellular matrix (ECM) in three dimensional (3D) space. We have engineered a 3D in vitro model of mammary gland that encompasses a defined, porous collagen/hyaluronic acid (HA) scaffold forming a physiologically relevant foundation for epithelial and adipocyte co-culture. Polarized ductal and acinar structures form within this scaffold recapitulating normal tissue morphology in the absence of reconstituted basement membrane (rBM) hydrogel. Furthermore, organoid developmental outcome can be controlled by the ratio of collagen to HA, with a higher HA concentration favouring acinar morphological development. Importantly, this culture system recapitulates the stem cell niche as primary mammary stem cells form complex organoids, emphasising the utility of this approach for developmental and tumorigenic studies using genetically altered animals or human biopsy material, and for screening cancer therapeutics for personalised medicine.

Measured variability of product within Cell and Gene Therapy (CGT) manufacturing arises from numerous sources across pre-analytical to post-analytical phases of testing. Operators are a function of the manufacturing process and are an important source of variability as a result of personal differences impacted by numerous factors. This research uses measurement uncertainty in comparison to Coefficient of Variation to quantify variation of participants when they complete Flow Cytometry data analysis through a 5-step gating sequence. Two study stages captured participants applying gates using their own judgement, and then following a diagrammatical protocol, respectively. Measurement uncertainty was quantified for each participant (and analysis phase) by following Guide to the Expression of Uncertainty in Measurement protocols, combining their standard deviations in quadrature from each gating step in the respective protocols. When participants followed a diagrammatical protocol, variation between participants reduced by 57%, increasing confidence in a more uniform reported cell count percentage. Measurement uncertainty provided greater resolution to the analysis processes, identifying that most variability contributed in the Flow Cytometry gating process is from the very first gate, where isolating target cells from dead or dying cells is required. This work has demonstrated the potential for greater usage of measurement uncertainty within CGT manufacturing scenarios, due to the resolution it provides for root cause analysis and continuous improvement.

Flow cytometry is widely used within the manufacturing of cell and gene therapies to measure and characterise cells. Conventional manual data analysis relies heavily on operator judgement, presenting a major source of variation that can adversely impact the quality and predictive potential of therapies given to patients. Computational tools have the capacity to minimise operator variation and bias in flow cytometry data analysis; however, in many cases, confidence in these technologies has yet to be fully established mirrored by aspects of regulatory concern. Here, we employed synthetic flow cytometry datasets containing controlled population characteristics of separation, and normal/skew distributions to investigate the accuracy and reproducibility of six cell population identification tools, each of which implement different unsupervised clustering algorithms: Flock2, flowMeans, FlowSOM, PhenoGraph, SPADE3 and SWIFT (density-based, k-means, self-organising map, k-nearest neighbour, deterministic k-means, and model-based clustering, respectively). We found that outputs from software analysing the same reference synthetic dataset vary considerably and accuracy deteriorates as the cluster separation index falls below zero. Consequently, as clusters begin to merge, the flowMeans and Flock2 software platforms struggle to identify target clusters more than other platforms. Moreover, the presence of skewed cell populations resulted in poor performance from SWIFT, though FlowSOM, PhenoGraph and SPADE3 were relatively unaffected in comparison. These findings illustrate how novel flow cytometry synthetic datasets can be utilised to validate a range of automated cell identification methods, leading to enhanced confidence in the data quality of automated cell characterisations and enumerations.

Viral vectors are agents enabling gene transfer and genome editing and have widespread utility across the healthcare and biotechnology sectors. In January 2023, the International Bureau for Weights and Measures’ Consultative Committee for Amount of Substance (CCQM) held a workshop on Metrology for Viral systems as molecular tools. The workshop brought together international leaders from across regulatory, industry, government science, and metrology sectors to better understand key challenges for the community: Exploring current limitations in the measurement of virus-derived, virus-based, and virus-like systems in terms of quantification and characterisation; surveying the state-of-the-art in analytical methods and reference material provision for these entities; and initiating a dialog for the strategic development and implementation of suitable standardisation approaches for this sector. This article presents the workshop background and rationale, presentation summaries, conclusions, and recommendations.

Breast cancers are highly heterogeneous and their metastatic potential and response to therapeutic drugs is difficult to predict. A tool that could accurately gauge tumour invasiveness and drug response would provide a valuable addition to the oncologist’s arsenal. We have developed a 3-dimensional (3D) culture model that recapitulates the stromal environment of breast cancers by generating anisotropic (directional) collagen scaffolds seeded with adipocytes and culturing tumour fragments therein. Analysis of tumour cell invasion in the presence of various therapeutic drugs, by immunofluorescence microscopy coupled with an optical clearing technique, demonstrated the utility of this approach in determining both the rate and capacity of tumour cells to migrate through the stroma while shedding light also on the mode of migration. Furthermore, the response of different murine mammary tumour types to chemotherapeutic drugs could be readily quantified.

More than half a century after the advent of the nuclear age, is the world approaching a tipping point that will unleash an epidemic of nuclear proliferation? Today many of the building blocks of a nuclear arsenal-scientific and engineering expertise, precision machine tools, software, design information-are more readily available than ever before. The nuclear pretensions of so-called rogue states and terrorist organizations are much discussed. But how firm is the resolve of those countries that historically have chosen to forswear nuclear weapons? A combination of changes in the international environment could set off a domino effect, with countries scrambling to develop nuclear weapons so as not to be left behind-or to develop nuclear \"hedge\" capacities that would allow them to build nuclear arsenals relatively quickly, if necessary. The Nuclear Tipping Point examines the factors, both domestic and transnational, that shape nuclear policy. The authors, distinguished scholars and foreign policy practitioners with extensive government experience, develop a framework for understanding why certain countries may originally have decided to renounce nuclear weapons-and pinpoint some more recent country-specific factors that could give them cause to reconsider. Case studies of eight long-term stalwarts of the nonproliferation regime-Egypt, Germany, Japan, Saudi Arabia, South Korea, Syria, Turkey, and Taiwan-flesh out this framework and show how even these countries might be pushed over the edge of a nuclear tipping point. The authors offer prescriptions that would both prevent such countries from reconsidering their nuclear option and avert proliferation by others. The stakes are enormous and success is far from assured. To keep the tipping point beyond reach, the authors argue, the international community will have to act with unity, imagination, and strength, and Washington's leadership will be essential. Contributors include Leon Feurth, George Washington University; Ellen Laipson, Stimson Center; Thomas W. Lippman, Middle East Institute; Jenifer Mackby, Center for Strategic and International Studies; Derek J. Mitchell, Center for Strategic and International Studies; Jonathan D. Pollack, U.S. Naval War College; Walter B. Slocombe, Caplin and Drysdale; and Tsuyoshi Sunohara, Center for Strategic and International Studies.

Abstract Glucagon-like peptide-1 (GLP-1) is produced in gut endocrine cells and in the brain, and acts through hormonal and neural pathways to regulate islet function, satiety, and gut motility, supporting development of GLP-1 receptor (GLP-1R) agonists for the treatment of diabetes and obesity. Classic notions of GLP-1 acting as a meal-stimulated hormone from the distal gut are challenged by data supporting production of GLP-1 in the endocrine pancreas, and by the importance of brain-derived GLP-1 in the control of neural activity. Moreover, attribution of direct vs indirect actions of GLP-1 is difficult, as many tissue and cellular targets of GLP-1 action do not exhibit robust or detectable GLP-1R expression. Furthermore, reliable detection of the GLP-1R is technically challenging, highly method dependent, and subject to misinterpretation. Here we revisit the actions of GLP-1, scrutinizing key concepts supporting gut vs extra-intestinal GLP-1 synthesis and secretion. We discuss new insights refining cellular localization of GLP-1R expression and integrate recent data to refine our understanding of how and where GLP-1 acts to control inflammation, cardiovascular function, islet hormone secretion, gastric emptying, appetite, and body weight. These findings update our knowledge of cell types and mechanisms linking endogenous vs pharmacological GLP-1 action to activation of the canonical GLP-1R, and the control of metabolic activity in multiple organs. Graphical Abstract Graphical Abstract

Inflammation alters host physiology to promote cancer, as seen in colitis-associated colorectal cancer (CRC). Here, we identify the intestinal microbiota as a target of inflammation that affects the progression of CRC. High-throughput sequencing revealed that inflammation modifies gut microbial composition in colitis-susceptible interleukin-10—deficient (Il10⁻ / ⁻) mice. Monocolonization with the commensal Escherichia coli NC101 promoted invasive carcinoma in azoxymethane (AOM)—treated Il10⁻ / ⁻ mice. Deletion of the polyketide synthase (pks) genotoxic island from E. coli NC101 decreased tumor multiplicity and invasion in AOM/Il10⁻ / ⁻ mice, without altering intestinal inflammation. Mucosa-associated pks⁺ E. coli were found in a significantly high percentage of inflammatory bowel disease and CRC patients. This suggests that in mice, colitis can promote tumorigenesis by altering microbial composition and inducing the expansion of microorganisms with genotoxic capabilities.

Therapies to reduce liver fibrosis and stimulate organ regeneration are urgently needed. We conducted a first-in-human, phase 1 dose-escalation trial of autologous macrophage therapy in nine adults with cirrhosis and a Model for End-Stage Liver Disease (MELD) score of 10–16 (ISRCTN 10368050). Groups of three participants received a single peripheral infusion of 10 7 , 10 8 or up to 10 9 cells. Leukapheresis and macrophage infusion were well tolerated with no transfusion reactions, dose-limiting toxicities or macrophage activation syndrome. All participants were alive and transplant-free at one year, with only one clinical event recorded, the occurrence of minimal ascites. The primary outcomes of safety and feasibility were met. This study informs and provides a rationale for efficacy studies in cirrhosis and other fibrotic diseases. A first-in-human, phase 1 dose-escalation trial demonstrates the safety and feasibility of autologous macrophage therapy in adults with liver cirrhosis.

Tirzepatide (LY3298176) is a dual GIP and GLP-1 receptor agonist under development for the treatment of type 2 diabetes mellitus (T2DM), obesity, and nonalcoholic steatohepatitis. Early phase trials in T2DM indicate that tirzepatide improves clinical outcomes beyond those achieved by a selective GLP-1 receptor agonist. Therefore, we hypothesized that the integrated potency and signaling properties of tirzepatide provide a unique pharmacological profile tailored for improving broad metabolic control. Here, we establish methodology for calculating occupancy of each receptor for clinically efficacious doses of the drug. This analysis reveals a greater degree of engagement of tirzepatide for the GIP receptor than the GLP-1 receptor, corroborating an imbalanced mechanism of action. Pharmacologically, signaling studies demonstrate that tirzepatide mimics the actions of native GIP at the GIP receptor but shows bias at the GLP-1 receptor to favor cAMP generation over β-arrestin recruitment, coincident with a weaker ability to drive GLP-1 receptor internalization compared with GLP-1. Experiments in primary islets reveal β-arrestin1 limits the insulin response to GLP-1, but not GIP or tirzepatide, suggesting that the biased agonism of tirzepatide enhances insulin secretion. Imbalance toward GIP receptor, combined with distinct signaling properties at the GLP-1 receptor, together may account for the promising efficacy of this investigational agent.