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A digital twin is a computer-based “virtual” representation of a complex system, updated using data from the “real” twin. Digital twins are established in product manufacturing, aviation, and infrastructure and are attracting significant attention in medicine. In medicine, digital twins hold great promise to improve prevention of cardiovascular diseases and enable personalised health care through a range of Internet of Things (IoT) devices which collect patient data in real-time. However, the promise of such new technology is often met with many technical, scientific, social, and ethical challenges that need to be overcome—if these challenges are not met, the technology is therefore less likely on balance to be adopted by stakeholders. The purpose of this work is to identify the facilitators and barriers to the implementation of digital twins in cardiovascular medicine. Using, the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework, we conducted a document analysis of policy reports, industry websites, online magazines, and academic publications on digital twins in cardiovascular medicine, identifying potential facilitators and barriers to adoption. Our results show key facilitating factors for implementation: preventing cardiovascular disease, in silico simulation and experimentation, and personalised care. Key barriers to implementation included: establishing real-time data exchange, perceived specialist skills required, high demand for patient data, and ethical risks related to privacy and surveillance. Furthermore, the lack of empirical research on the attributes of digital twins by different research groups, the characteristics and behaviour of adopters, and the nature and extent of social, regulatory, economic, and political contexts in the planning and development process of these technologies is perceived as a major hindering factor to future implementation.

The Muon g−2 Experiment at Fermi National Accelerator Laboratory was designed to measure the anomalous magnetic moment of the muon, a µ, with a precision of 140 parts-per-billion; a four-fold improvement over the former BNL measurement. The Fermilab experiment was motivated by the about 3.5 standard deviation between the experiment and the Standard Model calculation of a µ which could be a hint of new physics. The experiment at Fermilab relies on the well-established storage ring technique using magic momentum muons but employs new detector systems and a higher rate of muons per injection cycle to achieve the significant improvement in precision. A first result from the Run-1 data taking period has achieved an uncertainty of 0.46 parts-per-million and confirmed the BNL discrepancy, further increasing the tension with the Standard Model to 4.2 σ. The experimental technique, key aspects of the measurement, and the data analysis of Run-1 will be summarized.

The global outbreak of COVID-19 has brought to light the profound impact that large-scale disease outbreaks can have on healthcare systems and the dedicated professionals who serve within them. It becomes increasingly important to explore strategies for retaining nurses and physicians within hospital settings during such challenging times. This paper aims to investigate the determinants of retention among nurses and physicians during the COVID-19 pandemic. A systematic review of other potential determinants impacting retention rates during the pandemic was carried out. Secondly, a meta-analysis on the prevalence of intention to leave for nurses and physicians during the COVID-19 pandemic. A comprehensive search was performed within four electronic databases on March 17 2023. Fifty-five papers were included in the systematic review, whereas thirty-three papers fulfilled the eligibility criteria for the meta-analysis. The systematic review resulted in six themes of determinants impacting intention to leave: personal characteristics, job demands, employment services, working conditions, work relationships, and organisational culture. The main determinants impacting the intention to leave are the fear of COVID-19, age, experience, burnout symptoms and support. Meta-analysis showed a prevalence of intent to leave the current job of 38% for nurses (95% CI: 26%-51%) and 29% for physicians (95% CI: 21%-39%), whereas intention to leave the profession for nurses 28% (95% CI: 21%-34%) and 24% for physicians (95% CI: 23%-25%). The findings of this paper showed the critical need for hospital managers to address the concerning increase in nurses' and physicians' intentions to leave during the COVID-19 pandemic. This intention to leave is affected by a complex conjunction of multiple determinants, including the fear of COVID-19 and the confidence in and availability of personal protective equipment. Moreover, individual factors like age, experience, burnout symptoms, and support are maintained in this review. Understanding the influence of determinants on retention during the COVID-19 pandemic offers an opportunity to formulate prospective strategies for retaining nurses and physicians within hospital settings.

While inhibitors of BCL-2 family proteins (BH3 mimetics) have shown promise as anti-cancer agents, the various dependencies or co-dependencies of diverse cancers on BCL-2 genes remain poorly understood. Here we develop a drug screening approach to define the sensitivity of cancer cells from ten tissue types to all possible combinations of selective BCL-2, BCL-X L , and MCL-1 inhibitors and discover that most cell lines depend on at least one combination for survival. We demonstrate that expression levels of BCL-2 genes predict single mimetic sensitivity, whereas EMT status predicts synergistic dependence on BCL-X L +MCL-1. Lastly, we use a CRISPR/Cas9 screen to discover that BFL-1 and BCL-w promote resistance to all tested combinations of BCL-2, BCL-X L , and MCL-1 inhibitors. Together, these results provide a roadmap for rationally targeting BCL-2 family dependencies in diverse human cancers and motivate the development of selective BFL-1 and BCL-w inhibitors to overcome intrinsic resistance to BH3 mimetics. Dependency of diverse cancers on specific BCL-2 family members and their combinations is unknown. Here they perform drug screening and find most cell lines to be dependent on at least one combination of BCL-2 family members, and using a CRISPR screen find BCL-w and BFL-1 to mediate resistance to BH3 mimetics

Immunosurveillance of cancer requires the presentation of peptide antigens on major histocompatibility complex class I (MHC-I) molecules 1 – 5 . Current approaches to profiling of MHC-I-associated peptides, collectively known as the immunopeptidome, are limited to in vitro investigation or bulk tumour lysates, which limits our understanding of cancer-specific patterns of antigen presentation in vivo 6 . To overcome these limitations, we engineered an inducible affinity tag into the mouse MHC-I gene ( H2-K1 ) and targeted this allele to the Kras LSL-G12D/+ Trp53 fl/fl mouse model (KP/K b Strep) 7 . This approach enabled us to precisely isolate MHC-I peptides from autochthonous pancreatic ductal adenocarcinoma and from lung adenocarcinoma (LUAD) in vivo. In addition, we profiled the LUAD immunopeptidome from the alveolar type 2 cell of origin up to late-stage disease. Differential peptide presentation in LUAD was not predictable by mRNA expression or translation efficiency and is probably driven by post-translational mechanisms. Vaccination with peptides presented by LUAD in vivo induced CD8 + T cell responses in naive mice and tumour-bearing mice. Many peptides specific to LUAD, including immunogenic peptides, exhibited minimal expression of the cognate mRNA, which prompts the reconsideration of antigen prediction pipelines that triage peptides according to transcript abundance 8 . Beyond cancer, the K b Strep allele is compatible with other Cre-driver lines to explore antigen presentation in vivo in the pursuit of understanding basic immunology, infectious disease and autoimmunity. A newly developed genetically engineered mouse model enables the analysis of specific antigen presentation in vivo, providing insights into the tumour immunopeptidome and cancer progression.

Activation of CD4+ T cells results in rapid proliferation and differentiation into effector and regulatory subsets. CD4+ effector T cell (Teff) (Th1 and Th17) and Treg subsets are metabolically distinct, yet the specific metabolic differences that modify T cell populations are uncertain. Here, we evaluated CD4+ T cell populations in murine models and determined that inflammatory Teffs maintain high expression of glycolytic genes and rely on high glycolytic rates, while Tregs are oxidative and require mitochondrial electron transport to proliferate, differentiate, and survive. Metabolic profiling revealed that pyruvate dehydrogenase (PDH) is a key bifurcation point between T cell glycolytic and oxidative metabolism. PDH function is inhibited by PDH kinases (PDHKs). PDHK1 was expressed in Th17 cells, but not Th1 cells, and at low levels in Tregs, and inhibition or knockdown of PDHK1 selectively suppressed Th17 cells and increased Tregs. This alteration in the CD4+ T cell populations was mediated in part through ROS, as N-acetyl cysteine (NAC) treatment restored Th17 cell generation. Moreover, inhibition of PDHK1 modulated immunity and protected animals against experimental autoimmune encephalomyelitis, decreasing Th17 cells and increasing Tregs. Together, these data show that CD4+ subsets utilize and require distinct metabolic programs that can be targeted to control specific T cell populations in autoimmune and inflammatory diseases.

A dual-view light sheet microscope allows high-speed imaging with an isotropic spatial resolution Optimal four-dimensional imaging requires high spatial resolution in all dimensions, high speed and minimal photobleaching and damage. We developed a dual-view, plane illumination microscope with improved spatiotemporal resolution by switching illumination and detection between two perpendicular objectives in an alternating duty cycle. Computationally fusing the resulting volumetric views provides an isotropic resolution of 330 nm. As the sample is stationary and only two views are required, we achieve an imaging speed of 200 images/s (i.e., 0.5 s for a 50-plane volume). Unlike spinning-disk confocal or Bessel beam methods, which illuminate the sample outside the focal plane, we maintain high spatiotemporal resolution over hundreds of volumes with negligible photobleaching. To illustrate the ability of our method to study biological systems that require high-speed volumetric visualization and/or low photobleaching, we describe microtubule tracking in live cells, nuclear imaging over 14 h during nematode embryogenesis and imaging of neural wiring during Caenorhabditis elegans brain development over 5 h.

We report superresolution optical sectioning using a multiangle total internal reflection fluorescence (TIRF) microscope. TIRF images were constructed from several layers within a normal TIRF excitation zone by sequentially imaging and photobleaching the fluorescent molecules. The depth of the evanescent wave at different layers was altered by tuning the excitation light incident angle. The angle was tuned from the highest (the smallest TIRF depth) toward the critical angle (the largest TIRF depth) to preferentially photobleach fluorescence from the lower layers and allow straightforward observation of deeper structures without masking by the brighter signals closer to the coverglass. Reconstruction of the TIRF images enabled 3D imaging of biological samples with 20-nm axial resolution. Two-color imaging of epidermal growth factor (EGF) ligand and clathrin revealed the dynamics of EGF-activated clathrin-mediated endocytosis during internalization. Furthermore, Bayesian analysis of images collected during the photobleaching step of each plane enabled lateral superresolution (<100 nm) within each of the sections.

Sporulation in the bacterium Bacillus subtilis is a developmental program in which a progenitor cell differentiates into two different cell types, the smaller of which eventually becomes a dormant cell called a spore. The process begins with an asymmetric cell division event, followed by the activation of a transcription factor, σF, specifically in the smaller cell. Here, we show that the structural protein DivIVA localizes to the polar septum during sporulation and is required for asymmetric division and the compartment-specific activation of σF. Both events are known to require a protein called SpoIIE, which also localizes to the polar septum. We show that DivIVA copurifies with SpoIIE and that DivIVA may anchor SpoIIE briefly to the assembling polar septum before SpoIIE is subsequently released into the forespore membrane and recaptured at the polar septum. Finally, using super-resolution microscopy, we demonstrate that DivIVA and SpoIIE ultimately display a biased localization on the side of the polar septum that faces the smaller compartment in which σF is activated.