Identification of a Master Regulator of Differentiation in Toxoplasma.

Toxoplasma gondii chronically infects a quarter of the world's population, and its recrudescence can cause life-threatening disease in immunocompromised individuals and recurrent ocular lesions in the immunocompetent. Acute-stage tachyzoites differentiate into chronic-stage bradyzoites, which form intracellular cysts resistant to immune clearance and existing therapies. The molecular basis of this differentiation is unknown, despite being efficiently triggered by stresses in culture. Through Cas9-mediated screening and single-cell profiling, we identify a Myb-like transcription factor (BFD1) necessary for differentiation in cell culture and in mice. BFD1 accumulates during stress and its synthetic expression is sufficient to drive differentiation. Consistent with its function as a transcription factor, BFD1 binds the promoters of many stage-specific genes and represents a counterpoint to the ApiAP2 factors that dominate our current view of parasite gene regulation. BFD1 provides a genetic switch to study and control Toxoplasma differentiation and will inform prevention and treatment of chronic infections.

The Master Observational Trial: A New Class of Master Protocol to Advance Precision Medicine.

This commentary introduces a new clinical trial construct, the Master Observational Trial (MOT), which hybridizes the power of molecularly based master interventional protocols with the breadth of real-world data. The MOT provides a clinical venue to allow molecular medicine to rapidly advance, answers questions that traditional interventional trials generally do not address, and seamlessly integrates with interventional trials in both diagnostic and therapeutic arenas. The result is a more comprehensive data collection ecosystem in precision medicine.

An overview of precision oncology basket and umbrella trials for clinicians.

With advancements in biomarkers and momentum in precision medicine, biomarker-guided trials such as basket trials and umbrella trials have been developed under the master protocol framework. A master protocol refers to a single, overarching design developed to evaluate multiple hypotheses with the general goal of improving the efficiency of trial evaluation. One type of master protocol is the basket trial, in which a targeted therapy is evaluated for multiple diseases that share common molecular alterations or risk factors that may help predict whether the patients will respond to the given therapy. Another variant of a master protocol is the umbrella trial, in which multiple targeted therapies are evaluated for a single disease that is stratified into multiple subgroups based on different molecular or other predictive risk factors. Both designs follow the core principle of precision medicine-to tailor intervention strategies based on the patient's risk factor(s) that can help predict whether they will respond to a specific treatment. There have been increasing numbers of basket and umbrella trials, but they are still poorly understood. This article reviews common characteristics of basket and umbrella trials, key trials and recent US Food and Drug Administration approvals for precision oncology, and important considerations for clinical readers when critically evaluating future publications on basket trials and umbrella trials and for researchers when designing these clinical trials.

Canalizing kernel for cell fate determination.

The tendency for cell fate to be robust to most perturbations, yet sensitive to certain perturbations raises intriguing questions about the existence of a key path within the underlying molecular network that critically determines distinct cell fates. Reprogramming and trans-differentiation clearly show examples of cell fate change by regulating only a few or even a single molecular switch. However, it is still unknown how to identify such a switch, called a master regulator, and how cell fate is determined by its regulation. Here, we present CAESAR, a computational framework that can systematically identify master regulators and unravel the resulting canalizing kernel, a key substructure of interconnected feedbacks that is critical for cell fate determination. We demonstrate that CAESAR can successfully predict reprogramming factors for de-differentiation into mouse embryonic stem cells and trans-differentiation of hematopoietic stem cells, while unveiling the underlying essential mechanism through the canalizing kernel. CAESAR provides a system-level understanding of how complex molecular networks determine cell fates.

A variegated model of transcription factor function in the immune system.

Specific combinations of transcription factors (TFs) control the gene expression programs that underlie specialized immune responses. Previous models of TF function in immunocytes had restricted each TF to a single functional categorization [e.g., lineage-defining (LDTFs) vs. signal-dependent TFs (SDTFs)] within one cell type. Synthesizing recent results, we instead propose a variegated model of immunological TF function, whereby many TFs have flexible and different roles across distinct cell states, contributing to cell phenotypic diversity. We discuss evidence in support of this variegated model, describe contextual inputs that enable TF diversification, and look to the future to imagine warranted experimental and computational tools to build quantitative and predictive models of immunocyte gene regulatory networks.

Building insightful, memory-enriched models to capture long-time biochemical processes from short-time simulations.

The ability to predict and understand complex molecular motions occurring over diverse timescales ranging from picoseconds to seconds and even hours in biological systems remains one of the largest challenges to chemical theory. Markov state models (MSMs), which provide a memoryless description of the transitions between different states of a biochemical system, have provided numerous important physically transparent insights into biological function. However, constructing these models often necessitates performing extremely long molecular simulations to converge the rates. Here, we show that by incorporating memory via the time-convolutionless generalized master equation (TCL-GME) one can build a theoretically transparent and physically intuitive memory-enriched model of biochemical processes with up to a three order of magnitude reduction in the simulation data required while also providing a higher temporal resolution. We derive the conditions under which the TCL-GME provides a more efficient means to capture slow dynamics than MSMs and rigorously prove when the two provide equally valid and efficient descriptions of the slow configurational dynamics. We further introduce a simple averaging procedure that enables our TCL-GME approach to quickly converge and accurately predict long-time dynamics even when parameterized with noisy reference data arising from short trajectories. We illustrate the advantages of the TCL-GME using alanine dipeptide, the human argonaute complex, and FiP35 WW domain.

Identifying a missing lineage driver in a subset of lung neuroendocrine tumors.

Tumor heterogeneity of a primary histologic cancer type has major implications for cancer research and therapeutics. An important and understudied aspect of this heterogeneity is the role of transcription factors that serve as "lineage oncogenes" in a tumor type. A demonstration that different subgroups have distinct dependencies on lineage-specific transcription factors is highlighted in a relatively homogenous cancer type: the pulmonary neuroendocrine cancer small cell lung carcinoma (SCLC). Identification of these factors is providing new insights into the origin of the heterogeneity and subtype-specific vulnerabilities in SCLC and provides a template for studying heterogeneity in other cancer types.

POU2F3 is a master regulator of a tuft cell-like variant of small cell lung cancer.

Small cell lung cancer (SCLC) is widely considered to be a tumor of pulmonary neuroendocrine cells; however, a variant form of this disease has been described that lacks neuroendocrine features. Here, we applied domain-focused CRISPR screening to human cancer cell lines to identify the transcription factor (TF) POU2F3 (POU class 2 homeobox 3; also known as SKN-1a/OCT-11) as a powerful dependency in a subset of SCLC lines. An analysis of human SCLC specimens revealed that POU2F3 is expressed exclusively in variant SCLC tumors that lack expression of neuroendocrine markers and instead express markers of a chemosensory lineage known as tuft cells. Using chromatin- and RNA-profiling experiments, we provide evidence that POU2F3 is a master regulator of tuft cell identity in a variant form of SCLC. Moreover, we show that most SCLC tumors can be classified into one of three lineages based on the expression of POU2F3, ASCL1, or NEUROD1. Our CRISPR screens exposed other unique dependencies in POU2F3-expressing SCLC lines, including the lineage TFs SOX9 and ASCL2 and the receptor tyrosine kinase IGF1R (insulin-like growth factor 1 receptor). These data reveal POU2F3 as a cell identity determinant and a dependency in a tuft cell-like variant of SCLC, which may reflect a previously unrecognized cell of origin or a trans-differentiation event in this disease.

Experimental validation and characterization of putative targets of Escargot and STAT, two master regulators of the intestinal stem cells in Drosophila melanogaster.

Many organs contain adult stem cells (ASCs) to replace cells due to damage, disease, or normal tissue turnover. ASCs can divide asymmetrically, giving rise to a new copy of themselves (self-renewal) and a sister that commits to a specific cell type (differentiation). Decades of research have led to the identification of pleiotropic genes whose loss or gain of function affect diverse aspects of normal ASC biology. Genome-wide screens of these so-called genetic "master regulator" (MR) genes, have pointed to hundreds of putative targets that could serve as their downstream effectors. Here, we experimentally validate and characterize the regulation of several putative targets of Escargot (Esg) and the Signal Transducer and Activator of Transcription (Stat92E, a.k.a. STAT), two known MRs in Drosophila intestinal stem cells (ISCs). Our results indicate that regardless of bioinformatic predictions, most experimentally validated targets show a profile of gene expression that is consistent with co-regulation by both Esg and STAT, fitting a rather limited set of co-regulatory modalities. A bioinformatic analysis of proximal regulatory sequences in specific subsets of co-regulated targets identified additional transcription factors that might cooperate with Esg and STAT in modulating their transcription. Lastly, in vivo manipulations of validated targets rarely phenocopied the effects of manipulating Esg and STAT, suggesting the existence of complex genetic interactions among downstream targets of these two MR genes during ISC homeostasis.

Master graph: an essential integrated assembly model for the plant mitogenome based on a graph-based framework.

Unlike the typical single circular structure of most animal mitochondrial genomes (mitogenome), the drastic structural variation of plant mitogenomes is a result of a mixture of molecules of various sizes and structures. Obtaining the full panoramic plant mitogenome is still considered a roadblock in evolutionary biology. In this study, we developed a graph-based sequence assembly toolkit (GSAT) to construct the pan-structural landscape of plant mitogenome with high-quality mitochondrial master graphs (MMGs) for model species including rice (Oryza sativa) and thale cress (Arabidopsis thaliana). The rice and thale cress MMGs have total lengths of 346 562 and 358 041 bp, including 9 and 6 contigs and 12 and 8 links, respectively, and could be further divided into 6 and 3 minimum master circles and 4 and 2 minimum secondary circles separately. The nuclear mitochondrial DNA segments (NUMTs) in thale cress strongly affected the frequency evaluation of the homologous structures in the mitogenome, while the effects of NUMTs in rice were relatively weak. The mitochondrial plastid DNA segments (MTPTs) in both species had no effects on the assessment of the MMGs. All potential recombinant structures were evaluated, and the findings revealed that all, except for nuclear-homologous structures, MMG structures are present at a much higher frequency than non-MMG structures are. Investigations of potential circular and linear molecules further supported multiple dominant structures in the mitogenomes and could be completely summarized in the MMG. Our study provided an efficient and accurate model for assembling and applying graph-based plant mitogenomes to assess their pan-structural variations.

Using single-cell models to predict the functionality of synthetic circuits at the population scale.

SignificanceAt the single-cell level, biochemical processes are inherently stochastic. For many natural systems, the resulting cell-to-cell variability is exploited by microbial populations. In synthetic biology, however, the interplay of cell-to-cell variability and population processes such as selection or growth often leads to circuits not functioning as predicted by simple models. Here we show how multiscale stochastic kinetic models that simultaneously track single-cell and population processes can be obtained based on an augmentation of the chemical master equation. These models enable us to quantitatively predict complex population dynamics of a yeast optogenetic differentiation system from a specification of the circuit's components and to demonstrate how cell-to-cell variability can be exploited to purposefully create unintuitive circuit functionality.

Dephasing Dynamics Accessed by High Harmonic Generation: Determination of Electron-Hole Decoherence of Dirac Fermions.

We reveal the critical effect of ultrashort dephasing on the polarization of high harmonic generation in Dirac fermions. As the elliptically polarized laser pulse falls in or slightly beyond the multiphoton regime, the elliptically polarized high harmonic generation is produced and exhibits a characteristic polarimetry of the polarization ellipse, which is found to depend on the decoherence time T2. T2 could then be determined to be a few femtoseconds directly from the experimentally observed polarimetry of high harmonics. This shows a sharp contrast with the semimetal regime of higher pump intensity, where the polarimetry is irrelevant to T2. An access to the dephasing dynamics would extend the prospect of high harmonic generation into the metrology of a femtosecond dynamic process in the coherent quantum control.

Bayesian sample size determination in basket trials borrowing information between subsets.

Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach to sample size determination in basket trials that permit borrowing of information between commensurate subsets. Specifically, we consider a randomized basket trial design where patients are randomly assigned to the new treatment or control within each trial subset ("subtrial" for short). Closed-form sample size formulae are derived to ensure that each subtrial has a specified chance of correctly deciding whether the new treatment is superior to or not better than the control by some clinically relevant difference. Given prespecified levels of pairwise (in)commensurability, the subtrial sample sizes are solved simultaneously. The proposed Bayesian approach resembles the frequentist formulation of the problem in yielding comparable sample sizes for circumstances of no borrowing. When borrowing is enabled between commensurate subtrials, a considerably smaller trial sample size is required compared to the widely implemented approach of no borrowing. We illustrate the use of our sample size formulae with two examples based on real basket trials. A comprehensive simulation study further shows that the proposed methodology can maintain the true positive and false positive rates at desired levels.

Paradoxes in the coevolution of contagions and institutions.

Epidemic models study the spread of undesired agents through populations, be it infectious diseases through a country, misinformation in social media or pests infesting a region. In combating these epidemics, we rely neither on global top-down interventions, nor solely on individual adaptations. Instead, interventions commonly come from local institutions such as public health departments, moderation teams on social media platforms or other forms of group governance. Classic models, which are often individual or agent-based, are ill-suited to capture local adaptations. We leverage developments of institutional dynamics based on cultural group selection to study how groups attempt local control of an epidemic by taking inspiration from the successes and failures of other groups. Incorporating institutional changes into epidemic dynamics reveals paradoxes: a higher transmission rate can result in smaller outbreaks as does decreasing the speed of institutional adaptation. When groups perceive a contagion as more worrisome, they can invest in improved policies and, if they maintain these policies long enough to have impact, lead to a reduction in endemicity. By looking at the interplay between the speed of institutions and the transmission rate of the contagions, we find rich coevolutionary dynamics that reflect the complexity of known biological and social contagions.

Pragmatic nationwide master observational trial based on genomic alterations in advanced solid tumors: KOrean Precision Medicine Networking Group Study of MOlecular profiling guided therapy based on genomic alterations in advanced Solid tumors (KOSMOS)-II study protocol KCSG AL-22-09.

BACKGROUND: Next-generation sequencing (NGS) has been introduced to many Korean institutions to support molecular diagnostics in cancer since 2017, when it became eligible for reimbursement by the National Health Insurance Service. However, the uptake of molecularly guided treatment (MGT) based on NGS results has been limited because of stringent regulations regarding prescriptions outside of approved indications, a lack of clinical trial opportunities, and limited access to molecular tumor boards (MTB) at most institutions. The KOSMOS-II study was designed to demonstrate the feasibility and effectiveness of MGT, informed by MTBs, using a nationwide precision medicine platform. METHODS: The KOSMOS-II trial is a large-scale nationwide master observational study. It involves a framework for screening patients with metastatic solid tumors for actionable genetic alterations based on local NGS testing. It recommends MGT through a remote and centralized MTB meeting held biweekly. MGT can include one of the following options: Tier 1, the therapeutic use of investigational drugs targeting genetic alterations such as ALK, EGFR, ERBB2, BRAF, FH, ROS1, and RET, or those with high tumor mutational burden; Tier 2, comprising drugs with approved indications or those permitted for treatment outside of the indications approved by the Health Insurance Review and Assessment Service of Korea; Tier 3, involving clinical trials matching the genetic alterations recommended by the MTB. Given the anticipated proportion of patients receiving MGT in the range of 50% ± 3.25%, this study aims to enroll 1,000 patients. Patients must have progressed to one or more lines of therapy and undergone NGS before enrollment. DISCUSSION: This pragmatic master protocol provides a mass-screening platform for rare genetic alterations and high-quality real-world data. Collateral clinical trials, translational studies, and clinico-genomic databases will contribute to generating evidence for drug repositioning and the development of new biomarkers. TRIAL REGISTRATION: NCT05525858.

Advantages and Challenges of Platform Trials for Disease Modifying Therapies in Parkinson's Disease.

Traditional drug development in Parkinson's disease (PD) faces significant challenges because of its protracted timeline and high costs. In response, innovative master protocols are emerging and designed to address multiple research questions within a single overarching protocol. These trials may offer advantages such as increased efficiency, agility in adding new treatment arms, and potential cost savings. However, they also present organizational, methodological, funding, regulatory, and sponsorship challenges. We review the potential of master protocols, focusing on platform trials, for disease modifying therapies in PD. These trials share a common control group and allow for the termination or addition of treatment arms during a trial with non-predetermined end. Specific issues exist for a platform trial in the PD field considering the heterogeneity of patients in terms of phenotype, genotype and staging, the confounding effects of symptomatic treatments, and the choice of outcome measures with no consensus on a non-clinical biomarker to serve as a surrogate and the slowness of PD progression. We illustrate these aspects using the examples of the main PD platform trials currently in development with each one targeting distinct goals, populations, and outcomes. Overall, platform trials hold promise in expediting the evaluation of potential therapies for PD. However, it remains to be proven whether these theoretical benefits will translate into increased production of high-quality trial data. Success also depends on the willingness of pharmaceutical companies to engage in such trials and whether this approach will ultimately hasten the identification and licensing of effective disease-modifying drugs. © 2024 International Parkinson and Movement Disorder Society.

Predicting the postoperative intraocular lens position based on IOL Master 700 biometry, compared with results from the anterior segment analysis system.

PURPOSE: Predict intraocular lens position after cataract surgery using the IOL Master 700 and explore the associated ocular parameters compared with the results obtained from the anterior segment analysis system (Sirius, CSO Inc, Florence, Italy). METHODS: A total of 98 patients (106 eyes) were included in the retrospective study. The postoperative intraocular lens position was obtained using the IOL Master 700 and measured using Adobe Illustrator software. Correlation analysis and linear regression analysis were applied to study the correlation between the actual position of the postoperative intraocular lens (ALP) and the ocular parameters. In addition, Bland-Altman consistency analysis was used to compare the consistency between any two among the predicted intraocular lens position (ALPi) obtained using IOL Master 700 biometry, the predicted artificial lens position (ALPs) calculated using the anterior segment analysis system, or the ALP. RESULTS: Ocular parameters, including preoperative anterior chamber depth, lens thickness, axial length, white-to-white, and postoperative refractive error were all correlated with ALP after cataract surgery (P < 0.05) using univariate analysis. However, in multivariate linear regression, only the first three variables were correlated with ALP. Compared with the equation obtained by the anterior segment analysis, the equation from IOL Master 700 biometry provided a better fit. The results of the consistency analysis showed that ALP, ALPi, and ALPs were in good agreement. CONCLUSION: IOL Master 700 biometry can help predict intraocular lens position after surgery, and its accuracy is better than that provided by the anterior segment analysis system.

Identifying competencies in advanced healthcare practice: an umbrella review.

The four pillars of advanced healthcare practice (AHCP) are clinical practice, leadership and management, education, and research. It is unclear, however; how competencies of AHCP as defined by individual health professions relate to these pillars. Addressing this knowledge gap will help to facilitate the operationalization of AHCP as a concept and help inform educational curricula. To identify existing competencies across AHCP literature and examine how they relate to the four pillars of a multi-professional AHCP framework. An umbrella review was conducted in accordance with JBI methodology. The electronic search for published and grey literature was completed using CINAHL, Scopus, Medline (OVID), Embase (OVID), ERIC (OVID) and Google. Secondary reviews and research syntheses of master level AHCP programs published after 1990 in either English or French were considered for inclusion and results were analyzed using a directed content analysis. Seventeen publications detailing 620 individual competencies were included. AHCP competencies were described across four professions and 22 countries, with many publications related to nursing and AHCP in the United Kingdom, Canada, and Australia. Many retrieved competencies were found to map to the four pillars of AHCP, although clinical practice and leadership and management pillars were addressed more often. Competencies of AHCP are generally consistent with the four pillars. However, the distribution of competencies is unequal across pillars, professions, and geographical regions, which may provide direction for further research. Doi: 10.17605/OSF.IO/KV2FD Published on March 07, 2023.

Epistemic discourses concerning the competence developed in a norwegian master's degree program in health science.

It has been claimed that various discourses related to competence influence higher education, but there is limited understanding of the discourses underlying competence development. The specific aim of this study was to explore epistemic discourses concerning the development of competence of health professionals with a master's degree in health science. Accordingly, the study was qualitative and adopted discourse analysis. Twelve participants, all of whom were Norwegian health professionals aged between 29 and 49 years, participated in this study. Four participants were in the final stage of study for their master's degree with three months left before completion, four had completed their degree two weeks before their participation, and four had been working for one year after the completion of their degree. Data were collected in three group interviews. Three epistemic discourses were revealed: (1) a critical thinking competencies discourse, (2) a scientific thinking competencies discourse, and (3) a competence-in-use discourse. The former two discourses were considered the dominant discourses and indicated that a knowing "that" discourse connected the specialized competence of different health professionals with a wider field of competence. This wider field transcended the boundaries of various health disciplines and represented a novel competence developed through a synergizing process between critical and scientific thinking competencies, which seems to drive continued competence development. A competence-in-use discourse was formed in the process. This discourse can be viewed as a unique outcome that contributes to health professionals' specialized competence and suggests that a knowing "how" discourse was also an underlying background discourse.

Stochastic dynamics of barrier island elevation.

Barrier islands are ubiquitous coastal features that create low-energy environments where salt marshes, oyster reefs, and mangroves can develop and survive external stresses. Barrier systems also protect interior coastal communities from storm surges and wave-driven erosion. These functions depend on the existence of a slowly migrating, vertically stable barrier, a condition tied to the frequency of storm-driven overwashes and thus barrier elevation during the storm impact. The balance between erosional and accretional processes behind barrier dynamics is stochastic in nature and cannot be properly understood with traditional continuous models. Here we develop a master equation describing the stochastic dynamics of the probability density function (PDF) of barrier elevation at a point. The dynamics are controlled by two dimensionless numbers relating the average intensity and frequency of high-water events (HWEs) to the maximum dune height and dune formation time, which are in turn a function of the rate of sea level rise, sand availability, and stress of the plant ecosystem anchoring dune formation. Depending on the control parameters, the transient solution converges toward a high-elevation barrier, a low-elevation barrier, or a mixed, bimodal, state. We find the average after-storm recovery time-a relaxation time characterizing barrier's resiliency to storm impacts-changes rapidly with the control parameters, suggesting a tipping point in barrier response to external drivers. We finally derive explicit expressions for the overwash probability and average overwash frequency and transport rate characterizing the landward migration of barriers.