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Abstract Idiopathic pulmonary fibrosis (IPF) is a progressive respiratory scarring disease arising from the maladaptive differentiation of lung stem cells into bronchial epithelial cells rather than into alveolar type 1 (AT1) cells, which are responsible for gas exchange. Here, we report that healthy lungs maintain their stem cells through tonic Hippo and β-catenin signaling, which promote Yap/Taz degradation and allow for low-level expression of the Wnt target gene Myc. Inactivation of upstream activators of the Hippo pathway in lung stem cells inhibits this tonic β-catenin signaling and Myc expression and promotes their Taz-mediated differentiation into AT1 cells. Vice versa, increased Myc in collaboration with Yap promotes the differentiation of lung stem cells along the basal and myoepithelial-like lineages allowing them to invade and bronchiolize the lung parenchyma in a process reminiscent of submucosal gland development. Our findings indicate that stem cells exhibiting the highest Myc levels become supercompetitors that drive remodeling, whereas loser cells with lower Myc levels terminally differentiate into AT1 cells.

Hemibiotrophic fungi in the genus Colletotrichum employ a biotrophic phase to invade host epidermal cells followed by a necrotrophic phase to spread through neighboring mesophyll and epidermal cells. We used serial block face-scanning electron microscopy (SBF-SEM) to compare subcellular changes that occur in Medicago sativa (alfalfa) cotyledons during infection by Colletotrichum destructivum (compatible on M. sativa) and C. higginsianum (incompatible on M. sativa). Three-dimensional reconstruction of serial images revealed that alfalfa epidermal cells infected with C. destructivum undergo massive cytological changes during the first 60 h following inoculation to accommodate extensive intracellular hyphal growth. Conversely, inoculation with the incompatible species C. higginsianum resulted in no successful penetration events and frequent formation of papilla-like structures and cytoplasmic aggregates beneath attempted fungal penetration sites. Further analysis of the incompatible interaction using focused ion beam-scanning electron microscopy (FIB-SEM) revealed the formation of large multivesicular body-like structures that appeared spherical and were not visible in compatible interactions. These structures often fused with the host plasma membrane, giving rise to paramural bodies that appeared to be releasing extracellular vesicles (EVs). Isolation of EVs from the apoplastic space of alfalfa leaves at 60 h postinoculation showed significantly more vesicles secreted from alfalfa infected with incompatible fungus compared with compatible fungus, which in turn was more than produced by noninfected plants. Thus, the increased frequency of paramural bodies during incompatible interactions correlated with an increase in EV quantity in apoplastic wash fluids. Together, these results suggest that EVs and paramural bodies contribute to immunity during pathogen attack in alfalfa. [Figure: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

The move toward early detection and treatment of cancer presents challenges for value assessment using traditional endpoints. Current cancer management rarely considers the full economic and societal benefits of therapies. Our study used a modified Delphi process to develop principles for defining and assessing value of cancer therapies that aligns with the current trajectory of oncology research and reflects broader notions of value. 24 experts participated in consensus-building activities across 5 months (16 took part in structured interactions, including a survey, plenary sessions, interviews, and off-line discussions, while 8 participated in interviews). Discussion focused on: 1) which oncology-relevant endpoints should be used for assessing treatments for early-stage cancer and access decisions for early-stage treatments, and 2) the importance of additional value components and how these can be integrated in value assessments. The expert group reached consensus on 4 principles in relation to the first area (consider oncology-relevant endpoints other than overall survival; build evidence for endpoints that provide earlier indication of efficacy; develop evidence for the next generation of predictive measures; use managed entry agreements supported by ongoing evidence collection to address decision-maker evidence needs) and 3 principles in relation to the second (routinely use patient reported outcomes in value assessments; assess broad economic impact of new medicines; consider other value aspects of relevance to patients and society).

We used serial block-face scanning electron microscopy (SBF-SEM) to study the host–pathogen interface between Arabidopsis cotyledons and the hemibiotrophic fungus Colletotrichum higginsianum. By combining high-pressure freezing and freeze-substitution with SBF-SEM, followed by segmentation and reconstruction of the imaging volume using the freely accessible software IMOD, we created 3D models of the series of cytological events that occur during the Colletotrichum–Arabidopsis susceptible interaction. We found that the host cell membranes underwent massive expansion to accommodate the rapidly growing intracellular hypha. As the fungal infection proceeded from the biotrophic to the necrotrophic stage, the host cell membranes went through increasing levels of disintegration culminating in host cell death. Intriguingly, we documented autophagosomes in proximity to biotrophic hyphae using transmission electron microscopy (TEM) and a concurrent increase in autophagic flux between early to mid/late biotrophic phase of the infection process. Occasionally, we observed osmiophilic bodies in the vicinity of biotrophic hyphae using TEM only and near necrotrophic hyphae under both TEM and SBF-SEM. Overall, we established a method for obtaining serial SBF-SEM images, each with a lateral (x-y) pixel resolution of 10 nm and an axial (z) resolution of 40 nm, that can be reconstructed into interactive 3D models using the IMOD. Application of this method to the Colletotrichum–Arabidopsis pathosystem allowed us to more fully understand the spatial arrangement and morphological architecture of the fungal hyphae after they penetrate epidermal cells of Arabidopsis cotyledons and the cytological changes the host cell undergoes as the infection progresses toward necrotrophy. [Graphic: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Abstract Recent advances in single-cell RNA sequencing (scRNA-seq) and epithelium lineage labeling have yielded identification of multiple abnormal epithelial progenitor populations during alveolar type 2 (ATII) cell differentiation into alveolar type 1 (ATI) cells during regenerative lung post-fibrotic injury. These abnormal cells include basaloid/basal-like cells, ATII transition cells, and persistent epithelial progenitors (PEPs). These cells occurred and accumulated during the regeneration of distal airway and alveoli in response to both chronic and acute pulmonary injury. Among the alveolar epithelial progenitors, PEPs express a distinct Krt8 + phenotype that is rarely found in intact alveoli. However, post-injury, the Krt8 + phenotype is seen in dysplastic epithelial cells. Fully understanding the characteristics and functions of these newly found, injury-induced abnormal behavioral epithelial progenitors and the signaling pathways regulating their phenotype could potentially point the way to unique therapeutic targets for fibrosing lung diseases. This review summarizes recent advances in understanding these epithelial progenitors as they relate to uncovering regenerative mechanisms.

Objectives The enormous toll of the COVID-19 pandemic has heightened the urgency of collecting and analysing population-scale datasets in real time to monitor and better understand the evolving pandemic. The objectives of this study were to examine the relationship of risk factors to COVID-19 susceptibility and severity and to develop risk models to accurately predict COVID-19 outcomes using rapidly obtained self-reported data.Design A cross-sectional study.Setting AncestryDNA customers in the USA who consented to research.Participants The AncestryDNA COVID-19 Study collected self-reported survey data on symptoms, outcomes, risk factors and exposures for over 563 000 adult individuals in the USA in just under 4 months, including over 4700 COVID-19 cases as measured by a self-reported positive test.Results We replicated previously reported associations between several risk factors and COVID-19 susceptibility and severity outcomes, and additionally found that differences in known exposures accounted for many of the susceptibility associations. A notable exception was elevated susceptibility for men even after adjusting for known exposures and age (adjusted OR=1.36, 95% CI=1.19 to 1.55). We also demonstrated that self-reported data can be used to build accurate risk models to predict individualised COVID-19 susceptibility (area under the curve (AUC)=0.84) and severity outcomes including hospitalisation and critical illness (AUC=0.87 and 0.90, respectively). The risk models achieved robust discriminative performance across different age, sex and genetic ancestry groups within the study.Conclusions The results highlight the value of self-reported epidemiological data to rapidly provide public health insights into the evolving COVID-19 pandemic.

Type 2 alveolar epithelial cells (AEC2s) function as progenitor cells in the lung. We have shown previously that failure of AEC2 regeneration results in progressive lung fibrosis in mice and is a cardinal feature of idiopathic pulmonary fibrosis (IPF). In this study, we identified deficiency of a specific zinc transporter, SLC39A8 (ZIP8), in AEC2s from both IPF lungs and lungs of old mice. Loss of ZIP8 expression was associated with impaired renewal capacity of AEC2s and enhanced lung fibrosis. ZIP8 regulation of AEC2 progenitor function was dependent on SIRT1. Replenishment with exogenous zinc and SIRT1 activation promoted self-renewal and differentiation of AEC2s from lung tissues of IPF patients and old mice. Deletion of Zip8 in AEC2s in mice resulted in impaired AEC2 renewal, increased susceptibility to bleomycin injury, and development of spontaneous lung fibrosis. Therapeutic strategies to restore zinc metabolism and appropriate SIRT1 signaling could improve AEC2 progenitor function and mitigate ongoing fibrogenesis.

Idiopathic pulmonary fibrosis (IPF) is characterized by aberrant repair that diminishes lung function via mechanisms that remain poorly understood. CC chemokine receptor (CCR10) and its ligand CCL28 were both elevated in IPF compared with normal donors. CCR10 was highly expressed by various cells from IPF lungs, most notably stage-specific embryonic antigen-4–positive mesenchymal progenitor cells (MPCs). In vitro, CCL28 promoted the proliferation of CCR10+ MPCs while CRISPR/Cas9–mediated targeting of CCR10 resulted in the death of MPCs. Following the intravenous injection of various cells from IPF lungs into immunodeficient (NOD/SCID-γ, NSG) mice, human CCR10+ cells initiated and maintained fibrosis in NSG mice. Eph receptor A3 (EphA3) was among the highest expressed receptor tyrosine kinases detected on IPF CCR10+ cells. Ifabotuzumab-targeted killing of EphA3+ cells significantly reduced the numbers of CCR10+ cells and ameliorated pulmonary fibrosis in humanized NSG mice. Thus, human CCR10+ cells promote pulmonary fibrosis, and EphA3 mAb–directed elimination of these cells inhibits lung fibrosis.

Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of this study was to improve upon the established Revised Framingham Stroke Risk Score and design an interactive Non-Linear Stroke Risk Score. Leveraging machine learning algorithms, our work aimed at increasing the accuracy of event prediction and uncovering new relationships in an interpretable fashion. A two-phase approach was used to create our stroke risk prediction score. First, clinical examinations of the Framingham offspring cohort were utilized as the training dataset for the predictive model. Optimal Classification Trees were used to develop a tree-based model to predict 10-year risk of stroke. Unlike classical methods, this algorithm adaptively changes the splits on the independent variables, introducing non-linear interactions among them. Second, the model was validated with a multi-ethnicity cohort from the Boston Medical Center. Our stroke risk score suggests a key dichotomy between patients with history of cardiovascular disease and the rest of the population. While it agrees with known findings, it also identified 23 unique stroke risk profiles and highlighted new non-linear relationships; such as the role of T-wave abnormality on electrocardiography and hematocrit levels in a patient's risk profile. Our results suggested that the non-linear approach significantly improves upon the baseline in the c-statistic (training 87.43% (CI 0.85-0.90) vs. 73.74% (CI 0.70-0.76); validation 75.29% (CI 0.74-0.76) vs 65.93% (CI 0.64-0.67), even in multi-ethnicity populations. The clinical implications of the new risk score include prioritization of risk factor modification and personalized care at the patient level with improved targeting of interventions for stroke prevention.

Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients. De-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts. The derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation (≤ 93%), elevated levels of C-reactive protein (≥ 130 mg/L), blood urea nitrogen (≥ 18 mg/dL), and blood creatinine (≥ 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-of-sample AUCs of 0.90 (95% CI, 0.87-0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88-0.95) on Seville patients, 0.87 (95% CI, 0.84-0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76-0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality_calculator and is currently in clinical use. The CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States.

Summary: Fibroblast heterogeneity has long been recognized in mouse and human lungs, homeostasis, and disease states. However, there is no common consensus on fibroblast subtypes, lineages, biological properties, signaling, and plasticity, which severely hampers our understanding of the mechanisms of fibrosis. To comprehensively classify fibroblast populations in the lung using an unbiased approach, single-cell RNA sequencing was performed with mesenchymal preparations from either uninjured or bleomycin-treated mouse lungs. Single-cell transcriptome analyses classified and defined six mesenchymal cell types in normal lung and seven in fibrotic lung. Furthermore, delineation of their differentiation trajectory was achieved by a machine learning method. This collection of single-cell transcriptomes and the distinct classification of fibroblast subsets provide a new resource for understanding the fibroblast landscape and the roles of fibroblasts in fibrotic diseases. : Xie et al. have analyzed mesenchymal cell subpopulations at single-cell resolution and have demonstrated known subtypes and a newly emerging subtype during pulmonary fibrosis in mouse lung. Keywords: single-cell RNA-seq, fibroblast, lung mesenchymal cells, fibrosis

The paper argues that stochastic and deterministic knowledge complement and improve upon each other. We introduce a stochastic model for acquired knowledge and prove that the numerical data provided fits quite well the estimated outcomes of the model.

Abstract Background Though most models of palliative care specifically include spiritual care as an essential element, secular health care organizations struggle with supporting spiritual care for people who are dying and their families. Organizations often leave responsibility for such care with individual care providers, some of whom are comfortable with this role and well supported, others who are not. This study looked to hospice programs founded and operated on specific spiritual foundations to identify, if possible, organizational-level practices that support high-quality spiritual care that then might be applied in secular healthcare organizations. Methods Forty-six digitally-recorded interviews were conducted with bereaved family members, care providers and administrators associated with four hospice organizations in North America, representing Buddhist, Catholic, Jewish, and Salvation Army faith traditions. The interviews were analyzed iteratively using the constant comparison method within a grounded theory approach. Results Nine Principles for organizational support for spiritual care emerged from the interviews. Three Principles identify where and how spiritual care fits with the other aspects of palliative care; three Principles guide the organizational approach to spiritual care, including considerations of assessment and of sacred places; and three Principles support the spiritual practice of care providers within the organizations. Organizational practices that illustrate each of the principles were provided by interviewees. Conclusions These Principles, and the practices underlying them, could increase the quality of spiritual care offered by secular health care organizations at the end of life.

Members of the PEA3 transcription factors are emerging as bone fide targets for fibroblast growth factor (FGF) signaling. Among them, ETV4 and ETV5 appear to mediate FGF10 signaling during early embryonic lung development. In this paper, recently obtained Tg(Etv4-GFP) and Etv5CreERT2−RFP fluorescent reporter lines were generally characterized during early embryonic development and in the context of FGF10 signaling, in particular. We found that both Tg(Etv4-GFP) and Etv5CreERT2−RFP were primarily expressed in the epithelium of the lung during embryonic development. However, the expression of Etv5CreERT2−RFP was much higher than that of Tg(Etv4-GFP), and continued to increase during development, whereas Tg(Etv4-GFP) decreased. The expression patterns of the surrogate fluorescent protein GFP and RFP for ETV4 and ETV5, respectively, agreed with known regions of FGF10 signaling in various developing organs, including the lung, where ETV4-GFP was seen primarily in the distal epithelium and to a lesser extent in the surrounding mesenchyme. As expected, ETV5-RFP was restricted to the lung epithelium, showing a decreasing expression pattern from distal buds to proximal conducting airways. FGF10 inhibition experiments confirmed that both Etv4 and Etv5 are downstream of FGF10 signaling. Finally, we also validated that both fluorescent reporters responded to FGF10 inhibition in vitro. In conclusion, these two reporter lines appear to be promising tools to monitor FGF10/FGFR2b signaling in early lung development. These tools will have to be further validated at later stages and in other organs of interest.

A foundation stone of Hans Georg Gadamer’s philosophical hermeneutics is the notion of the sensus communis. The philosophical significance of a “sensus communis” (common sense) begins with Aristotle, who offered scattered reflections. The topic was taken up in earnest in Enlightenment thought and in German idealism, but it became more of an individual faculty, lacking the deep sense of community and tradition found in earlier formulations. In this paper, the author demonstrates Gadamer’s debt to Pietist thought, examining his appropriation and use of the theology of Friedrich Christoph Oetinger (1702–1782), a leading figure in Swabian Pietism, whose ideas had a significant impact in theological circles and broader cultural life. Gadamer’s critique of the Enlightenment’s ‘prejudice against prejudice,’ owes a debt to the Pietist conception of the sensus communis and his practical philosophy to Pietism’s emphasis on ‘application’ as a fundamental aspect of a hermeneutical triad.

Early mouse lung development, including specification of primordia, patterning of early endoderm and determination of regional progenitor cell fates, is tightly regulated. The ability to culture explanted embryonic lung tissue provides a tractable model to study cellular interactions and paracrine factors that regulate these processes. We provide up-to-date protocols for the establishment of this culture model and its application to investigate hedgehog signaling in the developing lung.