Acinar cell clonal expansion in pancreas homeostasis and carcinogenesis.

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer deaths worldwide1. Studies in human tissues and in mouse models have suggested that for many cancers, stem cells sustain early mutations driving tumour development2,3. For the pancreas, however, mechanisms underlying cellular renewal and initiation of PDAC remain unresolved. Here, using lineage tracing from the endogenous telomerase reverse transcriptase (Tert) locus, we identify a rare TERT-positive subpopulation of pancreatic acinar cells dispersed throughout the exocrine compartment. During homeostasis, these TERThigh acinar cells renew the pancreas by forming expanding clones of acinar cells, whereas randomly marked acinar cells do not form these clones. Specific expression of mutant Kras in TERThigh acinar cells accelerates acinar clone formation and causes transdifferentiation to ductal pre-invasive pancreatic intraepithelial neoplasms by upregulating Ras-MAPK signalling and activating the downstream kinase ERK (phospho-ERK). In resected human pancreatic neoplasms, we find that foci of phospho-ERK-positive acinar cells are common and frequently contain activating KRAS mutations, suggesting that these acinar regions represent an early cancer precursor lesion. These data support a model in which rare TERThigh acinar cells may sustain KRAS mutations, driving acinar cell expansion and creating a field of aberrant cells initiating pancreatic tumorigenesis.

Predicting Intensive Care Delirium with Machine Learning: Model Development and External Validation.

BACKGROUND: Delirium poses significant risks to patients, but countermeasures can be taken to mitigate negative outcomes. Accurately forecasting delirium in intensive care unit (ICU) patients could guide proactive intervention. Our primary objective was to predict ICU delirium by applying machine learning to clinical and physiologic data routinely collected in electronic health records. METHODS: Two prediction models were trained and tested using a multicenter database (years of data collection 2014 to 2015), and externally validated on two single-center databases (2001 to 2012 and 2008 to 2019). The primary outcome variable was delirium defined as a positive Confusion Assessment Method for the ICU screen, or an Intensive Care Delirium Screening Checklist of 4 or greater. The first model, named "24-hour model," used data from the 24 h after ICU admission to predict delirium any time afterward. The second model designated "dynamic model," predicted the onset of delirium up to 12 h in advance. Model performance was compared with a widely cited reference model. RESULTS: For the 24-h model, delirium was identified in 2,536 of 18,305 (13.9%), 768 of 5,299 (14.5%), and 5,955 of 36,194 (11.9%) of patient stays, respectively, in the development sample and two validation samples. For the 12-h lead time dynamic model, delirium was identified in 3,791 of 22,234 (17.0%), 994 of 6,166 (16.1%), and 5,955 of 28,440 (20.9%) patient stays, respectively. Mean area under the receiver operating characteristics curve (AUC) (95% CI) for the first 24-h model was 0.785 (0.769 to 0.801), significantly higher than the modified reference model with AUC of 0.730 (0.704 to 0.757). The dynamic model had a mean AUC of 0.845 (0.831 to 0.859) when predicting delirium 12 h in advance. Calibration was similar in both models (mean Brier Score [95% CI] 0.102 [0.097 to 0.108] and 0.111 [0.106 to 0.116]). Model discrimination and calibration were maintained when tested on the validation datasets. CONCLUSIONS: Machine learning models trained with routinely collected electronic health record data accurately predict ICU delirium, supporting dynamic time-sensitive forecasting.

Widespread sex dimorphism in aging and age-related diseases.

Although aging is a conserved phenomenon across evolutionary distant species, aspects of the aging process have been found to differ between males and females of the same species. Indeed, observations across mammalian studies have revealed the existence of longevity and health disparities between sexes, including in humans (i.e. with a female or male advantage). However, the underlying mechanisms for these sex differences in health and lifespan remain poorly understood, and it is unclear which aspects of this dimorphism stem from hormonal differences (i.e. predominance of estrogens vs. androgens) or from karyotypic differences (i.e. XX vs. XY sex chromosome complement). In this review, we discuss the state of the knowledge in terms of sex dimorphism in various aspects of aging and in human age-related diseases. Where the interplay between sex differences and age-related differences has not been explored fully, we present the state of the field to highlight important future research directions. We also discuss various dietary, drug or genetic interventions that were shown to improve longevity in a sex-dimorphic fashion. Finally, emerging tools and models that can be leveraged to decipher the mechanisms underlying sex differences in aging are also briefly discussed.

Lack of accelerated ovarian aging in a follicle-stimulating hormone receptor haploinsufficiency model.

Follicle-stimulation hormone (FSH) and FSH receptor (FSHR) signaling is essential for lifelong ovarian and endocrine functions in females. Previous studies have reported that Fshr haploinsufficiency in female mice led to accelerated ovarian aging, including anticipated progressive fertility decline, irregular estrus cycles, increased follicular atresia and premature ovarian failure at 7 to 9 months of age. Interestingly, these phenotypes resemble key characteristics of human menopause and thus Fshr haploinsufficiency was proposed as a promising research mouse model of menopause. However, the Fshr haploinsufficiency model had not been fully explored, especially at the molecular level. In this study, we characterized the ovarian and endocrine functions of a Fshr heterozygous knockout allele that was generated on the C57BL/6 genetic background as part of the Knockout Mouse Project (KOMP). Based on our analyses of these mice using a breeding assay, ovarian tissue histology and serum hormone quantifications (i.e. FSH, AMH, INHA) analyses, the KOMP Fshr heterozygous knockout female mice do not show the anticipated phenotypes of ovarian aging in terms of fertility and endocrine function. We further confirmed that the expression of Fshr is unaltered in the ovaries of the KOMP Fshr heterozygous knockout animals compared to wild-type. Together, our data suggests that the KOMP Fshr heterozygous knockout strain does not recapitulate the previously reported ovarian aging phenotypes associated to another model of Fshr haploinsufficiency.

Transcriptomes of aging brain, heart, muscle, and spleen from female and male African turquoise killifish.

The African turquoise killifish is an emerging vertebrate model organism with great potential for aging research due to its naturally short lifespan. Thus far, turquoise killifish aging 'omic' studies have examined a single organ, single sex and/or evaluated samples from non-reference strains. Here, we describe a resource dataset of ribosomal RNA-depleted RNA-seq libraries generated from the brain, heart, muscle, and spleen from both sexes, as well as young and old animals, in the reference GRZ turquoise killifish strain. We provide basic quality control steps and demonstrate the utility of our dataset by performing differential gene expression and gene ontology analyses by age and sex. Importantly, we show that age has a greater impact than sex on transcriptional landscapes across probed tissues. Finally, we confirm transcription of transposable elements (TEs), which are highly abundant and increase in expression with age in brain tissue. This dataset will be a useful resource for exploring gene and TE expression as a function of both age and sex in a powerful naturally short-lived vertebrate model.

Age-maintained human neurons demonstrate a developmental loss of intrinsic neurite growth ability.

Injury to adult mammalian central nervous system (CNS) axons results in limited regeneration. Rodent studies have revealed a developmental switch in CNS axon regenerative ability, yet whether this is conserved in humans is unknown. Using human fibroblasts from 8 gestational-weeks to 72 years-old, we performed direct reprogramming to transdifferentiate fibroblasts into induced neurons (Fib-iNs), avoiding pluripotency which restores cells to an embryonic state. We found that early gestational Fib-iNs grew longer neurites than all other ages, mirroring the developmental switch in regenerative ability in rodents. RNA-sequencing and screening revealed ARID1A as a developmentally-regulated modifier of neurite growth in human neurons. These data suggest that age-specific epigenetic changes may drive the intrinsic loss of neurite growth ability in human CNS neurons during development. One-Sentence Summary: Directly-reprogrammed human neurons demonstrate a developmental decrease in neurite growth ability.

Single-cell RNA-seq of primary bone marrow neutrophils from female and male adult mice.

Widespread sex-dimorphism is observed in the mammalian immune system. Consistently, studies have reported sex differences in the transcriptome of immune cells at the bulk level, including neutrophils. Neutrophils are the most abundant cell type in human blood, and they are key components of the innate immune system as they form a first line of defense against pathogens. Neutrophils are produced in the bone marrow, and differentiation and maturation produce distinct neutrophil subpopulations. Thus, single-cell resolution studies are crucial to decipher the biological significance of neutrophil heterogeneity. However, since neutrophils are very RNA-poor, single-cell profiling of these cells has been technically challenging. Here, we generated a single-cell RNA-seq dataset of primary neutrophils from adult female and male mouse bone marrow. After stringent quality control, we found that previously characterized neutrophil subpopulations can be detected in both sexes. Additionally, we confirmed that canonical sex-linked markers are differentially expressed between female and male cells across neutrophil subpopulations. This dataset provides a groundwork for comparative studies on the lifelong transcriptional sexual dimorphism of neutrophils.

Functional genomics of inflamm-aging and immunosenescence.

The aging population is at a higher risk for age-related diseases and infections. This observation could be due to immunosenescence: the decline in immune efficacy of both the innate and the adaptive immune systems. Age-related immune decline also links to the concept of 'inflamm-aging,' whereby aging is accompanied by sterile chronic inflammation. Along with a decline in immune function, aging is accompanied by a widespread of 'omics' remodeling. Transcriptional landscape changes linked to key pathways of immune function have been identified across studies, such as macrophages having decreased expression of genes associated to phagocytosis, a major function of macrophages. Therefore, a key mechanism underlying innate immune cell dysfunction during aging may stem from dysregulation of youthful genomic networks. In this review, we discuss both molecular and cellular phenotypes of innate immune cells that contribute to age-related inflammation.

Ancillary studies on cell blocks from fine needle aspiration specimens of salivary gland lesions: A multi-institutional study.

BACKGROUND: Ancillary studies are commonly performed on cell blocks prepared from fine-needle aspiration (FNA) specimens. There are limited studies in application of ancillary studies on cell blocks from salivary gland (SG) FNAs. This multi-institutional study evaluates the role of ancillary studies performed on cell blocks in the diagnosis of SG lesions, and their impact on clinical management. METHOD: The electronic pathology archives of three large academic institutions were searched for SG FNAs with ancillary studies performed on cell blocks. The patient demographics, FNA site, cytologic diagnosis, ancillary studies, and surgical follow-up were recorded. If needed, the cytologic diagnoses were reclassified as per the Milan System for Reporting Salivary Gland Cytopathology (MSRSGC). RESULTS: 117 SG FNA cases were identified including 3, 10, 11, 6, 23, 4, and 60 cases in MSRSGC categories I, II, III, IVa, IVb, V, VI, respectively with surgical follow-up available ranging from 27% to 100% within each category. Ancillary studies including histochemistry, immunocytochemistry (IHC), and in situ hybridization (ISH) were beneficial in 60%-100% of cases in each category. Risk of malignancy was 100% in both the suspicious for malignancy (V) and malignant (VI) categories. Ancillary studies improved diagnosis in 60% of non-neoplastic cases (II, 6/10), 100% of benign neoplasm cases (IVa, 6/6), and 98.3% of malignant cases (VI, 59/60). CONCLUSION: Judicious and case-based ancillary studies performed on SG FNA cell blocks with sufficient material can improve the diagnostic yield by further characterization of the atypical/neoplastic cells, particularly in MSRSGC categories IVa-VI.

Protocol for analysis of mouse neutrophil NETosis by flow cytometry.

Studies involving neutrophils are steadily increasing, thus creating a need for more optimized and thorough protocols for studying neutrophil function. Here, we present our protocol for extracting mouse bone marrow neutrophils, estimating the purity of isolated neutrophils, and assessing their ability to induce NETosis upon an external cue. We test two isolation protocols that can be used to attain neutrophils to assess NETosis induction. This approach allows for the parallel assessment of NETosis induction in cohorts larger than 10 samples. For complete details on the use and execution of this protocol, please refer to Lu et al., 2021.