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Salt marshes are globally important ecosystems, but many have been lost or transformed due to the impacts of global change. There have been attempts to broadly quantify salt marsh communities, especially the ubiquitous grasses which serve as foundation species such as Spartina alterniflora and Spartina patens, the latter of which is being lost due to sea level rise. However, few researchers have used high-resolution geospatial imagery to quantify fine-scale changes in the distribution of grasses or to track losses of S. patens. To address this issue, we utilized a simple and rapid method of classifying geospatial marsh imagery with cloud-based machine learning in Google Earth Engine (>92% accuracy for S. patens regardless of imagery age). Our methods allowed us to characterize full landscapes (two geospatially proximal areas, >7,000 ha each) of critical salt marshes on the New Jersey coast and to evaluate fine-scale (1-m) community transformations in response to global change with imagery from 2006 to 2019. Notably, one marsh experienced very little change while the other experienced an 81.17% (1,087 ha) loss of S. patens, illuminating disparate patterns of change for two geographically proximal ecosystems. Further exploration revealed an association in the loss of S. patens with increases in streamflow and total nitrogen content in the rivers that run through each marsh. These results signify the importance of broad-scale ecological studies that evaluate fine-scale community transformations and for management strategies that do not generalize across landscapes of an ecosystem-type.

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

Acute stress triggers plasticity of forebrain synapses as well as behavioral changes. Here we reveal that Tumor Necrosis Factor α (TNF) is a required downstream mediator of the stress response in mice, necessary for stress-induced synaptic potentiation in the ventral hippocampus and for an increase in anxiety-like behaviour. Acute stress is sufficient to activate microglia, triggering the long-term release of TNF. Critically, on-going TNF signaling specifically in the ventral hippocampus is necessary to sustain both the stress-induced synaptic and behavioral changes, as these could be reversed hours after induction by antagonizing TNF signaling. This demonstrates that TNF maintains the synaptic and behavioral stress response in vivo, making TNF a potential novel therapeutic target for stress disorders.

Background The human CD19 antigen is expressed throughout B cell ontogeny with the exception of neoplastic plasma cells and a subset of normal plasma cells. CD19 plays a role in propagating signals from the B cell receptor and other receptors such as CXCR4 in mature B cells. Studies of CD19-deficient patients have confirmed its function during the initial stages of B cell activation and the production of memory B cells; however, its role in the later stages of B cell differentiation is unclear. Objective Using B cells from a newly identified CD19-deficient individual, we investigated the role of CD19 in the generation and function of plasma cells using an in vitro differentiation model. Methods Flow cytometry and long-read nanopore sequencing using locus-specific long-range amplification products were used to screen a patient with suspected primary immunodeficiency. Purified B cells from the patient and healthy controls were activated with CD40L, IL-21, IL-2, and anti-Ig, then transferred to different cytokine conditions to induce plasma cell differentiation. Subsequently, the cells were stimulated with CXCL12 to induce signalling through CXCR4. Phosphorylation of key downstream proteins including ERK and AKT was assessed by Western blotting. RNA-seq was also performed on in vitro differentiating cells. Results Long-read nanopore sequencing identified the homozygous pathogenic mutation c.622del (p.Ser208Profs*19) which was corroborated by the lack of CD19 cell surface staining. CD19-deficient B cells that are predominantly naïve generate phenotypically normal plasma cells with expected patterns of differentiation-associated genes and normal levels of CXCR4. Differentiated CD19-deficient cells were capable of responding to CXCL12; however, plasma cells derived from naïve B cells, both CD19-deficient and sufficient, had relatively diminished signaling compared to those generated from total B cells. Additionally, CD19 ligation on normal plasma cells results in AKT phosphorylation. Conclusion CD19 is not required for generation of antibody-secreting cells or the responses of these populations to CXCL12, but may alter the response other ligands that require CD19 potentially affecting localization, proliferation, or survival. The observed hypogammaglobulinemia in CD19-deficient individuals is therefore likely attributable to the lack of memory B cells.

Cardiovascular imaging studies provide a multitude of structural and functional data to better understand disease mechanisms. While pooling data across studies enables more powerful and broader applications, performing quantitative comparisons across datasets with varying acquisition or analysis methods is problematic due to inherent measurement biases specific to each protocol. We show how dynamic time warping and partial least squares regression can be applied to effectively map between left ventricular geometries derived from different imaging modalities and analysis protocols to account for such differences. To demonstrate this method, paired real-time 3D echocardiography (3DE) and cardiac magnetic resonance (CMR) sequences from 138 subjects were used to construct a mapping function between the two modalities to correct for biases in left ventricular clinical cardiac indices, as well as regional shape. Leave-one-out cross-validation revealed a significant reduction in mean bias, narrower limits of agreement, and higher intraclass correlation coefficients for all functional indices between CMR and 3DE geometries after spatiotemporal mapping. Meanwhile, average root mean squared errors between surface coordinates of 3DE and CMR geometries across the cardiac cycle decreased from 7 ± 1 to 4 ± 1 mm for the total study population. Our generalised method for mapping between time-varying cardiac geometries obtained using different acquisition and analysis protocols enables the pooling of data between modalities and the potential for smaller studies to leverage large population databases for quantitative comparisons.

Background Excessive gestational weight gain (GWG) predicts negative health outcomes among individuals with overweight or obesity. Loss of control eating (LOC), the ingestion of food associated with being unable to control eating, is the core psychopathology of binge eating disorders. We evaluated the contribution of LOC to GWG among pregnant individuals with prepregnancy overweight/obesity. Methods In a prospective longitudinal study, individuals with prepregnancy BMI ≥ 25 (N = 257) were interviewed monthly to assess LOC and reported demographic, parity, and smoking information. GWG was abstracted from medical records. Results Among individuals with prepregnancy overweight/obesity, 39% endorsed LOC prior to or during pregnancy. After adjusting for factors that have previously been linked to GWG, LOC during pregnancy, uniquely predicted higher GWG and greater likelihood of exceeding GWG recommendations. Participants with prenatal LOC gained 3.14 kg (p = 0.03) more than did those without LOC during pregnancy and 78.7% (n = 48/61) exceeded IOM guidelines for GWG. The frequency of LOC episodes was also associated with greater weight gain. Conclusions Prenatal LOC is common among pregnant individuals with overweight/obesity and predicts greater GWG and increased likelihood of exceeding IOM GWG guidelines. LOC may represent a modifiable behavioral mechanism to prevent excessive GWG among individuals at risk for adverse pregnancy outcomes.

The dynamical system described herein uses a hybrid cellular automata (CA) mechanism to attain reversibility, and this approach is adapted to create a novel block cipher algorithm called HCA. CA are widely used for modeling complex systems and employ an inherently parallel model. Therefore, applications derived from CA have a tendency to fit very well in the current computational paradigm where scalability and multi-threading potential are quite desirable characteristics. HCA model has recently received a patent by the Brazilian agency INPI. Several evaluations and analyses performed on the model are presented here, such as theoretical discussions related to its reversibility and an analysis based on graph theory, which reduces HCA security to the well-known Hamiltonian cycle problem that belongs to the NP-complete class. Finally, the cryptographic robustness of HCA is empirically evaluated through several tests, including avalanche property compliance and the NIST randomness suite., 34 pages, 12 figures

Herein, we studied the impact of empty LNP (eLNP), component of mRNA-based vaccine, on anti-viral pathways and immune function of cells from young and aged individuals. eLNP induced maturation of monocyte derived dendritic cells (MDDCs). We further show that eLNP upregulated CD40 and induced cytokine production in multiple DC subsets and monocytes. This coincided with phosphorylation of TANK binding kinase 1 (pTBK1) and interferon response factor 7 (pIRF7). In response to eLNP, healthy older adults (>65 yrs) have decreased CD40 expression, and IFN-γ output compared to young adults (

There is a continuing debate concerning “adjustments” to heart period variability [i.e., heart rate variability (HRV)] for the heart period [i.e., increases inter-beat-intervals (IBI)]. To date, such arguments have not seriously considered the impact a demographic variable, such as gender, can have on the association between HRV and the heart period. A prior meta-analysis showed women to have greater HRV compared to men despite having shorter IBI and higher heart rate (HR). Thus, it is plausible that men and women differ in the association between HRV and HR/IBI. Thus, the present study investigates the potential moderating effect of gender on the association between HRV and indices of cardiac chronotropy, including both HR and IBI. Data from 633 participants (339 women) were available for analysis. Cardiac measures were assessed during a 5-min baseline-resting period. HRV measures included the standard deviation of inter-beat-intervals, root mean square of successive differences, and autoregressive high frequency power. Moderation analyses showed gender significantly moderated the association between all HRV variables and both HR and IBI (each p

The aberrant production of collagen by fibroblasts is a hallmark of many solid tumours and can influence cancer progression. How the mesenchymal cells in the tumour microenvironment maintain their production of extracellular matrix proteins as the vascular delivery of glutamine and glucose becomes compromised remains unclear. Here we show that pyruvate carboxylase (PC)-mediated anaplerosis in tumour-associated fibroblasts contributes to tumour fibrosis and growth. Using cultured mesenchymal and cancer cells, as well as mouse allograft models, we provide evidence that extracellular lactate can be utilized by fibroblasts to maintain tricarboxylic acid (TCA) cycle anaplerosis and non-essential amino acid biosynthesis through PC activity. Furthermore, we show that fibroblast PC is required for collagen production in the tumour microenvironment. These results establish TCA cycle anaplerosis as a determinant of extracellular matrix collagen production, and identify PC as a potential target to inhibit tumour desmoplasia.

Objective During the COVID-19 pandemic, limitations on in-person medical school clerkships created a deficit in urologic learning opportunities. We sought to develop and evaluate a blended curriculum of interactive online modules with small-group discussion to enhance the educational experience for medical students in urology. Materials and Methods We created a curriculum of four online case-based urology modules. Between July and October 2020, 14 fourth-year medical students completed the modules. Students answered questions on a discussion board and engaged in asynchronous dialogue with 16 physicians, in addition to a weekly live review session. Students and physicians completed anonymous surveys to assess satisfaction and perceived learning outcomes, with questions scored on a 5-point Likert scale. Results Thirteen students (93% response rate) and 12 physicians (75% response rate) completed the survey. Overall, 12/13 students and 11/12 physicians “strongly agree” or “somewhat agree” that the modules improved the rotation. Students and physicians perceived that the modules were effective for learning/teaching foundational knowledge (average ratings 4.8 and 4.5, respectively) and facilitating performance assessment (4.4 and 4.0). Students reported high learning scores across multiple Accreditation Council for Graduate Medical Education core competencies, and 12/13 students found the modules fun/engaging. The majority of students (12/13) and physicians (10/12) felt that the online modules should be incorporated into future urology electives. Conclusions A blended learning curriculum utilizing online modules is an effective tool for enhancing urologic education, improving perceived learning outcomes and facilitating performance assessment. Supplementary Information The online version contains supplementary material available at 10.1007/s40670-021-01427-3.

Increasing rates of Anthropocene biodiversity extinctions suggest a possible sixth mass extinction event. Conservation planners are seeking effective ways to protect species, hotspots of biodiversity, and dynamic ecosystems to reduce and eventually eliminate the degradation and loss of diversity at the scale of genes, species, and ecosystems. While well-established, adequately enforced protected areas (PAs) increase the likelihood of preserving species and habitats, traditional placement methods are frequently inadequate in protecting biodiversity most at risk. Consequently, the Key Biodiversity Area (KBA) Partnership developed a set of science-based criteria and thresholds that iteratively identify sites where biodiversity is most in need of protection. KBA methodology has been rarely applied in the marine realm, where data are often extremely limited. We tested the feasibility of KBA population metrics in the Greater Caribbean marine region using occurrence and population data and threat statuses for 1669 marine vertebrates. These data identified areas where site-specific conservation measures can effectively protect biodiversity. Using KBA criteria pertaining to threatened and irreplaceable biodiversity, we identified 90 geographically unique potential KBAs, 34 outside and 56 within existing PAs. These provide starting points for local conservation managers to verify that KBA thresholds are met and to delineate site boundaries. Significant data gaps, such as population sizes, life history characteristics, and extent of habitats, prevent the full application of the KBA criteria to data-poor marine species. Increasing the rate and scope of marine sampling programs and digital availability of occurrence datasets will improve identification and delineation of KBAs in the marine environment.