Endothelial cells decode VEGF-mediated Ca2+ signaling patterns to produce distinct functional responses

A single extracellular stimulus can promote diverse behaviors among isogenic cells by differentially regulated signaling networks. We examined Ca(2+) signaling in response to VEGF (vascular endothelial growth factor), a growth factor that can stimulate different behaviors in endothelial cells. We found that altering the amount of VEGF signaling in endothelial cells by stimulating them with different VEGF concentrations triggered distinct and mutually exclusive dynamic Ca(2+) signaling responses that correlated with different cellular behaviors. These behaviors were cell proliferation involving the transcription factor NFAT (nuclear factor of activated T cells) and cell migration involving MLCK (myosin light chain kinase). Further analysis suggested that this signal decoding was robust to the noisy nature of the signal input. Using probabilistic modeling, we captured both the stochastic and deterministic aspects of Ca(2+) signal decoding and accurately predicted cell responses in VEGF gradients, which we used to simulate different amounts of VEGF signaling. Ca(2+) signaling patterns associated with proliferation and migration were detected during angiogenesis in developing zebrafish.

Energy reserve utilization in northern elephant seal (Mirounga angustirostris) pups during the postweaning fast: size does matter

During fasting most mammals preferentially utilize lipid reserves for energy while sparing protein reserves. This presents a potential problem for marine mammals that also depend on lipids as a major component of blubber, the primary thermoregulatory structure. Because of this dual function for lipid, rates of lipid and protein utilization should be closely regulated during the postweaning fast in northern elephant seals (Mirounga angustirostris). To quantify energy expenditure during the fast, we measured body mass and composition of 60 pups at 2.3+/-0.2 days and 55.9+/-0.3 days postweaning in 1999 and in 2000. Body condition differed significantly between years. At weaning, body mass (125.9+/-3.8 kg) and percentage lipid content (39.3+/-0.6% of body mass) in 2000 were significantly greater than body mass (115.2+/-3.1 kg) and percentage lipid content (35.8+/-0.6%) in 1999. In general, percentage lipid content increased with body mass, and fatter pups utilized lipid at relatively higher rates during the fast. Lipid fueled 85-95% and 88-98% of energy expended by pups in 1999 and 2000, respectively. Postweaning fast duration (32-78 days) was positively correlated with body mass and hence lipid content at weaning. This suggests that body composition at weaning influences lipid utilization patterns and ultimately the duration of the postweaning fast in northern elephant seal pups.

The diving physiology of bottlenose dolphins (Tursiops truncatus). III. Thermoregulation at depth

During diving, marine mammals initiate a series of cardiovascular changes that include bradycardia and decreased peripheral circulation. Because heat transfer from thermal windows located in peripheral sites of these mammals depends on blood flow, such adjustments may limit their thermoregulatory capabilities during submergence. Here, we demonstrate how the thermoregulatory responses of bottlenose dolphins (Tursiops truncatus) are coordinated with the diving response. Heart rate, skin temperature and heat transfer from the dorsal fin and flank were measured while dolphins rested on the water surface, stationed 5–50 m under water and floated at the surface immediately following a dive. The results showed that heat flow ranged from 42.9+/−7.3 to 126.2+/−23.1 W m(−)(2) and varied with anatomical site and diving activity. Upon submergence, heat flow declined by 35 % from the dorsal fin and by 24 % from the flank. An immediate increase in heat flow to levels exceeding pre-dive values occurred at both sites upon resurfacing. Changes in heart rate during diving paralleled the thermoregulatory responses. Mean pre-dive heart rate (102.0+/−2.6 beats min(−)(1), N=26) decreased by 63.4 % during dives to 50 m and immediately returned to near resting levels upon resurfacing. These studies indicate that heat dissipation by dolphins is attenuated during diving. Rather than challenge the diving response, heat transfer is delayed until post-dive periods when the need for oxygen conservation is reduced.

Thermoregulation during swimming and diving in bottlenose dolphins, Tursiops truncatus

Heat transfer from the periphery is in important thermoregulatory response in exercising mammals. However, when marine mammals submerge, peripheral vasoconstriction associated with the dive response may preclude heat dissipation at depth. To determine the effects of exercise and diving on thermoregulation in cetaceans, we measured heat flow and skin temperatures of bottlenose dolphins (Tursiops truncatus) trained to follow a boat and to dive to 15 m. The results demonstrated that skin temperatures usually remained within 1 degree C of the water after all exercise levels. Heat flow from peripheral sites (dorsal fin and flukes) increased over resting values immediately after exercise at the water surface and remained elevated for up to 20 min. However, post-exercise values for heat flow from the flukes and dorsal fin decreased by 30-67% when dolphins stationed at 15 m below the surface. The pattern in heat flow was reversed during ascent. For example, mean heat flow from the flukes measured at 5 m depth, 40.10 +/- 2.47 W.m-2, increased by 103.2% upon ascent. There is some flexibility in the balance between thermal and diving responses of dolphins. During high heat loads, heat transfer may momentarily increase during submergence. However, the majority of excess heat in dolphins appears to be dissipated upon resurfacing, thereby preserving the oxygen-conserving benefits of the dive response.

GH and ghrelin increase with fasting in a naturally adapted species, the northern elephant seal (Mirounga angustirostris)

After nursing, pups of the northern elephant seal (Mirounga angustirostris) are approximately 46% body fat and rely almost entirely on the oxidation of their large fat stores to sustain their metabolism for the ensuing 8-12 week postweaning fast, which is a natural component of their life history. Thus, fasting pups provide an ideal opportunity to examine the hormonal alterations associated with prolonged food deprivation in a naturally adapted model. Cortisol, ghrelin, glucagon, growth hormone (GH), insulin-like growth factor-I (IGF-I), insulin, blood urea nitrogen (BUN), glucose and non-esterified fatty acids (NEFA) were examined in 20 male and 20 female pups blood sampled early (<1 week postweaning) and late (6-8 weeks postweaning) during the fast. Mean cortisol, ghrelin, GH, and glucagon increased 1.8-, 1.8-, 1.4-, and 2.3-fold between early and late periods, while mean IGF-I and insulin decreased 97% and 38%, respectively. NEFA increased 2.3-fold, while BUN and glucose decreased 46% and 11%, respectively. NEFA was significantly and positively correlated with cortisol and GH; individually; however, when the relationship was examined as a multiple regression the correlation improved suggesting that cortisol and GH act synergistically to promote lipolysis during the fast. GH and BUN were negatively and significantly correlated between early and late fasting suggesting that GH may promote protein sparing as well. The decrease in glucose may be responsible for stimulating glucagon, resulting in the maintenance of relative hyperglycemia. The increases in cortisol, ghrelin, glucagon, and GH suggest that these hormones may be integral in mediating the metabolism of seal pups during prolonged fasting.

Analysis of pairwise cell interactions using an integrated dielectrophoretic-microfluidic system

Blood vessel formation, during either normal vascular reconstruction or pathogenic tumour formation, relies upon highly organized cell–cell interactions. Isolating the function of any particular component of this cell–cell communication is often difficult, given the vast complexity of communication networks in multicellular systems. One way to address this problem is to analyse cell–cell communication on the most elementary scale—cell pairs. Here, we describe an integrated dielectrophoretic (DEP)-microfluidic device allowing for such analysis. Single cancer and endothelial cells (ECs) and cell pairs were patterned using DEP force and cultured within a minimally stressful microfluidic channel network. Controlling both the initial cell positions and extracellular environment, we investigated cell motility in homo- and heterotypic cell pairs under diverse conditions. We found that secreted collagen IV and soluble vascular endothelial growth factor have considerable guidance effect on ECs at the level of two interacting cells. Cell interaction rules extracted from the experiments of cell pairs were used to mathematically predict branching patterns characteristic of developing multicellular blood vessels. This integrative analysis method can be extended to other systems involving complex multicellular interactions.

A new perspective on adiposity in a naturally obese mammal

Many mammals seasonally reduce body fat due to inherent periods of fasting, which is associated with decreased leptin concentrations. However, no data exist on the correlation between fat mass (FM) and circulating leptin in marine mammals, which have evolved large fat stores as part of their adaptation to periods of prolonged fasting. Therefore, FM was estimated (by tritiated water dilution), and serum leptin and cortisol were measured in 40 northern elephant seal (Mirounga angustirostris) pups early (<1 wk postweaning) and late (6-8 wk postweaning) during their natural, postweaning fast. Body mass (BM) and FM were reduced late; however, percent FM (early: 43.9 +/- 0.5, late: 45.5 +/- 0.5%) and leptin [early: 2.9 +/- 0.1 ng/ml human equivalents (HE), late: 3.0 +/- 0.1 ng/ml HE] did not change. Cortisol increased between early (9.2 +/- 0.5 microg/dl) and late (16.3 +/- 0.9 microg/dl) periods and was significantly and negatively correlated with BM (r = 0.426; P < 0.0001) and FM (r = 0.328; P = 0.003). FM and percent FM were not correlated (P > 0.10) with leptin at either period. The present study suggests that these naturally obese mammals appear to possess a novel cascade for regulating body fat that includes cortisol. The lack of a correlation between leptin and FM may reflect the different functions of fat between terrestrial and marine mammals.

Evolution-informed modeling improves outcome prediction for cancers

Despite wide applications of high-throughput biotechnologies in cancer research, many biomarkers discovered by exploring large-scale omics data do not provide satisfactory performance when used to predict cancer treatment outcomes. This problem is partly due to the overlooking of functional implications of molecular markers. Here, we present a novel computational method that uses evolutionary conservation as prior knowledge to discover bona fide biomarkers. Evolutionary selection at the molecular level is nature's test on functional consequences of genetic elements. By prioritizing genes that show significant statistical association and high functional impact, our new method reduces the chances of including spurious markers in the predictive model. When applied to predicting therapeutic responses for patients with acute myeloid leukemia and to predicting metastasis for patients with prostate cancers, the new method gave rise to evolution-informed models that enjoyed low complexity and high accuracy. The identified genetic markers also have significant implications in tumor progression and embrace potential drug targets. Because evolutionary conservation can be estimated as a gene-specific, position-specific, or allele-specific parameter on the nucleotide level and on the protein level, this new method can be extended to apply to miscellaneous "omics" data to accelerate biomarker discoveries.

Estradiol and Testosterone Concentrations Increase with Fasting in Weaned Pups of the Northern Elephant Seal (Mirounga angustirostris)

Although neonatal development is generally associated with increased levels of circulating testosterone (T) and estradiol (E2), food deprivation may inhibit steroidogenesis. Therefore, these potentially conflicting stimuli were examined in fasting weaned northern elephant seal (Mirounga angustirostris) pups by measuring serum concentrations of T, E2, progesterone (P4), and luteinizing hormone (LH) by either radioimmunoassay (P4, LH) or enzymeimmunoassay (T, E2). Blood samples were obtained from 20 male and 20 female pups at both early (<1 wk postweaning) and late (6-8 wk postweaning) periods during their natural postweaning fast. T in males (early: 2.9 +/- 0.4 ng/mL; late: 16 +/- 2 ng/mL; P < 0.0001) and E2 in females (early: 42 +/- 6 pg/mL; late: 67 +/- 5 pg/mL; P < 0.01) increased between the two measurement periods, while P4 (early: 2.5 +/- 0.3 ng/mL; late: 2.1 +/- 0.3 ng/mL; P > 0.05) did not. LH increased (early: 46 +/- 4 pg/mL; late: 65 +/- 6 pg/mL; P < 0.05) in males but not in females (early: 69 +/- 9 pg/mL; late: 65 +/- 6 pg/mL; P > 0.05). Increases in LH and T suggest that LH may stimulate T secretion. Alternatively, relatively low concentrations of LH in both males and females may reflect negative feedback inhibition imposed by elevated T and E2 concentrations. Despite the inherent postweaning fast, concentrations of T and E2 increased, suggesting that they may be critical for the continued development of pups. Therefore, compensatory mechanisms may exist that alleviate the fasting-induced inhibition of gonadal steroidogenesis during neonatal development in elephant seal pups.

A Retrospective Cohort Study of Clinical Factors Associated with Transitions of Care among COVID-19 Patients

Coronavirus Disease 2019 (COVID-19) is an international health crisis. In this article, we report on patient characteristics associated with care transitions of: 1) hospital admission from the emergency department (ED) and 2) escalation to the intensive care unit (ICU). Analysis of data from the electronic medical record (EMR) was performed for patients with COVID-19 seen in the ED of a large Western U.S. Health System from April to August of 2020, totaling 10,079 encounters. Of these, 5172 resulted in admission as an inpatient within 72 h. Inpatient encounters (n = 6079) were also considered for patients with positive COVID-19 test results, of which 970 resulted in a transfer to the ICU or in-hospital mortality. Laboratory results, vital signs, symptoms, and comorbidities were investigated for each of these care transitions. Different top risk factors were found, but two factors common to hospital admission and ICU transfer were respiratory rate and the need for oxygen support. Comorbidities common to both settings were cerebrovascular disease and congestive heart failure. Regarding laboratory results, the neutrophil-to-lymphocyte ratio was associated with transitions to higher levels of care, along with the ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT).

Interpretable Identification of Comorbidities Associated with Recurrent ED and Inpatient Visits

In the hospital setting, a small percentage of recurrent frequent patients contribute to a disproportional amount of healthcare resource utilization. Moreover, in many of these cases, patient outcomes can be greatly improved by reducing re-occurring visits, especially when they are associated with substance abuse, mental health, and medical factors that could be improved by social-behavioral interventions, outpatient or preventative care. Additionally, health care costs can be reduced significantly with fewer preventable recurrent visits. To address this, we developed a novel, interpretable framework that both identifies recurrent patients with high utilization and determines which comorbidities contribute most to their recurrent visits. Specifically, we present a novel algorithm, called the minimum similarity association rules (MSAR), which balances the confidence-support trade-off, to determine the conditions most associated with re-occurring Emergency department and inpatient visits. We validate MSAR on a large Electronic Health Record dataset, demonstrating the effectiveness and consistency in ability to find low-support comorbidities with high likelihood of being associated with recurrent visits, which is challenging for other algorithms such as XGBoost. Clinical relevance- In the era of value-based care and population health management, the proposal could be used for decision making to help reduce future recurrent admissions, improve patient outcomes and reduce the cost of healthcare.

Leveraging observational and prospective data to develop an opioid exposure detection model

Experimental studies are widely considered as the gold standard for discovering new evidence. However, advances in computational science provide an opportunity to take advantage of large clinical datasets in cases where randomized experiments are not practical. In this study, we used a large clinical database to train a model capable of detecting exposure to opioid medication (AUROC=0.76). We designed and implemented a clinical study to measure the performance of the model against the unseen data from the study. Our results show that the model based on hospital patient data exhibited promising performance against the retrospective clinical study data (AUROC=0.68).

Predicted wall shear rate gradients in T-type arteriolar bifurcations

The purpose of this study was to examine the theoretical impact of the local bifurcation geometry on the shear rate gradient in a divergent arteriolar-type bifurcation. Newtonian flow through an arteriolar bifurcation was modeled using 3-dimensional computational fluid dynamics (CFD). Branching angles of 30 degrees, 50 degrees, 70 degrees, 90 degrees, 110 degrees, 130 degrees, and 150 degrees were studied at a Reynolds number (Re) of 0.01 in seven separate models. Both the flow split (30%) and the branch to main vessel diameter ratio (4/5) were held constant. Velocity profiles were predicted to deviate significantly from a parabolic form, both immediately before and after the branch. This deviation was shown to be a function of the local bifurcation geometry of each model, which consisted of a branching angle and associated feed-branch intersection shape. Immediately before and after the branch, the shear rate along the lateral branching wall was predicted to exceed (5-fold) that calculated for fully developed flow in the feed. In vivo data were from the anesthetized (pentobarbital, 70 mg/kg) hamster cremaster muscle preparation. Red blood cells were used as flow markers in arteriolar branch points (n = 74) show that a significant gradient in shear rate occurs at the locations and branch shapes predicted by the computational model. Thus, for low Re divergent flow, the gradient in shear rate measured for non-Newtonian conditions, is approximated by a finite element fluid dynamics model of Newtonian flow.

Machine learning-based clinical decision support for infection risk prediction

Background

Healthcare-associated infection (HAI) remains a significant risk for hospitalized patients and a challenging burden for the healthcare system. This study presents a clinical decision support tool that can be used in clinical workflows to proactively engage secondary assessments of pre-symptomatic and at-risk infection patients, thereby enabling earlier diagnosis and treatment.

Methods

This study applies machine learning, specifically ensemble-based boosted decision trees, on large retrospective hospital datasets to develop an infection risk score that predicts infection before obvious symptoms present. We extracted a stratified machine learning dataset of 36,782 healthcare-associated infection patients. The model leveraged vital signs, laboratory measurements and demographics to predict HAI before clinical suspicion, defined as the order of a microbiology test or administration of antibiotics.

Results

Our best performing infection risk model achieves a cross-validated AUC of 0.88 at 1 h before clinical suspicion and maintains an AUC >0.85 for 48 h before suspicion by aggregating information across demographics and a set of 163 vital signs and laboratory measurements. A second model trained on a reduced feature space comprising demographics and the 36 most frequently measured vital signs and laboratory measurements can still achieve an AUC of 0.86 at 1 h before clinical suspicion. These results compare favorably against using temperature alone and clinical rules such as the quick sequential organ failure assessment (qSOFA) score. Along with the performance results, we also provide an analysis of model interpretability via feature importance rankings.

Conclusion

The predictive model aggregates information from multiple physiological parameters such as vital signs and laboratory measurements to provide a continuous risk score of infection that can be deployed in hospitals to provide advance warning of patient deterioration.