Migration against the direction of flow is LFA-1-dependent in human hematopoietic stem and progenitor cells.

The recruitment of immune cells during inflammation is regulated by a multi-step cascade of cell rolling, activation, adhesion and transmigration through the endothelial barrier. Similarly, hematopoietic stem and progenitor cells (HSPCs) use this pathway to migrate and home to the bone marrow. After selectin-mediated braking, HSPCs migrate on adhesion ligands presented by the vascular endothelium including ICAM-1, VCAM-1 or MAdCAM-1. Here, we report that both the KG1a stem cell line and primary bone marrow CD34+ HSPCs can migrate against the direction of fluid flow on surfaces coated with cell adhesion molecules (CAMs), a behavior thus far only reported in T lymphocytes. We demonstrate that KG1a cells and primary HSPCs migrate upstream on surfaces presenting ICAM-1, downstream on surfaces presenting VCAM-1, and both upstream and downstream on surfaces presenting MAdCAM-1. In addition, we demonstrate that KG1a cells and HSPCs display upstream migration both on surfaces with multiple CAMs, as well as on human umbilical vein endothelial cell (HUVEC) monolayers. By blocking with monoclonal antibodies, we show that lymphocyte function-associated antigen-1 (LFA-1) is the key receptor responsible for upstream migration on the endothelium during the trafficking of HSPCs to the bone marrow.This article has an associated First Person interview with the first author of the paper.

A simulation of the random and directed motion of dendritic cells in chemokine fields.

Dendritic cells (DCs) are the most effective professional antigen-presenting cell. They ferry antigen from the extremities to T cells and are essential for the initiation of an adaptive immune response. Despite interest in how DCs respond to chemical stimuli, there have been few attempts to model DC migration. In this paper, we simulate the motility of DCs by modeling the generation of forces by filopodia and a force balance on the cell. The direction of fliopodial extension is coupled to differential occupancy of cognate chemokine receptors across the cell. Our model simulates chemokinesis and chemotaxis in a variety of chemical and mechanical environments. Simulated DCs undergoing chemokinesis were measured to have a speed of 5.1 ± 0.07 µm·min-1 and a persistence time of 3.2 ± 0.46 min, consistent with experiment. Cells undergoing chemotaxis exhibited a stronger chemotactic response when exposed to lower average chemokine concentrations, also consistent with experiment. We predicted that when placed in two opposing gradients, cells will cluster in a line, which we call the "line of equistimulation;" this clustering has also been observed. We calculated the effect of varying gradient steepness on the line of equistimulation, with steeper gradients resulting in tighter clustering. Moreover, gradients are found to be most potent when cells are in a gradient of chemokine whose mean concentration is close to the binding of the Kd to the receptor, and least potent when the mean concentration is 0.1Kd. Comparing our simulations to experiment, we can give a quantitative measure of the strength of certain chemokines relative to others. Assigning the signal of CCL19 binding CCR7 a baseline strength of 1, we found CCL21 binding CCR7 had a strength of 0.28, and CXCL12 binding CXCR4 had a strength of 0.30. These differences emerge despite both chemokines having virtually the same Kd, suggesting a mechanism of signal amplification in DCs requiring further study.

Leveraging IoTs and Machine Learning for Patient Diagnosis and Ventilation Management in the Intensive Care Unit.

Future healthcare systems will rely heavily on clinical decision support systems (CDSS) to improve the decision-making processes of clinicians. To explore the design of future CDSS, we developed a research-focused CDSS for the management of patients in the intensive care unit that leverages Internet of Things (IoT) devices capable of collecting streaming physiologic data from ventilators and other medical devices. We then created machine learning (ML) models that could analyze the collected physiologic data to determine if the ventilator was delivering potentially harmful therapy and if a deadly respiratory condition, acute respiratory distress syndrome (ARDS), was present. We also present work to aggregate these models into a mobile application that can provide responsive, real-time alerts of changes in ventilation to providers. As illustrated in the recent COVID-19 pandemic, being able to accurately predict ARDS in newly infected patients can assist in prioritizing care. We show that CDSS may be used to analyze physiologic data for clinical event recognition and automated diagnosis, and we also highlight future research avenues for hospital CDSS.

Human Neutrophils Will Crawl Upstream on ICAM-1 If Mac-1 Is Blocked.

The recruitment of neutrophils to sites of inflammatory insult is a hallmark of the innate immune response. Neutrophil recruitment is regulated by a multistep process that includes cell rolling, activation, adhesion, and transmigration through the endothelium commonly referred to as the leukocyte adhesion cascade. After selectin-mediated braking, neutrophils migrate along the activated vascular endothelium on which ligands, including intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), are expressed. Previous studies have shown that two cells that commonly home from blood vessel to tissue-T cells and hematopoietic stem and progenitor cells-use the integrin lymphocyte functional antigen-1 (LFA-1) to migrate against the direction of shear flow once adherent on ICAM-1 surfaces. Like T cells and hematopoietic stem and progenitor cells, neutrophils express LFA-1, but they also express macrophage-1 antigen (Mac-1), which binds to ICAM-1. Previous reports have shown that neutrophils will not migrate against the direction of flow on ICAM-1, but we hypothesized this was due to the influence of Mac-1. Here, we report that both the HL-60 neutrophil-like cell line and primary human neutrophils can migrate against the direction of fluid flow on ICAM-1 surfaces via LFA-1 if Mac-1 is blocked; otherwise, they migrate downstream. We demonstrate this both on ICAM-1 surfaces and on activated endothelium. In sum, both LFA-1 and Mac-1 binding ICAM-1 play a critical role in determining the direction of neutrophil migration along the endothelium, and their interaction may play an important role in controlling neutrophil trafficking during inflammation.

Exploration of Fermi-Pasta-Ulam Behavior in a Magnetic System.

We study nonlinear spin motion in one-dimensional magnetic chains. We find significant differences from the classic Fermi-Pasta-Ulam (FPU) problem examining nonlinear elastic motion in a chain. We find that FPU behavior, the transfer of energy among low order eigenmodes, does not occur in magnetic systems with only exchange and external fields, but does exist if a uniaxial anisotropy is also present. The FPU behavior may be altered or turned off through the magnitude and orientation of an external magnetic field. A realistic micromagnetic model shows such behavior could be measurable.

Supplemented αMEM/F12-based medium enables the survival and growth of primary ovarian follicles encapsulated in alginate hydrogels.

Hydrogel-encapsulating culture systems for ovarian follicles support the in vitro growth of secondary follicles from various species including mouse, non-primate human, and human; however, the growth of early stage follicles (primary and primordial) has been limited. While encapsulation maintains the structure of early stage follicles, feeder cell populations, such as mouse embryonic fibroblasts (MEFs), are required to stimulate growth and development. Hence, in this report, we investigated feeder-free culture environments for early stage follicle development. Mouse ovarian follicles were encapsulated within alginate hydrogels and cultured in various growth medium formulations. Initial studies employed embryonic stem cell medium formulations as a tool to identify factors that influence the survival, growth, and meiotic competence of early stage follicles. The medium formulation that maximized survival and growth was identified as αMEM/F12 supplemented with fetuin, insulin, transferrin, selenium, and follicle stimulating hormone (FSH). This medium stimulated the growth of late primary (average initial diameter of 80 µm) and early secondary (average initial diameter of 90 µm) follicles, which developed antral cavities and increased to terminal diameters exceeding 300 µm in 14 days. Survival ranged from 18% for 80 µm follicles to 36% for 90 µm follicles. Furthermore, 80% of the oocytes from surviving follicles with an initial diameter of 90-100 µm underwent germinal vesicle breakdown (GVBD), and the percentage of metaphase II (MII) eggs was 50%. Follicle/oocyte growth and GVBD/MII rates were not significantly different from MEF co-culture. Survival was reduced relative to MEF co-culture, yet substantially increased relative to the control medium that had been previously used for secondary follicles. Continued development of culture medium could enable mechanistic studies of early stage folliculogenesis and emerging strategies for fertility preservation.

Not all (cells) who wander are lost: Upstream migration as a pervasive mode of amoeboid cell motility.

Leukocytes possess the ability to migrate upstream-against the direction of flow-on surfaces of specific chemistry. Upstream migration was first characterized in vitro for T-cells on surfaces comprised of intracellular adhesion molecule-1 (ICAM-1). Upstream migration occurs when the integrin receptor αLß2 (also known as lymphocyte function-associated antigen-1, or LFA-1) binds to ICAM-1. LFA-1/ICAM-1 interactions are ubiquitous and are widely found in leukocyte trafficking. Upstream migration would be employed after cells come to arrest on the apical surface of the endothelium and might confer an advantage for both trans-endothelial migration and tissue surveillance. It has now been shown that several other motile amoeboid cells which have the responsibility of trafficking from blood vessels into tissues, such as Marginal zone B cells, hematopoietic stem cells, and neutrophils (when macrophage-1 antigen, Mac-1, is blocked), can also migrate upstream on ICAM-1 surfaces. This review will summarize what is known about the basic mechanisms of upstream migration, which cells have displayed this phenomenon, and the possible role of upstream migration in physiology and tissue homeostasis.

Microenvironmental CXCL12 deletion enhances Flt3-ITD acute myeloid leukemia stem cell response to therapy by reducing p38 MAPK signaling.

Fms-like tyrosine kinase 3 (Flt3) tyrosine kinase inhibitors (Flt3-TKI) have improved outcomes for patients with Flt3-mutated acute myeloid leukemia (AML) but are limited by resistance and relapse, indicating persistence of leukemia stem cells (LSC). Here utilizing a Flt3-internal tandem duplication (Flt3-ITD) and Tet2-deleted AML genetic mouse model we determined that FLT3-ITD AML LSC were enriched within the primitive ST-HSC population. FLT3-ITD LSC showed increased expression of the CXCL12 receptor CXCR4. CXCL12-abundant reticular (CAR) cells were increased in Flt3-ITD AML marrow. CXCL12 deletion from the microenvironment enhanced targeting of AML cells by Flt3-TKI plus chemotherapy treatment, including enhanced LSC targeting. Both treatment and CXCL12 deletion partially reduced p38 mitogen-activated protein kinase (p38) signaling in AML cells and further reduction was seen after treatment in CXCL12 deleted mice. p38 inhibition reduced CXCL12-dependent and -independent maintenance of both murine and human Flt3-ITD AML LSC by MSC and enhanced their sensitivity to treatment. p38 inhibition in combination with chemotherapy plus TKI treatment leads to greater depletion of Flt3-ITD AML LSC compared with CXCL12 deletion. Our studies support roles for CXCL12 and p38 signaling in microenvironmental protection of AML LSC and provide a rationale for inhibiting p38 signaling to enhance Flt3-ITD AML targeting.

Electrocorticographic (ECoG) correlates of human arm movements.

Invasive and non-invasive brain-computer interface (BCI) studies have long focused on the motor cortex for kinematic control of artificial devices. Most of these studies have used single-neuron recordings or electroencephalography (EEG). Electrocorticography (ECoG) is a relatively new recording modality in BCI research that has primarily been built on successes in EEG recordings. We built on prior experiments related to single-neuron recording and quantitatively compare the extent to which different brain regions reflect kinematic tuning parameters of hand speed, direction, and velocity in both a reaching and tracing task in humans. Hand and arm movement experiments using ECoG have shown positive results before, but the tasks were not designed to tease out which kinematics are encoded. In non-human primates, the relationships among these kinematics have been more carefully documented, and we sought to begin elucidating that relationship in humans using ECoG. The largest modulation in ECoG activity for direction, speed, and velocity representation was found in the primary motor cortex. We also found consistent cosine tuning across both tasks, to hand direction and velocity in the high gamma band (70-160 Hz). Thus, the results of this study clarify the neural substrates involved in encoding aspects of motor preparation and execution and confirm the important role of the motor cortex in BCI applications.

Technical desiderata for the integration of genomic data into Electronic Health Records.

The era of "Personalized Medicine," guided by individual molecular variation in DNA, RNA, expressed proteins and other forms of high volume molecular data brings new requirements and challenges to the design and implementation of Electronic Health Records (EHRs). In this article we describe the characteristics of biomolecular data that differentiate it from other classes of data commonly found in EHRs, enumerate a set of technical desiderata for its management in healthcare settings, and offer a candidate technical approach to its compact and efficient representation in operational systems.

Autophagy inhibition impairs leukemia stem cell function in FLT3-ITD AML but has antagonistic interactions with tyrosine kinase inhibition.

The FLT3-ITD mutation is associated with poor prognosis in acute myeloid leukemia (AML). FLT3 tyrosine kinase inhibitors (TKIs) demonstrate clinical efficacy but fail to target leukemia stem cells (LSC) and do not generate sustained responses. Autophagy is an important cellular stress response contributing to hematopoietic stem cells (HSC) maintenance and promoting leukemia development. Here we investigated the role of autophagy in regulating FLT3-ITD AML stem cell function and response to TKI treatment. We show that autophagy inhibition reduced quiescence and depleted repopulating potential of FLT3-ITD AML LSC, associated with mitochondrial accumulation and increased oxidative phosphorylation. However, TKI treatment reduced mitochondrial respiration and unexpectedly antagonized the effects of autophagy inhibition on LSC attrition. We further show that TKI-mediated targeting of AML LSC and committed progenitors was p53-dependent, and that autophagy inhibition enhanced p53 activity and increased TKI-mediated targeting of AML progenitors, but decreased p53 activity in LSC and reduced TKI-mediated LSC inhibition. These results provide new insights into the role of autophagy in differentially regulating AML stem and progenitor cells, reveal unexpected antagonistic effects of combined oncogenic tyrosine kinase inhibition and autophagy inhibition in AML LSC, and suggest an alternative approach to target AML LSC quiescence and regenerative potential.

Macrophage-Based Approaches for Cancer Immunotherapy.

Adoptive cell therapy with genetically modified T cells has generated exciting outcomes in hematologic malignancies, but its application to solid tumors has proven challenging. This gap has spurred the investigation of alternative immune cells as therapeutics. Macrophages are potent immune effector cells whose functional plasticity leads to antitumor as well as protumor function in different settings, and this plasticity has led to notable efforts to deplete or repolarize tumor-associated macrophages. Alternatively, macrophages could be adoptively transferred after ex vivo genetic modification. In this review, we highlight the role of macrophages in solid tumors, the progress made with macrophage-focused immunotherapeutic modalities, and the emergence of chimeric antigen receptor macrophage cell therapy.

Simulating the Self-Assembly and Hysteresis Loops of Ferromagnetic Nanoparticles with Sticking of Ligands.

The agglomeration of ferromagnetic nanoparticles in a fluid is studied using nanoparticle-level Langevin dynamics simulations. The simulations have interdigitation and bridging between ligand coatings included using a computationally-cheap, phenomenological sticking parameter c. The interactions between ligand coatings are shown in this preliminary study to be important in determining the shapes of agglomerates that form. A critical size for the sticking parameter is estimated analytically and via the simulations and indicates where particle agglomerates transition from well-ordered (c is small) to disordered (c is large) shapes. Results are also presented for the hysteresis loops (magnetization versus applied field) for these particle systems in an oscillating magnetic field appropriate for hyperthermia applications. The results show that the clumping of particles has a significant effect on their macroscopic properties, with important consequences on applications. In particular, the work done by an oscillating field on the system has a nonmonotonic dependence on c.

Standardisation, multi-measure, data quality and trending: A qualitative study on multidisciplinary perspectives to improve intensive care early mobility monitoring.

OBJECTIVE: To explore multi-clinician perspectives on intensive care early mobility, monitoring and to assess the perceived value of technology-generated mobility metrics to provide user feedback to inform research, practice improvement, and technology development. METHODS: We performed a qualitative descriptive study. Three focus groups were conducted with critical care clinicians, including nurses (n = 10), physical therapists (n = 8) and physicians (n = 8) at an academic medical centre that implemented an intensive care early mobility programme in 2012. Qualitative thematic analysis was used to code transcripts and identify overarching themes. FINDINGS: Along with reaffirming the value of performing early mobility interventions, four themes for improving mobility monitoring emerged, including the need for: 1) standardised indicators for documenting mobility; 2) inclusion of both quantitative and qualitative metrics to measure mobility 3) a balance between quantity and quality of data; and 4) trending mobility metrics over time. CONCLUSION: Intensive care mobility monitoring should be standardised and data generated should be high quality, capable of supporting trend analysis, and meaningful. By improving measurement and monitoring of mobility, future researchers can examine the arc of activity that patients in the intensive care unit undergo and develop models to understand factors that influence successful implementation.

Use of Machine Learning to Screen for Acute Respiratory Distress Syndrome Using Raw Ventilator Waveform Data.

To develop and characterize a machine learning algorithm to discriminate acute respiratory distress syndrome from other causes of respiratory failure using only ventilator waveform data. DESIGN: Retrospective, observational cohort study. SETTING: Academic medical center ICU. PATIENTS: Adults admitted to the ICU requiring invasive mechanical ventilation, including 50 patients with acute respiratory distress syndrome and 50 patients with primary indications for mechanical ventilation other than hypoxemic respiratory failure. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Pressure and flow time series data from mechanical ventilation during the first 24-hours after meeting acute respiratory distress syndrome criteria (or first 24-hr of mechanical ventilation for non-acute respiratory distress syndrome patients) were processed to extract nine physiologic features. A random forest machine learning algorithm was trained to discriminate between the patients with and without acute respiratory distress syndrome. Model performance was assessed using the area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, and negative predictive value. Analyses examined performance when the model was trained using data from the first 24 hours and tested using withheld data from either the first 24 hours (24/24 model) or 6 hours (24/6 model). Area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, and negative predictive value were 0.88, 0.90, 0.71, 0.77, and 0.90 (24/24); and 0.89, 0.90, 0.75, 0.83, and 0.83 (24/6). CONCLUSIONS: Use of machine learning and physiologic information derived from raw ventilator waveform data may enable acute respiratory distress syndrome screening at early time points after intubation. This approach, combined with traditional diagnostic criteria, could improve timely acute respiratory distress syndrome recognition and enable automated clinical decision support, especially in settings with limited availability of conventional diagnostic tests and electronic health records.

Brain computer interface (BCI) tools developed in a clinical environment.

Brain computer interfaces are devices that collect signals from a subject's cortical surface and interpret these signals to control a computer Recently much development has been done on these devices with the help of epilepsy patients and the clinical staff who treat these patients. The types of data collected from epilepsy patients, particularly the invasive data give a unique opportunity to researchers in this area. The clinical staff has a unique opportunity to use the treatment of one patient population to help another

Modeling Clinical Processes to Consent Research Donors of Remnant Biospecimens in an Outpatient Cardiology Clinic.

Introduction: Informed consent for research biospecimen donations is traditionally obtained through a face-to-face interaction with research staff and by signing an Institutional Review Board (IRB)-approved printed form. Electronic signatures (eSign) are routinely used in the electronic medical record (EMR) for the consenting of clinical services after patients review printed documentation. Our goal was to develop an electronic self-consenting workflow that mimicked clinical services. Specifically, we tested a research consent process for the biobanking of remnant clinical samples that relies solely on clinical resources in a busy outpatient practice. Materials and Methods: The Biorepositories Core Resource (BCR) unit initiated a new enterprise-wide biobanking infrastructure for consenting patients, termed Biospecimen Use for Research-Related Investigations and Translational Objectives (BURRITO). BURRITO is modeled after an established clinical process called Terms and Conditions of Service (TACOS). The TACOS requires patients to annually review printed documentation and self-consent electronically for clinical services. BURRITO also requires patients to review printed documentation and self-consent with eSign to opt-in for remnant biospecimen banking, but patients must complete this process only once. We captured eSign for consents directly into the EMR without research staff. Results: Patients reviewed the IRB-approved documents and self-consented during their cardiology clinic visit. At checkout, their participation preferences were electronically documented by clinic staff. During a 6-month period, 123 patients agreed to donate. After a review of process, a second 3-month period identified 202 patients agreeing to donate. BURRITO did not require face-to-face interactions with research staff, used a "no-paper" eSign for consent, and created discrete fields in the clinical EMR of the patient's preference. Conclusions: BURRITO electronically documents informed consent using an EMR functionality and the least amount of clinical and research resources. Our results show promise for developing institutionally adopted processes, which could leverage existing clinical workflows for universal research consenting and scalability.

Human chimeric antigen receptor macrophages for cancer immunotherapy.

Chimeric antigen receptor (CAR) T cell therapy has shown promise in hematologic malignancies, but its application to solid tumors has been challenging1-4. Given the unique effector functions of macrophages and their capacity to penetrate tumors5, we genetically engineered human macrophages with CARs to direct their phagocytic activity against tumors. We found that a chimeric adenoviral vector overcame the inherent resistance of primary human macrophages to genetic manipulation and imparted a sustained pro-inflammatory (M1) phenotype. CAR macrophages (CAR-Ms) demonstrated antigen-specific phagocytosis and tumor clearance in vitro. In two solid tumor xenograft mouse models, a single infusion of human CAR-Ms decreased tumor burden and prolonged overall survival. Characterization of CAR-M activity showed that CAR-Ms expressed pro-inflammatory cytokines and chemokines, converted bystander M2 macrophages to M1, upregulated antigen presentation machinery, recruited and presented antigen to T cells and resisted the effects of immunosuppressive cytokines. In humanized mouse models, CAR-Ms were further shown to induce a pro-inflammatory tumor microenvironment and boost anti-tumor T cell activity.

Adhesive dynamics simulations quantitatively predict effects of kindlin-3 deficiency on T-cell homing.

Leukocyte adhesion is important for the proper functioning of the immune system. While leukocyte homing is mediated by adhesion receptors, the activation of these receptors is modulated by intracellular signaling molecules. In Leukocyte Adhesion Deficiency Type 3, the loss of the kindlin-3 prevents the activation of Leukocyte Function-associated Antigen-1 (LFA-1), which leads to a defect in adhesion, causing recurrent infections and bleeding disorders. Here, we use Integrated Signaling Adhesive Dynamics, a computer model of leukocyte rolling and adhesion combined with a simulated intracellular signaling cascade, to predict the response of T cells to depletion of kindlin-3. Our model predicts that cell adhesion is hypersensitive to the amount of kindlin-3 in the cell, while the rolling velocity is independent of kindlin-3 concentration. In addition, our simulation predicted that the time to stop, an important metric of adhesion, would increase with decreasing kindlin-3 expression. These predictions were confirmed experimentally in experiments using Jurkat cells with reduced expression of kindlin-3. These results suggest that Adhesive Dynamics is a versatile tool for quantifying adhesion in the immune response and predicting the effects of engineering cellular components.