Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “PrO”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

Statistical Properties of Rainfall in Tasmania (SPORT) Field Campaign Report

The objective of this project is to complement the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility second ARM Mobile Facility (AMF2) deployment at kennaook-Cape Grim (CAPE-k) with a micro-rain radar (MRR-PRO) mounted on top of one of the ARM containers. This was done to locate the MRR-PRO close to the ARM cloud radars (Ka-band ARM Zenith Radar [KAZR] and Marine W-band ARM Cloud Radar [MWACR]). This will allow for a continuous calibration check of the ARM cloud radars against the MRR-PRO and Parsivel-2 disdrometers. Scientifically, it will add one radar frequency to the analysis of vertical profiles of cloud and precipitation properties (K-band).

54 ENVIRONMENTAL SCIENCES↗

Polyunsaturated Fatty Acids Mend Macrophage Transcriptome, Glycome, and Phenotype in the Patients with Neurodegenerative Diseases, Including Alzheimer’s Disease

Macrophages of healthy subjects have a pro-resolution phenotype, upload amyloid-β (Aβ) into endosomes, and degrade Aβ, whereas macrophages of patients with Alzheimer’s disease (AD) generally have a pro-inflammatory phenotype and lack energy for brain clearance of Aβ. To clarify the pathogenesis of sporadic AD and therapeutic effects of polyunsaturated fatty acids (PUFA) with vitamins B and D and antioxidants on monocyte/macrophage (MM) migration in the AD brain, MM transcripts in energy and Aβ degradation, MM glycome, and macrophage clearance of Aβ. We followed for 31.3 months (mean) ten PUFA-supplemented neurodegenerative patients: 3 with subjective cognitive impairment (SCI), 2 with mild cognitive impairment (MCI), 3 MCI/vascular cognitive impairment, 2 with dementia with Lewy bodies, and 7 non-supplemented caregivers. We examined: monocyte migration in the brain and a blood-brain barrier model by immunochemistry and electron microscopy; macrophage transcriptome by RNAseq; macrophage glycome by N-glycan profiling and LTQ-Orbitrap mass spectrometry; and macrophage phenotype and phagocytosis by immunofluorescence. MM invade Aβ plaques, upload but do not degrade Aβ, and release Aβ into vessels, which develop cerebrovascular amyloid angiopathy (CAA); PUFA upregulate energy and Aβ degradation enzyme transcripts in macrophages; PUFA enhance sialylated N-glycans in macrophages; PUFA reduce oxidative stress and increase pro-resolution MM phenotype, mitochondrial membrane potential, and Aβ phagocytosis (p < 0.001). Macrophages of SCI, MCI, and AD patients have interrelated defects in the transcriptome, glycome, Aβ phagocytosis, and Aβ degradation. PUFA mend macrophage transcriptome, enrich glycome, enhance Aβ clearance, and benefit the cognition of early-stage AD patients.

60 APPLIED LIFE SCIENCES↗

Structures of HIV-1 Neutralizing Antibody 10E8 Delineate the Mechanistic Basis of Its Multi-Peak Behavior on Size-Exclusion Chromatography

Antibody 10E8 is capable of effectively neutralizing HIV through its recognition of the membrane-proximal external region (MPER), and a suitably optimized version of 10E8 might have utility in HIV therapy and prophylaxis. However, 10E8 displays a three-peak profile on size-exclusion chromatography (SEC), complicating its manufacture. Here we show cis-trans conformational isomerization of the Tyr-Pro-Pro (YPP) motif in the heavy chain 3rd complementarity-determining region (CDR H3) of antibody 10E8 to be the mechanistic basis of its multipeak behavior. We observed 10E8 to undergo slow conformational isomerization and delineate a mechanistic explanation for effective comodifiers that were able to resolve its SEC heterogeneity and to allow an evaluation of the critical quality attribute of aggregation. We determined crystal structures of single and double alanine mutants of a key di-proline motif and of a light chain variant, revealing alternative conformations of the CDR H3. We also replicated both multi-peak and delayed SEC behavior with MPER-antibodies 4E10 and VRC42, by introducing a Tyr-Pro (YP) motif into their CDR H3s. Our results show how a conformationally dynamic CDR H3 can provide the requisite structural plasticity needed for a highly hydrophobic paratope to recognize its membrane-proximal epitope.

60 APPLIED LIFE SCIENCES↗

DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS Campaigns at the Teller 27 Field Site from 2017 and 2018, Seward Peninsula, Alaska

A Digital Elevation Model (DEM) and Digital Surface Model (DSM) were derived from airborne Light Detection and Ranging (LiDAR) data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) quadcopter and hexacopter platforms operated by Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) scientists from the EES-14 group at LANL. These data were collected in August 2017 and July 2018 at the NGEE Arctic field site near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway between Nome, Alaska and Teller, Alaska. A Vulcan Raven X8 Airframe (Mitcheldean, Gloucestershire, UK), DJI Matrice 600 Pro Airframe (Shenzhen, China), and Routescene UAV LiDARSystem (Edinburgh, Scotland, UK) were used to collect LiDAR data. Following pre-processing in Routescene LidarViewer Pro software, the LiDAR point clouds were cleaned and processed using CloudCompare software to separate ground and off-ground points. A high resolution DEM and DSM were then created using ArcGIS Pro software. This data package contains fully cleaned point clouds of ground and off-ground points (.las), a 25 cm DEM (.tif), and a 25 cm DSM (.tif) for the Teller 27 field site. Ancillary aircraft data, flight mission parameters, weather conditions, and raw lidar data and imagery can be found in the L0 datasets for these campaigns: NGA299 (2017) and NGA297 (2018). Minimally processed point clouds and auxiliary files can be found in the L1 dataset: NGA304 (2017 and 2018).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Reduction of Chemokine CXCL9 Expression by Omega-3 Fatty Acids via ADP-Ribosylhydrolase ARH3 in MIN6 Insulin-Producing Cells

Type 1 diabetes (T1D) results from the autoimmune destruction of the insulin-producing β cells of the pancreas. Omega-3 fatty acids protect β cells and reduce the incidence of T1D, but the mechanism is poorly understood. We have shown that omega-3 fatty acids reduce pro-inflammatory cytokine-mediated β-cell apoptosis by upregulating the expression of the ADP-ribosylhydrolase ARH3. Here, we further investigate the β-cell protection mechanism of ARH3 by performing siRNA analysis of its gene Adprhl2 in MIN6 insulin-producing cells, subsequent treatment with a cocktail of the pro-inflammatory cytokines IL-1β + IFN-γ + TNF-α, followed by proteomics analysis. ARH3 regulated proteins from several pathways related to the nucleus (splicing, RNA surveillance, and nucleocytoplasmic transport), mitochondria (metabolic pathways), and endoplasmic reticulum (protein folding). ARH3 also regulated the levels of proteins related to antigen processing and presentation, and the chemokine-signaling pathway. We further studied the role of ARH3 in regulating the chemokine CXCL9. We found that ARH3 reduces the cytokine-induced expression of CXCL9, which is dependent on omega-3 fatty acids. In conclusion, we demonstrate that omega-3 fatty acids regulate CXCL9 expression via ARH3, which may have a role in protecting β cells from immune attack thereby preventing T1D development.

59 BASIC BIOLOGICAL SCIENCES↗

Metabolic engineering of non-pathogenic microorganisms for 2,3-butanediol production

2,3-Butanediol (2,3-BDO) is a promising commodity chemical with various industrial applications. While petroleum-based chemical processes currently dominate the industrial production of 2,3-BDO, fermentation-based production of 2,3-BDO pro- vides an attractive alternative to chemical-based processes with regards to economic and environmental sustainability. The achievement of high 2,3-BDO titer, yield, and productivity in microbial fermentation is a prerequisite for the production of 2,3-BDO at large scales. Also, enantiopure production of 2,3-BDO production is desirable because 2,3-BDO stereoisomers have unique physicochemical properties. Pursuant to these goals, many metabolic engineering strategies to improve 2,3-BDO pro- duction from inexpensive sugars by Klebsiella oxytoca, Bacillus species, and Saccharomyces cerevisiae have been developed. Furthermore, this review summarizes the recent advances in metabolic engineering of non-pathogenic microorganisms to enable efficient and enantiopure production of 2,3-BDO.

2,3-BDO stereoisomers↗

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV- 2 main protease

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) approaches followed by experimental validation. Generative deep learning models have been recently developed that can generate thousands of new candidates, but their physiochemical properties are typically not optimized. Using our deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 M pro that preserve the core scaffold. Here we utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure–activity relationships, multi-parameter optimization, and graph neural networks on libraries of generated candidates to predict biological activity and binding affinity a priori. From these collective computational results, eight promising candidates were identified and tested experimentally using Native Mass Spectrometry (MS) and FRET-based functional assays. Two compounds, with quinazoline-2-thiol and acetylpiperidine core moiety showed IC 50 values in the low micromolar range: 2.95±0.0017 µM and 3.41±0.0015 µM, respectively. The molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations in the chain B and the interface domains of the M pro . The key fragments from these top hits can be used as input for closed loop lead optimization in the integrated pipeline.

60 APPLIED LIFE SCIENCES↗

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Identification of a Covalent Molecular Inhibitor of Anti-apoptotic BFL-1 by Disulfide Tethering

The BCL-2 family is composed of anti- and pro-apoptotic members that respectively protect or disrupt mitochondrial integrity. Anti-apoptotic overexpression can promote oncogenesis by trapping the BCL-2 homology 3 (BH3) “killer domains” of pro-apoptotic proteins in a surface groove, blocking apoptosis. Groove inhibitors, such as the relatively large BCL-2 drug venetoclax (868 Da), have emerged as cancer therapies. BFL-1 remains an undrugged oncogenic protein and can cause venetoclax resistance. Having identified a unique C55 residue in the BFL-1 groove, we performed a disulfide tethering screen to determine if C55 reactivity could enable smaller molecules to block BFL-1's BH3-binding functionality. We found that a disulfide-bearing N-acetyltryptophan analog (304 Da adduct) effectively targeted BFL-1 C55 and reversed BFL-1-mediated suppression of mitochondrial apoptosis. Structural analyses implicated the conserved leucine-binding pocket of BFL-1 as the interaction site, resulting in conformational remodeling. Thus, therapeutic targeting of BFL-1 may be achievable through the design of small, cysteine-reactive drugs.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive proteomics analysis of stressed human islets identifies GDF15 as a target for type 1 diabetes intervention

Type 1 diabetes results from the progressive loss of beta cells, a process propagated by pro-inflammatory cytokine signaling that disrupts the balance between the expression of pro- and anti-apoptotic proteins. To identify such proteins, we performed comprehensive proteomics of human pancreatic islets treated with interleukin-1ß and interferon-?, leading to the identification of 11,325 proteins, of which 387 were significantly regulated by treatment. We then tested the function of growth/differentiation factor 15 (GDF15), which was repressed by the cytokine treatment. We found that GDF15 translation was blocked during inflammation, while the addition of exogenous GDF15 inhibited interleukin-1ß/interferon-?-induced apoptosis of human islets and a human beta-cell line. Furthermore, administration of GDF15 significantly decreased insulitis in NOD mice. Our approach provides a unique resource for the identification of the human islet proteins regulated by cytokines and was effective in discovering a potential target for type 1 diabetes therapy.

Nakayasu, Ernesto S.↗

Cecropin P1 antimicrobial peptide modulates differential expression of immune relevant genes in rainbow trout ( Oncorhynchus mykiss ) gill cell line, RTgill-W1

Accumulated evidence indicates that antimicrobial peptides modulate immune activities in fish. In this study, we profiled the differential expression patterns of representative immune relevant genes in an epithelial-like cell line of rainbow trout gill, RTgill-W1, in response to exposure of cecropin P1 antimicrobial peptide. RTgill-W1 cells were treated with synthetic cecropin P1 over time (0, 2, 4 and 24 h) with or without the present of lipopolysaccharide (LPS) or polyinosinic polycytidylic acid (PolyI:C). The relative abundances of each mRNA were measured by real-time quantitative PCR. The dose-response study revealed significant perturbations of mRNA levels of genes related to pro-inflammation, acute phase, surface proteins and transcription factors at 30 μM of cecropin P1. In addition, cecropin P1 altered the differential expression patterns that were induced by LPS or PolyI:C, at different time points in RTgill-W1. Overall, our results indicate that cecropin P1 exhibits pro-inflammation activity, modulate cell-cell interaction and cytokine signal transduction in rainbow trout gill cell, and may suggest a potential application of this peptide as an immune adjuvant for disease control in aquaculture.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic algorithm optimization of a chemical kinetic mechanism for propane at engine relevant conditions

Propane has demonstrated significant potential for reductions in greenhouse gas and pollutant emissions in medium- and heavy-duty engine applications, but further improvements require accurate, compact, and scalable chemical kinetic mechanisms to design the next generation of propane fueled engines, particularly at the boosted operating conditions necessary to meet the power density demand of medium- and heavy-duty applications. In this work, six key chemical reactions were identified in a reduced mechanism with 70 species and 352 reactions through a sensitivity analysis performed at conditions typical of thermodynamic trajectories observed in a high compression ratio, long stroke engine operated on propane from throttled to boosted operating conditions. While the original mechanism was validated against rapid compression machine (RCM) data, it was found to overpredict experimental autoignition tendencies in 2-zone, 0-D SI engine simulations performed in Chemkin Pro. Subsequently, a genetic algorithm approach was used to optimize the six reaction rate parameters within established uncertainty bounds by performing RCM simulations and comparing to two independent sets of literature ignition delay times for propane, thus generating two new kinetic mechanisms. The first optimization achieved a mean absolute percent error (MPE) reduction in 2nd stage ignition delay of 61.4% in seven generations, while the second optimization utilized a newer experimental RCM dataset, and achieved MPE reduction of 56.7% in seven generations, and further marginal improvement to 57.8% reduction in 34 generations. Finally, the two mechanisms were then evaluated again in the 2-zone 0-D SI engine model in Chemkin Pro comparing typical mean and knocking cycle trajectories, and it was found that the second optimized mechanism provided better prediction of knock onset at the representative conditions evaluated in this work, particularly for higher load operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins

Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.

Additive Manufacturing↗

Long term durability test and post mortem for metal-supported solid oxide electrolysis cells

Hydrogen is a renewable energy carrier, and electrolysis to split water is the most environmentally friendly method to produce hydrogen. This work reports long-term durability and degradation mode analysis for metal-supported solid oxide electrolysis cells (MS-SOECs). Catalyst screening showed that MS-SOECs with composite electrode catalysts (samarium-doped ceria-nickel [SDC-Ni] serving as a fuel electrode catalyst, and praseodymium oxide [PrO x ]-SDC or La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 [LSCF]-SDC serving as an air electrode catalyst) exhibit the highest electrochemical performance at 700 °C. The degradation rate of cells with LSCF-SDC as the air electrode catalyst was as low as 1.3%/100 h in long term durability tests at a current density of 0.33 A cm -2 , in contrast to rapid degradation observed for a cell with a PrO x -SDC air electrode. Furthermore, post-mortem analysis reveals the degradation is dependent on the primary modes of fuel electrode catalyst coarsening and Cr poisoning on the air electrode catalyst, as well as secondary modes of oxidation of the metal support and local elemental accumulation of Ni. Other degradation modes reported in conventional anode-supported SOECs, such as Ni migration, foreign element contamination, delamination of the cell, and nano-voids on the electrolyte, are not observed in the present MS-SOECs.

25 ENERGY STORAGE↗

Low Peripheral Blood Counts and Elevated Proinflammatory Cytokines Signal a Poor CD19 Chimeric Antigen Receptor T-cell Response in Acute Lymphoblastic Leukemia

CD19 chimeric antigen receptor T-cell (CAR-T) therapy has significantly improved outcomes for patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL). However, approximately 20% of patients fail to achieve a complete remission (CR), and some develop severe, life-threatening toxicities. Understanding the biological mechanisms underlying both dysfunctional responses and severe toxicity is essential for optimizing patient management and improving therapeutic efficacy. This study aimed to (1) characterize cytokine profiles associated with dysfunctional responses and severe toxicity following CAR-T infusion, (2) examine the timing and trajectory of cytokine changes in relation to treatment outcomes, and evaluate potential strategies for mitigating toxicity and treatment failure. We conducted a comprehensive analysis of serum cytokine profiles in 86 adult and pediatric patients undergoing autologous CD19 CAR-T therapy for B-ALL. Patients were categorized into three groups: (1) Dysfunctional response—Patients who failed to achieve a minimal residual disease-negative CR (MRD-CR) by Day 63 or who experienced recurrence of CD19+ disease in the setting ongoing CAR-T cell detection before Day 63. (2) Functional response with severe cytokine release syndrome (CRS) and/or neurotoxicity (NTX)—Patients with best response of MRD-CR by Day 63 who experienced grade 3 or higher CRS or NTX. (3) Functional response without severe CRS or NTX—Patients with best response of MRD-CR by Day 63 who did not experience grade =3 CRS or NTX. Cytokine levels were measured during the first-week postinfusion and correlated with treatment efficacy, toxicity outcomes, complete blood counts, and CAR-T expansion dynamics. This analysis aimed to better understand how cytokine profiles relate to patient outcomes and immune responses in CAR-T therapy. Patients with dysfunctional response exhibited decreased neutrophils, platelets, and levels of granulocytic cytokines (suggestive of low bone marrow reserve) alongside elevated pro-inflammatory cytokines by Day 1. Functional response with severe toxicity patients showed a progressive rise in proinflammatory cytokines, reaching similar levels to dysfunctional response patients by Day 7. We observed that high cytokines at both the Day 1 and Day 7 time points were associated with poor survival. These findings remained significant when adjusting for high disease burden, a known predictor of severe inflammatory toxicity and lack of response. Early post-CAR-T infusion inflammation is associated with both dysfunctional response and severe toxicity—even after adjusting for disease burden. This suggests that inflammation, in addition to disease burden, plays a role in determining patient outcome. Therefore, strategies aimed at reducing the pro-inflammatory state prior to or early after CAR-T cell infusion may improve outcomes for R/R B-ALL patients.

Serum cytokines↗

Immunophenotypic characterization and therapeutics effects of human bone marrow- and umbilical cord-derived mesenchymal stromal cells in an experimental model of sepsis

Highlights: • Mesenchymal stromal cells (MSCs) may be a therapeutic option for sepsis. • Bone marrow (BM) vs. umbilical cord (UC) -MSCs induce different M1/M2 gene profiles. • In a CLP model of sepsis, only BM-MSCs improved survival and bacterial clearance. Sepsis is a complicated multi-system disorder characterized by a dysregulated host response to infection. Despite substantial progress in the understanding of mechanisms of sepsis, translation of these advances into clinically effective therapies remains challenging. Mesenchymal Stromal Cells (MSCs) possess immunomodulatory properties that have shown therapeutic promise in preclinical models of sepsis. The therapeutic effects of MSCs may vary depending on the source and type of these cells. In this comparative study, the gene expression pattern and surface markers of bone marrow-derived MSCs (BM-MSCs) and umbilical cord-derived MSCs (UC-MSCs) as well as their therapeutic effects in a clinically relevant mouse model of polymicrobial sepsis, cecal ligation and puncture (CLP), were investigated. The results showed remarkable differences in gene expression profile, surface markers and therapeutic potency in terms of enhancing survival and pro/anti-inflammatory responses between the two MSC types. BM-MSCs improved survival concomitant with an enhanced systemic bacterial clearance and improved inflammatory profile post CLP surgery. Despite some improvement in the inflammatory profile of the septic animals, treatment with UC-MSCs did not enhance survival or bacterial clearance. Overall, the beneficial therapeutic effects of BM-MSCs over UC-MSCs may likely be attributed to their pro-inflammatory function, and to some extent anti-inflammatory features, reflected in their gene expression pattern enhancing macrophage polarization to M1/M2 phenotypes resulting in a balanced pro- and anti-inflammatory response against polymicrobial sepsis.

60 APPLIED LIFE SCIENCES↗

Crosstalk between cyclophilins and T lymphocytes in coronary artery disease

Highlights: • CD147 receptor expression is elevated in T lymphocytes from CAD patients. • Intracellular CypA and B expression are augmented in T lymphocytes from CAD patients. • CypA, B and C, and IL-1β and IL-6 serum levels are increased in patients with CAD. • CypA and B levels in T lymphocytes are correlated with CypA and B serum levels, respectively. Cardiovascular diseases and atherosclerosis are currently some of the most widespread diseases of our time. Within cardiovascular disease, coronary artery disease and underlying atherosclerosis were recently linked with systemic and local inflammation. Cyclophilins participate in the initiation and progression of these inflammatory-related diseases. Cyclophilins are released into the extracellular space upon inflammatory stimuli and participate in the pathology of cardiovascular diseases. The cell surface receptor for extracellular cyclophilins, the CD147 receptor, also contributes to coronary artery disease pathogenesis. Nevertheless, the physiological relevance of cyclophilin's family and their receptor in cardiovascular diseases remains unclear. The present study aimed to better understand the role of cyclophilins in cardiovascular artery disease and their relationship with inflammation. Hence, cyclophilins and pro-inflammatory interleukins were measured in the serum of 30 subjects (divided into three groups according to coronary artery disease status: 10 patients with acute coronary syndrome, 10 patients with chronic coronary artery disease, and 10 control volunteers). In addition, cyclophilin levels and CD147 receptor expression were measured in T lymphocytes purified from these subjects. Cyclophilin A, B, and C, pro-inflammatory interleukins, and CD147 membrane expression were significantly elevated in patients with coronary artery disease.

60 APPLIED LIFE SCIENCES↗

Chorioallantoic membrane vascularization. A meta-analysis

The CAM is a widely used experimental assay to study angiogenesis, wound healing, tumor growth and metastatic process. In this study, we have analyzed and compared the existent literature data concerning the growth of the CAM. Moreover, we have analyzed the data concerning the development of the vascular system and the expression of the most important pro-angiogenic and anti-angiogenic factors. The availability of these data and their comparative evaluation allow to better analyze the experimental data concerning the testing of different pro-angiogenic and anti-angiogenic molecules, as well as biomaterials in the CAM assay. Moreover, the dynamic of the angiogenic response to different tumor cell lines and or tumor bioptic specimens, may be also better evaluated and estimated.

60 APPLIED LIFE SCIENCES↗