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Cooling channels play a critical role in various casting and molding processes, impacting both the cycle time and quality of the product. As additive manufacturing technologies become increasingly prevalent, conventional straight-drilled channels are being progressively substituted by intricate cooling lines that conform to the contours of the fabricated part. This transition can lead to a significant reduction of the solidification time and temperature gradients, consequently lowering the occurrence of part defects. However, designing such channels becomes challenging as geometric complexity and manufacturing constraints increase. In this work, we present a density-based topology optimization approach to generate conformal cooling channels in molds and dies inserts. To mitigate temperature variations, the objective function is penalized using the temperature standard deviation of the insert cavity surface. A density-gradient-based constraint is further utilized to reduce the generation of overhanging structures and promote manufacturability. In particular, the use of this constraint leads to the generation of channels characterized by a teardrop-shaped cross section. The cooling efficiency of a selected optimized design is confirmed through computations using a body-fitted solver. The geometry is subsequently manufactured by Laser Powder Bed Fusion (LPBF) and experiments are conducted to compare its performance in comparison to a design featuring straight-drilled channels. The results demonstrate that the optimized geometry significantly enhances the heat extraction rate and further leads to a 43% reduction of the cavity temperature standard deviation.

The onset and physical patterns of gap instability (GI), characterised previously as an inviscid, Kelvin–Helmholtz instability, were investigated experimentally and numerically in an eccentric annular channel with an inner-to-outer diameter ratio $d/D=0.5$ and a length equal to 320 hydraulic diameters. The focus was on the range of low and moderate eccentricities ($0\\lesssim e \\leqslant 0.5$) and Reynolds numbers ($\\textit {Re}\\lesssim 12\\,000$). It was found that, in laminar flow, GI occurred for $e$ as low as $0.05$. When, however, the flow was turbulent in at least part of the cross-section ($\\textit {Re}\\gtrsim 5000$), GI remained strong only for $e\\geqslant 0.5$ but was essentially undetectable for $e\\lesssim 0.3$. For $e$ lower than 0.3, the critical Reynolds number for the onset of GI increased with decreasing $e$. Time-frequency analysis of the velocity time histories has revealed the presence of a single type of dominant mode for $e=0.7$ and all considered $\\textit {Re}$, and two distinct, occasionally coexisting, modes for $e \\lesssim 0.5$ and $2000 \\lesssim \\textit {Re} \\lesssim 5000$. Within a range of low-$e$ or low-$\\textit {Re}$ conditions, quasi-periodic flows were highly intermittent and less energetic in an upstream section of the channel, but became progressively less intermittent further downstream. The energy of such motions generally increased with increasing streamwise distance, e and Re. By exception, this energy decreased with increasing $\\textit {Re}$ for $e\\leqslant 0.3$ and $\\textit {Re}\\gtrsim 2000$. The gap vortex street generation mechanism and development was analysed and an improved physical model was proposed.

Nanoparticles made of the coat protein of papaya mosaic virus (PapMV) and a single-strand RNA were previously shown to be an efficient antigen presentation system for the trigger of cellular immunity. Engineering of PapMV nano with a cytotoxic T lymphocyte epitope was previously shown activating specific T lymphocytes through a proteasome-independent major histocompatibility complex class I (MHC-I) cross-presentation. In this study, we provide new insights into the mechanism of the MHC-I cross-presentation mediated by PapMV nanoparticles. We demonstrate that PapMV nanoparticles do not require the transporter associated with antigen presentation (TAP), but rather depend on lysosome acidification and cathepsin S protease activity for presentation of the T cell epitope. We have also linked the induction of autophagy with this vacuolar MHC-I cross-presentation process. Interestingly, autophagy is induced in antigen-presenting cells after PapMV nanoparticles exposure and inhibition of autophagy reduce MHC-I cross-presentation. This study demonstrates that autophagy is associated with TAP- and proteasome-independent MHC-I cross-presentation. A deeper understanding of the autophagy-dependent MHC-I cross-presentation will be useful in designing vaccination platforms that aim to trigger an efficient cytotoxic T lymphocyte response.

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se . CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.

Visualisations of various types of flow separation are presented in an experimental set-up that translates a rotating cylinder parallel to a wall. Particle image velocimetry is used to measure the two velocity components in a plane perpendicular to the cylinder where the flow is two-dimensional. To spatially resolve the flow close to the wall, a high-viscosity fluid is used. For a periodic translation, the fixed separation is compared to the theory of Haller (J. Fluid Mech., vol. 512, 2004, pp. 257–311), while for non-periodic translations, a method is proposed to extract the moving separation point captured by a Lagrangian saddle point, and its finite-time unstable direction (separation profiles). Intermediate cases are also presented where both types of separation, fixed and moving, are either present simultaneously or appear successively. Some results issued from numerical simulations of an impinging jet show that all the cases observed in the rotor-oscillator flow are not restricted to high-viscosity fluid motions but may also occur within any vortical flow.

This paper provides new insight into the relationship between inflation and the setting of individual prices by examining a large data set of Mexican consumer prices covering episodes of both low and high inflation. When the annual rate of inflation is low (below 10%-15%), the frequency of price changes comoves weakly with inflation because movements in the frequency of price decreases and increases partly offset each other. In contrast, the average magnitude of price changes correlates strongly with inflation because it is sensitive to movements in the relative shares of price increases and decreases. When inflation rises beyond 10%-15%, few price decreases are observed and both the frequency and average magnitude are important determinants of inflation. I show that a menu-cost model with idiosyncratic technology shocks predicts the average frequency and magnitude of price changes well over a range of inflation similar to that experienced by Mexico.

To colonize phagocytes, Leishmania subverts microbicidal processes through components of its surface coat that include lipophosphoglycan and the GP63 metalloprotease. How these virulence glycoconjugates are shed, exit the parasitophorous vacuole (PV), and traffic within host cells is poorly understood. Here, we show that lipophosphoglycan and GP63 are released from the parasite surface following phagocytosis and redistribute to the endoplasmic reticulum (ER) of macrophages. Pharmacological disruption of the trafficking between the ER and the Golgi hindered the exit of these molecules from the PV and dampened the cleavage of host proteins by GP63. Silencing by RNA interference of the soluble N-ethylmaleimide-sensitive-factor attachment protein receptors Sec22b and syntaxin-5, which regulate ER-Golgi trafficking, identified these host proteins as components of the machinery that mediates the spreading of Leishmania effectors within host cells. Our findings unveil a mechanism whereby a vacuolar pathogen takes advantage of the host cell's secretory pathway to promote egress of virulence factors beyond the PV.

We study the pricing response of U.S. supermarkets to large demand shocks triggered by labor conflicts, mass population displacement, and shopping sprees around major snowstorms and hurricanes. We find that these large swings in demand have, at best, modest effects on the level of retail prices, consistent with flat short- to medium-term supply curves. This finding holds even when shocks are highly persistent and despite the fact that stores adjust prices frequently. We also provide evidence that retailers maintain frequent promotional sales even as their demand varies and that they seek to match movements in their local competitors’ recourse to promotional sales.

RIMap-RISC is a web-accessible database for transcriptome-wide modeling of human microRNA (miRNA) targeting. It computes plausible transcript-miRNA interactions and records their position, duplex secondary structure, free energy, site classification, dissociation constant, target accessibility, and evolutionary conservation. RIMap-RISC supports transcript-wide queries and allows users to explore and export interaction data through an interactive interface or RESTful API programmatic access. Unlike existing tools, RIMap-RISC integrates duplex-structure prediction within a biophysical framework modeling the bipartite architecture of RISC, accommodating a bridge between seed and supplementary pairing. A novel, unambiguous, miRNA-centric nomenclature for interaction types is also introduced.

BackgroundOne avenue of recent research has focused on harnessing the patient‘s immune system to eradicate tumors called immunotherapies. To do so, T cells from a cancer patient are harvested and genetically modified to express a chimeric antigen receptor (CAR), capable of recognizing tumor cells, then reinfused into the patient. CARs are synthetic transmembrane proteins composed of a tumor-targeting domain, a membrane anchoring domain and a complex signaling domain to activate T cells promoting tumor cell killing. These therapies have shown exceptional results in the treatment of young patients with leukemia and lymphoma. We hypothesize that CAR-based immunotherapy complications arise from faulty CAR architecture resulting in an aberrant immune response.MethodsTo mitigate this, we have developed a new CAR architecture through functional screening, which mimics natural immune receptor assembly and surface expression. These new modular CARs (mCARs) show better efficacy in signaling and killing tumor cells compared to the standard of care (SOC-CAR). More so, mCARs are compatible for hematopoietic stem cell-based treatment avenue as mCAR-HSC are able to differentiate into a myriad of immune cells enable the deployment of an effector cell armada against target cells.ResultsWe are currently optimizing the signaling cues provided by mCARs by introducing new signaling motifs and benchmarking them to SOC-CAR in clinically relevant mouse tumor models. Additionally, we are screening novel signaling domains to improve tumor cell killing, functionality and longevity. Finally, these results will allow us to pick the best combination of signaling motif provided by the mCAR that result in an increase treatment outcomes and decrease in complications.ConclusionsTogether, the findings made here will help determine the efficacy of the newly optimized mCARs in maintaining cell survival and functionality and set the framework for their clinical implementation.