Probing the Short-Distance Structure of the Quark-Gluon Plasma with Energy Correlators.

Energy-energy correlators (EECs) are promising observables to study the dynamics of jet evolution in the quark-gluon plasma (QGP) through its imprint on angular scales in the energy flux of final-state particles. We carry out the first complete calculation of EECs using realistic simulations of high-energy heavy-ion collisions and dissect the different dynamics underlying the final distribution through analyses of jet propagation in a uniform medium. The EECs of γ-jets in heavy-ion collisions are found to be enhanced by the medium response from elastic scatterings instead of induced gluon radiation at large angles. In the meantime, EECs are suppressed at small angles due to energy loss and transverse momentum broadening of jet shower partons. These modifications are further shown to be sensitive to the angular scale of the in-medium interaction, as characterized by the Debye screening mass. Experimental verification and measurement of such modifications will shed light on this scale and the short-distance structure of the QGP in heavy-ion collisions.

Songorine inhibits oxidative stress-related inflammation through PI3K/AKT/NRF2 signaling pathway to alleviate lipopolysaccharide-induced septic acute lung injury.

OBJECTIVE: The present study aimed to investigate the protective action and mechanism of songorine on sepsis-induced acute lung injury (ALI). METHODS: The sepsis-induced ALI mouse and cell models were established by lipopolysaccharide (LPS) induction. Lung injury was assayed by hematoxylin and eosin staining, lung injury score, and lung wet-to-dry (W/D) weight ratio. Apoptosis in lung tissues was evaluated by TUNEL assay, and the expression of apoptosis-related markers (Bcl2, Bax, and caspase-3) was measured by western blotting. Levels of pro-inflammatory factors and oxidative stress markers in the bronchoalveolar lavage fluid (BALF) of mice were measured by ELISA and RT-qPCR. The expression of PI3K/AKT/NRF2 pathway-related proteins was analyzed by western blotting. RESULTS: Songorine treatment at 40 mg/kg mitigated sepsis-induced ALI, characterized by improved histopathology, lung injury score, and lung W/D weight ratio (p < 0.05). Moreover, songorine markedly attenuated sepsis-induced apoptosis in lung tissues; this was evidenced by an increase in Bcl2 levels and a decrease in Bax and caspase-3 levels (p < 0.01). Also, songorine reduced levels of proinflammatory cytokines (TNF-α, IL-6, IL-1ß and MPO) and oxidative stress regulators (SOD and GSH) in the BALF of LPS-induced sepsis mice and RAW264.7 cells (p < 0.05). In addition, songorine upregulated the PI3K/AKT/NRF2 pathway-related proteins in LPS-induced sepsis mice and RAW264.7 cells (p < 0.05). Furthermore, LY294002 (a PI3K inhibitor) treatment reversed the protective effect of songorine on sepsis-induced ALI. CONCLUSION: Songorine inhibits oxidative stress-related inflammation in sepsis-induced ALI via the activation of the PI3K/AKT/NRF2 signaling pathway.

Development of the ARDS-derived gene panel for lung adenocarcinoma prognosis stratification and experiment validation of CCL20 expression.

Acute respiratory distress syndrome (ARDS) is a life-threatening condition characterized by lung inflammation and high mortality rates. Lung cancer, specifically lung adenocarcinoma (LUAD), is a major cause of cancer-related deaths worldwide. Patients with LUAD, particularly those undergoing chemotherapy, are more likely to develop ARDS. ARDS inflicts major malfunctioning in the immune system. We suspected a certain shared pathogenic mechanism between these diseases. This study analyzed 503 LUAD patients from the TCGA-LUAD cohort as the training set, 85 LUAD cases from the GSE30219 cohort as the validation set, and 24 RNA-seq samples from ARDS mice model and control groups in the GSE2411 cohort. The differentially expressed genes (DEGs) of ARDS were analyzed using the limma package and screened by Cox and Lasso analysis. ssGSEA and xCell algorithms were utilized for immune landscaping. RT-qPCR analysis was used to determine the mRNA levels of key genes in both the LPS-induced ARDS model and human LUAD cell lines. We identified DEGs between ARDS and control groups, which were highly associated with cytokine production and leukocyte migration. A prognosis model for LUAD patients was developed based on the expressions of the key genes in the ARDS-derived DEGs, including FMO3, IL1R2, CCL20, CFTR, and GADD45G. A satisfactory efficacy was observed in both the training and validation cohorts. The model demonstrated increased effectiveness in predicting the intratumor immune profile and mutation status of LUAD. Moreover, we utilized LPS to induce the ARDS model, which resulted in elevated expressions of IL1R2 and CCL20. Additionally, CCL20 was upregulated in cancerous LUAD cell lines. We developed an ARDS-based model for stratifying LUAD prognosis. CCL20 was found to be elevated in both the ARDS model and LUAD, suggesting a shared underlying mechanism of these two diseases.

3D Structure of Jet-Induced Diffusion Wake in an Expanding Quark-Gluon Plasma.

The diffusion wake accompanying the jet-induced Mach cone provides a unique probe of the properties of quark-gluon plasma in high-energy heavy-ion collisions. It can be characterized by a depletion of soft hadrons in the opposite direction of the propagating jet. We explore the 3D structure of the diffusion wake induced by γ-triggered jets in Pb+Pb collisions at the LHC energy within the coupled linear Boltzmann transport and hydro model. We identify a valley structure caused by the diffusion wake on top of a ridge from the initial multiple parton interaction (MPI) in jet-hadron correlation as a function of rapidity and azimuthal angle. This leads to a double-peak structure in the rapidity distribution of soft hadrons in the opposite direction of the jets as an unambiguous signal of the diffusion wake. Using a two-Gaussian fit, we extract the diffusion wake and MPI contributions to the double peak. The diffusion wake valley is found to deepen with the jet energy loss as characterized by the γ-jet asymmetry. Its sensitivity to the equation of state and shear viscosity is also studied.

Spin Alignment of Vector Mesons in Heavy-Ion Collisions.

Polarized quarks and antiquarks in high-energy heavy-ion collisions can lead to the spin alignment of vector mesons formed by quark coalescence. Using the relativistic spin Boltzmann equation for vector mesons derived from Kadanoff-Baym equations with an effective quark-meson model for strong interaction and quark coalescence model for hadronizaton, we calculate the spin density matrix element ρ_{00} for ϕ mesons and show that anisotropies of local field correlations with respect to the spin quantization direction lead to ϕ meson's spin alignment. We propose that the local correlation or fluctuation of ϕ fields is the dominant mechanism for the observed ϕ meson's spin alignment and its strength can be extracted from experimental data as functions of collision energies. The calculated transverse momentum dependence of ρ_{00} agrees with STAR's data. We further predict the azimuthal angle dependence of ρ_{00} which can be tested in future experiments.

From Hydrodynamics to Jet Quenching, Coalescence, and Hadron Cascade: A Coupled Approach to Solving the R_{AA}⊗v_{2} Puzzle.

Hydrodynamics and jet quenching are responsible for the elliptic flow v_{2} and suppression of large transverse momentum (p_{T}) hadrons, respectively, two of the most important phenomena leading to the discovery of a strongly coupled quark-gluon plasma in high-energy heavy-ion collisions. A consistent description of the hadron suppression factor R_{AA} and v_{2}, especially at intermediate p_{T}, however, remains a challenge. We solve this long-standing R_{AA}⊗v_{2} puzzle by including quark coalescence for hadronization and final state hadron cascade in the coupled linear Boltzmann transport-hydro model that combines concurrent jet transport and hydrodynamic evolution of the bulk medium. We illustrate that quark coalescence and hadron cascade, two keys to solving the puzzle, also lead to a splitting of v_{2} for pions, kaons, and protons in the intermediate p_{T} region. We demonstrate for the first time that experimental data on R_{AA}, v_{2}, and their hadron flavor dependence from low to intermediate and high p_{T} in high-energy heavy-ion collisions can be understood within this coupled framework.

Determination and pharmacokinetics study of UK-5099 in mouse plasma by LC-MS/MS.

BACKGROUND: UK-5099 is a potent mitochondrial acetone carrier inhibitor, that exhibits anticancer activity. Recently, the anti-Toxoplasma gondii activity of UK-5099 was proposed, and in vivo studies of its pharmacokinetics in BALB/c mice are necessary to further evaluate the clinical effect of UK-5099. METHODS AND RESULTS: A simple and fast high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis method was established and verified in terms of its linearity, matrix effect, accuracy, precision, recovery and stability. The analytes were separated by an Agilent ZORBAX XDB-C18 column (2.1 × 50 mm, 3.5 µm) at 30 °C. A gradient mobile phase consisting of water with 0.1% formic acid (FA) (phase A) and acetonitrile (ACN) (phase B) was delivered at a flow rate of 0.40 mL·min-1 with an injection volume of 5 µL. A good linear response was obtained in a concentration range of 5-5000 ng·mL-1 (r2 = 0.9947). The lower limit of quantification (LLOQ) was 5 ng·mL-1. The extraction recovery of UK-5099 was greater than 95%. The inter- and intra-day accuracy and precision of the method showed relative standard deviations (RSDs) of less than 15%. This method has been successfully applied to the pharmacokinetic evaluation of UK-5099 in mouse plasma. In health mice, the main pharmacokinetic parameters of UK-5099 after intraperitoneal administration were measured using a noncompartmental model, in which the AUC0-t was 42,103 ± 12,072 ng·h·mL-1 and the MRT0-t was 0.857 ± 0.143 h. The peak concentration (Cmax) was 82,500 ± 20,745 ng·h·mL-1, which occurred at a peak time (Tmax) = 0.250 ± 0.000 h. CONCLUSIONS: A fast and sensitive HPLC-MS/MS method was developed, validated and successfully used for the determination of UK-5099 levels in mice after intraperitoneal administration. This study was the first report of the pharmacokinetic parameters of UK-5099 in mice, which will help to further study the administration of UK-5099 in animals and humans.

Jet quenching and medium response in high-energy heavy-ion collisions: a review.

Jet quenching has been used successfully as a hard probe to study properties of the quark-gluon plasma (QGP) in high-energy heavy-ion collisions at both the relativistic heavy-ion collider and the large hadron collider. We will review recent progresses in theoretical and phenomenological studies of jet quenching with jet transport models. Special emphasis is given to effects of jet-induced medium response on a wide variety of experimental observables and their implications on extracting transport properties of the QGP in heavy-ion collisions.

Search for the Elusive Jet-Induced Diffusion Wake in Z/γ-Jets with 2D Jet Tomography in High-Energy Heavy-Ion Collisions.

Diffusion wake is an unambiguous part of the jet-induced medium response in high-energy heavy-ion collisions that leads to a depletion of soft hadrons in the opposite direction of the jet propagation. New experimental data on Z-hadron correlation in Pb+Pb collisions at the Large Hadron Collider show, however, an enhancement of soft hadrons in the direction of both the Z and the jet. Using a coupled linear Boltzmann transport and hydro model, we demonstrate that medium modification of partons from the initial multiple parton interaction (MPI) gives rise to a soft hadron enhancement that is uniform in azimuthal angle while jet-induced medium response and soft gluon radiation dominate the enhancement in the jet direction. After subtraction of the contributions from MPI with a mixed-event procedure, the diffusion wake becomes visible in the near-side Z-hadron correlation. We further employ the longitudinal and transverse gradient jet tomography for the first time to localize the initial jet production positions in Z/γ-jet events in which the effect of the diffusion wake is apparent in Z/γ-hadron correlation even without the subtraction of the MPI contribution.

Elevated Endostatin Expression Is Regulated by the pIgA Immune Complex and Associated with Disease Severity of IgA Nephropathy.

BACKGROUND/AIMS: Renal vascular injury accounts for the poor outcomes of patients with IgA nephropathy (IgAN). In this study, we investigated whether endostatin, a potent inhibitor of angiogenesis, is associated with IgAN. METHODS: Serum endostatin levels were detected in patients with IgAN, disease controls, and healthy controls, and the correlation among endostatin and clinicopathologic manifestations, as well as prognosis in patients with IgAN, was analyzed. In addition, serum endostatin levels were compared in patients "before" and "after" treatment. Data on endostatin expression in the renal interstitium of patients with IgAN were downloaded and analyzed from the GSE35489 array in the GEO database. The poly-IgA1 (pIgA) immune complex is widely recognized as the "trigger" of IgAN initiation. pIgA in the plasma of patients was extracted and used to stimulate human glomerular endothelial cells (GECs). Endostatin, IL-6, and CXCL1 in the cell supernatant were detected by ELISA kits. RESULTS: We found that serum endostatin levels were significantly increased in patients with IgAN, as was endostatin expression in the renal interstitium. Patients with IgAN were divided into 2 groups according to the median value. The high endostatin expression group had significantly higher levels of serum creatinine and BUN and more severe tubular/interstitial damage. Moreover, patients with arteriolar injury and endothelial cell proliferation had higher serum endostatin levels. Patients with high serum endostatin levels had poor prognosis. According to the in vitro experiment, the GEC apoptosis rate and the supernatant levels of endostatin, IL-6, and CXCL1 were significantly increased following pIgA stimulation. CONCLUSION: Our study found that elevated endostatin expression was associated with disease severity and poor prognosis in patients with IgAN and can be upregulated by pIgA, but how it participates in the pathogenesis of IgAN deserves further exploration.

Gradient Tomography of Jet Quenching in Heavy-Ion Collisions.

Transverse momentum broadening and energy loss of a propagating parton are dictated by the space-time profile of the jet transport coefficient q[over ^] in a dense QCD medium. The spatial gradient of q[over ^] perpendicular to the propagation direction can lead to a drift and asymmetry in parton transverse momentum distribution. Such an asymmetry depends on both the spatial position along the transverse gradient and path length of a propagating parton as shown by numerical solutions of the Boltzmann transport in the simplified form of a drift-diffusion equation. In high-energy heavy-ion collisions, this asymmetry with respect to a plane defined by the beam and trigger particle (photon, hadron, or jet) with a given orientation relative to the event plane is shown to be closely related to the transverse position of the initial jet production in full event-by-event simulations within the linear Boltzmann transport model. Such a gradient tomography can be used to localize the initial jet production position for more detailed study of jet quenching and properties of the quark-gluon plasma along a given propagation path in heavy-ion collisions.

Bayesian Extraction of Jet Energy Loss Distributions in Heavy-Ion Collisions.

Based on the factorization in perturbative QCD, a jet cross section in heavy-ion collisions can be expressed as a convolution of the jet cross section in p+p collisions and a jet energy loss distribution. Using this simple expression and the Markov Chain Monte Carlo method, we carry out Bayesian analyses of experimental data on jet spectra to extract energy loss distributions for both single inclusive and γ-triggered jets in Pb+Pb collisions with different centralities at two colliding energies at the Large Hadron Collider. The average jet energy loss has a dependence on the initial jet energy that is slightly stronger than a logarithmic form and decreases from central to peripheral collisions. The extracted jet energy loss distributions with a scaling behavior in x=Δp_{T}/⟨Δp_{T}⟩ have a large width. These are consistent with the linear Boltzmann transport model simulations, in which the observed jet quenching is caused on the average by only a few out-of-cone scatterings.

Multi-Layer Feature Based Shoeprint Verification Algorithm for Camera Sensor Images.

As a kind of forensic evidence, shoeprints have been treated as important as fingerprint and DNA evidence in forensic investigations. Shoeprint verification is used to determine whether two shoeprints could, or could not, have been made by the same shoe. Successful shoeprint verification has tremendous evidentiary value, and the result can link a suspect to a crime, or even link crime scenes to each other. In forensic practice, shoeprint verification is manually performed by forensic experts; however, it is too dependent on experts' experience. This is a meaningful and challenging problem, and there are few attempts to tackle it in the literatures. In this paper, we propose a multi-layer feature-based method to conduct shoeprint verification automatically. Firstly, we extracted multi-layer features; and then conducted multi-layer feature matching and calculated the total similarity score. Finally, we drew a verification conclusion according to the total similarity score. We conducted extensive experiments to evaluate the effectiveness of the proposed method on two shoeprint datasets. Experimental results showed that the proposed method achieved good performance with an equal error rate (EER) of 3.2% on the MUES-SV1KR2R dataset and an EER of 10.9% on the MUES-SV2HS2S dataset.

Vortical Fluid and Λ Spin Correlations in High-Energy Heavy-Ion Collisions.

Fermions become polarized in a vortical fluid due to spin-vorticity coupling, and the polarization density is proportional to the local fluid vorticity. The radial expansion converts spatial vortical structures in the transverse plane to spin correlations in the azimuthal angle of final Λ hyperons' transverse momentum in high-energy heavy-ion collisions. Using a (3+1)D viscous hydrodynamic model with fluctuating initial conditions from a multiphase transport (AMPT) model, we reveal two vortical structures that are common in many fluid dynamic systems: a right-handed toroidal structure around each beam direction for transverse vorticity and pairing of longitudinal vortices with opposite signs in the transverse plane. The calculated azimuthal correlation of the transverse spin is shown to have a cosine form plus an offset due to the toroidal structure of the transverse vorticity around the beam direction and the global spin polarization. The longitudinal spin correlation in the azimuthal angle shows an oscillatory structure due to multiple vorticity pairs in the transverse plane. Mechanisms of these vortical structures, physical implications of hyperon spin correlations, dependence on colliding energy, rapidity, centrality, and sensitivity to the shear viscosity are also investigated.

Next-to-leading order QCD factorization for semi-inclusive deep inelastic scattering at twist 4.

Within the framework of a high-twist approach, we calculate the next-to-leading order (NLO) perturbative QCD corrections to the transverse momentum broadening in semi-inclusive hadron production in deeply inelastic e+A collisions, as well as lepton pair production in p+A collisions. With explicit calculations of both real and virtual contributions, we verify, for the first time, the factorization theorem at twist 4 in NLO for the nuclear-enhanced transverse momentum weighted differential cross section and demonstrate the universality of the associated twist-4 quark-gluon correlation function. We also identify the QCD evolution equation for the twist-4 quark-gluon correlation function in a large nucleus, which can be solved to determine the scale dependence of the jet transport parameter in the study of jet quenching.

Ab initio modeling and experimental analysis of electronic conductivity in PEDOT:PSS-PEO films for extrusion-based manufacturing.

In this study, a combination of ab initio modeling and experimental analysis is presented to investigate and elucidate the electronic conductivity of films composed of conducting polymer blend PEDOT:PSS-PEO. Detailed density functional theory (DFT) calculations, aligned with experimental data, aided at profound understanding of the chemical composition, band structure, and the mechanical behavior of these composite materials. Systematic evaluation across diverse ratios of PEDOT, PSS, and PEO revealed a pronounced transformation in electronic properties. Specifically, the addition of PEO into the polymer matrix remarkably changes the band gap, with a marked alteration observed near a PEO concentration of 52 wt-%. This adjustment led to a substantial enhancement in the electrical conductivity, exhibiting an increase by a factor of approximately 20, compared to the original PEDOT:PSS polymer. The present investigation determined the crucial role of the PEDOT to PSS ratio in band gap determination, emphasizing its significant impact on the material's electrical conductivity. Concurrently, the mechanical property analysis unveiled a consistent increase in Young's modulus, reaching up to 765.93 MPa with increased PEO content, signifying a notable mechanical stiffening of the blend. The obtained combined theoretical and experimental insights illustrate a detailed perspective on the conductivity anomalies observed in PEDOT:PSS-PEO systems, establishing a robust framework for designing highly conducting and mechanically stable polymer blends. This comprehensive approach elucidates the interplay between chemical composition and electronic behavior, offering a strategic pathway for extrusion-based manufacturing techniques such as Direct Ink Writing (DIW).

A prefrontal-thalamic circuit encodes social information for social recognition.

Social recognition encompasses encoding social information and distinguishing unfamiliar from familiar individuals to form social relationships. Although the medial prefrontal cortex (mPFC) is known to play a role in social behavior, how identity information is processed and by which route it is communicated in the brain remains unclear. Here we report that a ventral midline thalamic area, nucleus reuniens (Re) that has reciprocal connections with the mPFC, is critical for social recognition in male mice. In vivo single-unit recordings and decoding analysis reveal that neural populations in both mPFC and Re represent different social stimuli, however, mPFC coding capacity is stronger. We demonstrate that chemogenetic inhibitions of Re impair the mPFC-Re neural synchronization and the mPFC social coding. Projection pathway-specific inhibitions by optogenetics reveal that the reciprocal connectivity between the mPFC and the Re is necessary for social recognition. These results reveal an mPFC-thalamic circuit for social information processing.

Medium modification of γ jets in high-energy heavy-ion collisions.

Two puzzling features in the experimental study of jet quenching in central Pb+Pb collisions at the LHC are explained within a linearized Boltzmann transport model for jet propagation. A γ-tagged jet is found to lose about 15% of its initial energy while its azimuthal angle remains almost unchanged due to rapid cooling of the medium. The reconstructed jet fragmentation function is found to have some modest enhancement at both small and large fractional momenta as compared to that in the vacuum because of the increased contribution of leading particles to the reconstructed jet energy and induced gluon radiation and recoiled partons. A γ-tagged jet fragmentation function is proposed that is more sensitive to jet-medium interaction and the jet transport parameter in the medium. The effects of recoiled medium partons on the reconstructed jets are also discussed.

Berry curvature and four-dimensional monopoles in the relativistic chiral kinetic equation.

We derive a relativistic chiral kinetic equation with manifest Lorentz covariance from Wigner functions of spin-1/2 massless fermions in a constant background electromagnetic field. It contains vorticity terms and a four-dimensional Euclidean Berry monopole which gives an axial anomaly. By integrating out the zeroth component of the 4-momentum p, we reproduce the previous three-dimensional results derived from the Hamiltonian approach, together with the newly derived vorticity terms. The phase space continuity equation has an anomalous source term proportional to the product of electric and magnetic fields (FσρF[over ˜]σρ∼EσBσ). This provides a unified interpretation of the chiral magnetic and vortical effects, chiral anomaly, Berry curvature, and the Berry monopole in the framework of Wigner functions.

ConvNeXt steel slag sand substitution rate detection method incorporating attention mechanism.

The proportion of natural sand replaced by steel slag sand affects the volumetric stability of steel slag mortar and steel slag concrete. However, the steel slag substitution rate detection method is inefficient and lacks representative sampling. Therefore, a deep learning-based steel slag sand substitution rate detection method is proposed. The technique adds a squeeze and excitation (SE) attention mechanism to the ConvNeXt model to improve the model's efficiency in extracting the color features of steel slag sand mix. Meanwhile, the model's accuracy is further enhanced by using the migration learning method. The experimental results show that SE can effectively help ConvNeXt acquire images' color features. The model's accuracy in predicting the replacement rate of steel slag sand is 87.99%, which is better than the original ConvNeXt network and other standard convolutional neural networks. After using the migration learning training method, the model predicts the steel slag sand substitution rate with 92.64% accuracy, improving accuracy by 4.65%. The SE attention mechanism and the migration learning training method can help the model acquire the critical features of the image better and effectively improve the model's accuracy. The method proposed in this paper can identify the steel slag sand substitution rate quickly and accurately and can be used for the detection of the steel slag sand substitution rate.