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Hepatocellular carcinoma (HCC) is linked to inflammation and immunosuppression. Chemerin is highly expressed in the liver and implicated in the regulation of inflammation. However, the role of chemerin in HCC remains unclear. In this study, we aimed to investigate whether chemerin is able to influence HCC progression by regulating tumor-associated inflammation. Here we demonstrated that chemerin significantly decreased in blood and tumor tissues of HCC patients, and tumor chemerin levels were inversely associated with the prognosis. In an orthotopic mouse model of HCC, Rarres2 −/− mice exhibited aggressive tumor growth and lung metastasis, whereas chemerin overexpression greatly inhibited tumor growth. The tumor-inhibitory effect of chemerin was accompanied by a shift in tumor-infiltrating immune cells from myeloid-derived suppressive cells (MDSCs) to interferon-γ + T cells and decreased tumor angiogenesis. Furthermore, we demonstrated that the tumor-inhibitory effect of chemerin was partly dependent on T cells, as chemerin overexpression could inhibit tumor growth, albeit to a lesser extent, in Rag1 −/− mice when compared with wild-type controls. Mechanistically, chemerin inhibited nuclear factor-κB activation and the expression of granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin-2 (IL-6) by tumor cells and tumor-associated endothelial cell, respectively, via its receptors, and consequently, MDSC induction was impaired, leading to restoration of antitumor T-cell response and decreased tumor angiogenesis. Clinically, systemic and tumor levels of chemerin were found to inversely correlate with circulating concentrations of GM-CSF or IL-6 and tumor-infiltrating myeloid cells, respectively, in HCC patients. Moreover, neutralization of GM-CSF and IL-6 abrogated HCC progression and MDSC accumulation in Rarres2 −/− mice. In conclusion, our study reveals the tumor-inhibitory effect of chemerin by suppressing inflammatory tumor microenvironment with therapeutic implications for inflammation-associated cancer-like HCC.

Fatigue resistance of nitinol stents implanted in femoropopliteal arteries is a critical issue because of their harsh biomechanical environment. Limb flexions due to daily walk expose the femoropopliteal arteries and, subsequently, the implanted stents to large cyclic deformations, which may lead to fatigue failure of the smart self-expandable stents. For the first time, this paper utilised the up-to-date measurements of walk-induced motion of a human femoropopliteal artery to investigate the fatigue behaviour of nitinol stent after implantation. The study was carried out by modelling the processes of angioplasty, stent crimping, self-expansion and deformation under diastolic-systolic blood pressure, repetitive bending, torsion and axial compression as well as their combination. The highest risk of fatigue failure of the nitinol stent occurs under a combined loading condition, with the bending contributing the most, followed by compression and torsion. The pulsatile blood pressure alone hardly causes any fatigue failure of the stent. The work is significant for understanding and improving the fatigue performance of nitinol stents through innovative design and procedural optimisation.

Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy’s utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable. Quantitative phase imaging suffers from a lack of specificity in label-free imaging. Here, the authors introduce Phase Imaging with Computational Specificity (PICS), a method that combines phase imaging with machine learning techniques to provide specificity in unlabeled live cells with automatic training.

Aposematic organisms defend themselves through various means to increase their unprofitability to predators which they advertise with conspicuous warning signals. Predators learn to avoid aposematic prey through associative learning that leads to lower predation. However, when these visual signals become unreliable (e.g., through automimicry or Batesian mimicry), predators may switch from using visual signals to taste sampling prey to choose among them. In this experiment, we tested this possibility in a field experiment where we released a total of 4800 mealworm prey in two clusters consisting of either: (i) undefended prey (injected with water) and (ii) model-mimics (injected with either quinine sulphate [models] or water [mimics]). Prey were deployed at 12 sites, with the mimic frequency of the model-mimics ranging between 0 and 1 (at 0.2 intervals). We found that taste rejection peaked at moderate mimic frequencies (0.4 and 0.6), supporting the idea that taste sampling and rejection of prey is related to signal reliability and predator uncertainty. This is the first time that taste-rejection has been shown to be related to the reliability of prey signals in a mimetic prey system.

Coronavirus disease 2019 (COVID-19) is a global health threat. A hospital in Zhuhai adopted several measures in Fever Clinic Management (FCM) to respond to the outbreak of COVID-19. FCM has been proved to be effective in preventing nosocomial cross infection. Faced with the emergency, the hospital undertook creative operational steps in relation to the control and spread of COVID-19, with special focuses on physical and administrative layout of buildings, staff training and preventative procedures. The first operational step was to set up triaging stations at all entrances and then complete a standard and qualified fever clinic, which was isolated from the other buildings within our hospital complex. Secondly, the hospital established its human resource reservation for emergency response and the allocation of human resources to ensure strict and standardised training methods through the hospital for all medical staff and ancillary employees. Thirdly, the hospital divided the fever clinic into partitioned areas and adapted a three-level triaging system. The experiences shared in this paper would be of practical help for the facilities that are encountering or will encounter the challenges of COVID-19, i.e. to prevent nosocomial cross infection among patients and physicians.

Considerable attention has been given in the past few years to two-dimensional electron gases formed at the interface between two bulk insulators. It is now shown that a similar electronic system can be created on the surface of an oxide insulator simply by exposure to UV light. Many-body interactions in transition-metal oxides give rise to a wide range of functional properties, such as high-temperature superconductivity 1 , colossal magnetoresistance 2 or multiferroicity 3 . The seminal recent discovery of a two-dimensional electron gas (2DEG) at the interface of the insulating oxides LaAlO 3 and SrTiO 3 (ref.  4 ) represents an important milestone towards exploiting such properties in all-oxide devices 5 . This conducting interface shows a number of appealing properties, including a high electron mobility 4 , 6 , superconductivity 7 and large magnetoresistance 8 , and can be patterned on the few-nanometre length scale. However, the microscopic origin of the interface 2DEG is poorly understood. Here, we show that a similar 2DEG, with an electron density as large as 8×10 13  cm −2 , can be formed at the bare SrTiO 3 surface. Furthermore, we find that the 2DEG density can be controlled through exposure of the surface to intense ultraviolet light. Subsequent angle-resolved photoemission spectroscopy measurements reveal an unusual coexistence of a light quasiparticle mass and signatures of strong many-body interactions.

The thermoelectric performance of materials relies substantially on the band structures that determine the electronic and phononic transports, while the transport behaviors compete and counter-act for the power factor PF and figure-of-merit ZT . These issues make a full-scale computation of the whole set of thermoelectric parameters particularly attractive, while a calculation scheme of the electronic and phononic contributions to thermal conductivity remains yet challenging. In this work, we present a full-scale computation scheme based on the first-principles calculations by choosing a set of doped half-Heusler compounds as examples for illustration. The electronic structure is computed using the WIEN2k code and the carrier relaxation times for electrons and holes are calculated using the Bardeen and Shockley’s deformation potential (DP) theory. The finite-temperature electronic transport is evaluated within the framework of Boltzmann transport theory. In sequence, the density functional perturbation combined with the quasi-harmonic approximation and the Klemens’ equation is implemented for calculating the lattice thermal conductivity of carrier-doped thermoelectric materials such as Ti-doped NbFeSb compounds without losing a generality. The calculated results show good agreement with experimental data. The present methodology represents an effective and powerful approach to calculate the whole set of thermoelectric properties for thermoelectric materials.

Breast carcinoma invasion is associated with prominent alterations in stromal fibroblasts. Carcinoma-associated fibroblasts (CAF) support and promote tumorigenesis, whereas normal mammary fibroblasts (NF) are thought to suppress tumor progression. Little is known about the difference in gene expression between CAF and NF or the patient-to-patient variability in gene expression. Paired CAF and NF were isolated from six primary human breast carcinoma specimens. RNA was extracted from low-passage cultures of CAF and NF and analyzed with Affymetrix Human Genome U133 Plus 2.0 arrays. The array data were examined with an empirical Bayes model and filtered according to the posterior probability of equivalent expression and fold difference in expression. Twenty-one genes (27 probe sets) were up-regulated in CAF, as compared with NF. Known functions of these genes relate to paracrine or intracellular signaling, transcriptional regulation, extracellular matrix and cell adhesion/migration. Ten genes (14 probe sets) were down-regulated in CAF, including the pluripotency transcription factor KLF4. Quantitative RT–PCR analysis of 10 genes validated the array results. Immunohistochemical staining for three gene products confirmed stromal expression in terms of location and relative quantity. Surprisingly, the variability of gene expression was slightly higher in NF than in CAF, suggesting inter-individual heterogeneity of normal stroma.

Using finite element method, this paper evaluates damage in an arterial wall and plaque caused by percutaneous coronary intervention. Hyperelastic damage models, calibrated with experimental results, are used to describe stress–stretch responses of arterial layers and plaque; these models are capable to simulate softening behaviour of the tissue due to damage. Abaqus CAE is employed to create the finite element models for the artery wall (with media and adventitia layers), a symmetric uniform plaque, a bioresorbable polymeric stent and a tri-folded expansion balloon. The effect of percutaneous coronary intervention on vessel damage is investigated by simulating the processes of vessel pre-dilation, stent deployment and post-stenting dilation. Energy dissipation density is used to assess the extent of damage in the tissue. Softening of the plaque and the artery, due to the pre-dilation-induced damage, can facilitate the subsequent stent deployment process. The plaque and the artery experienced heterogeneous damage behaviour after the stent deployment, caused by non-uniform deformation. The post-stenting dilation was effective to achieve a full expansion of the stent, but caused additional damage to the artery. The continuous and discontinuous damage models yielded similar results in the percutaneous coronary intervention simulations, while the incorporation of plaque rupture affected the simulated outcomes of stent deployment. The computational evaluation of the artery damage can be potentially used to assess the risk of in-stent restenosis after percutaneous coronary intervention.