Extracellular Matrix Protein Tenascin C Increases Phagocytosis Mediated by CD47 Loss of Function in Glioblastoma.

Glioblastomas (GBM) are highly infiltrated by myeloid-derived innate immune cells that contribute to the immunosuppressive nature of the brain tumor microenvironment (TME). CD47 has been shown to mediate immune evasion, as the CD47-SIRPα axis prevents phagocytosis of tumor cells by macrophages and other myeloid cells. In this study, we established CD47 homozygous deletion (CD47-/-) in human and mouse GBM cells and investigated the impact of eliminating the "don't eat me" signal on tumor growth and tumor-TME interactions. CD47 knockout (KO) did not significantly alter tumor cell proliferation in vitro but significantly increased phagocytosis of tumor cells by macrophages in cocultures. Compared with CD47 wild-type xenografts, orthotopic xenografts derived from CD47-/- tumor cells grew significantly slower with enhanced tumor cell phagocytosis and increased recruitment of M2-like tumor-associated microglia/macrophages (TAM). CD47 KO increased tumor-associated extracellular matrix protein tenascin C (TNC) in xenografts, which was further examined in vitro. CD47 loss of function upregulated TNC expression in tumor cells via a Notch pathway-mediated mechanism. Depletion of TNC in tumor cells enhanced the growth of CD47-/- xenografts in vivo and decreased the number of TAM. TNC knockdown also inhibited phagocytosis of CD47-/- tumor cells in cocultures. Furthermore, TNC stimulated release of proinflammatory factors including TNFα via a Toll-like receptor 4 and STAT3-dependent mechanism in human macrophage cells. These results reveal a vital role for TNC in immunomodulation in brain tumor biology and demonstrate the prominence of the TME extracellular matrix in affecting the antitumor function of brain innate immune cells. SIGNIFICANCE: These findings link TNC to CD47-driven phagocytosis and demonstrate that TNC affects the antitumor function of brain TAM, facilitating the development of novel innate immune system-based therapies for brain tumors

PAK1IP1, a ribosomal stress-induced nucleolar protein, regulates cell proliferation via the p53–MDM2 loop

Cell growth and proliferation are tightly controlled via the regulation of the p53–MDM2 feedback loop in response to various cellular stresses. In this study, we identified a nucleolar protein called PAK1IP1 as another regulator of this loop. PAK1IP1 was induced when cells were treated with chemicals that disturb ribosome biogenesis. Overexpression of PAK1IP1 inhibited cell proliferation by inducing p53-dependent G1 cell-cycle arrest. PAK1IP1 bound to MDM2 and inhibited its ability to ubiquitinate and to degrade p53, consequently leading to the accumulation of p53 levels. Interestingly, knockdown of PAK1IP1 in cells also inhibited cell proliferation and induced p53-dependent G1 arrest. Deficiency of PAK1IP1 increased free ribosomal protein L5 and L11 which were required for PAK1IP1 depletion-induced p53 activation. Taken together, our results reveal that PAK1IP1 is a new nucleolar protein that is crucial for rRNA processing and plays a regulatory role in cell proliferation via the p53–MDM2 loop

Genome Wide Association Identifies PPFIA1 as a Candidate Gene for Acute Lung Injury Risk Following Major Trauma

Acute Lung Injury (ALI) is a syndrome with high associated mortality characterized by severe hypoxemia and pulmonary infiltrates in patients with critical illness. We conducted the first investigation to use the genome wide association (GWA) approach to identify putative risk variants for ALI. Genome wide genotyping was performed using the Illumina Human Quad 610 BeadChip. We performed a two-stage GWA study followed by a third stage of functional characterization. In the discovery phase (Phase 1), we compared 600 European American trauma-associated ALI cases with 2266 European American population-based controls. We carried forward the top 1% of single nucleotide polymorphisms (SNPs) at p<0.01 to a replication phase (Phase 2) comprised of a nested case-control design sample of 212 trauma-associated ALI cases and 283 at-risk trauma non-ALI controls from ongoing cohort studies. SNPs that replicated at the 0.05 level in Phase 2 were subject to functional validation (Phase 3) using expression quantitative trait loci (eQTL) analyses in stimulated B-lymphoblastoid cell lines (B-LCL) in family trios. 159 SNPs from the discovery phase replicated in Phase 2, including loci with prior evidence for a role in ALI pathogenesis. Functional evaluation of these replicated SNPs revealed rs471931 on 11q13.3 to exert a cis-regulatory effect on mRNA expression in the PPFIA1 gene (p = 0.0021). PPFIA1 encodes liprin alpha, a protein involved in cell adhesion, integrin expression, and cell-matrix interactions. This study supports the feasibility of future multi-center GWA investigations of ALI risk, and identifies PPFIA1 as a potential functional candidate ALI risk gene for future research

Expert Consensus on Microtransplant for Acute Myeloid Leukemia in Elderly Patients -Report From the International Microtransplant Interest Group

Recent studies have shown that microtransplant (MST) could improve outcome of patients with elderly acute myeloid leukemia (EAML). To further standardize the MST therapy and improve outcomes in EAML patients, based on analysis of the literature on MST, especially MST with EAML from January 1st, 2011 to November 30th, 2022, the International Microtransplant Interest Group provides recommendations and considerations for MST in the treatment of EAML. Four major issues related to MST for treating EAML were addressed: therapeutic principle of MST (1), candidates for MST (2), induction chemotherapy regimens (3), and post-remission therapy based on MST (4). Others included donor screening, infusion of donor cells, laboratory examinations, and complications of treatment

Time Reversal Imaging Based on Synchronism

A new time-reversal (TR) imaging procedure is proposed in this letter. The traditional TR imaging method shows a snapshot of the amplitude values of the time-reversed retransmitted signals from the TR mirror (TRM) at a specified instant. The present approach gives the image based on the fact that the retransmitted signals from individual elements of the TRM achieve their maximum values synchronously at target positions but non-synchronously at nontarget positions. That is, a target is located based on whether the retransmitted signals achieve their maximum values at the same instant at the point. A grouping technique that divides the TRM into many sub-TRMs is devised to discriminate multitargets by further enhancing the synchronism at target positions. A normalization scheme is introduced to permit all targets to be displayed at the same visibility to avoid swamping of farther or weaker targets by nearer or stronger ones. Several examples are provided to validate the proposed method and its merits.NSFC Project [61531001, 61271032]SCI(E)ARTICLE2058-20611

MAGNETIC FIELD INDUCED BY WAKE OF MOVING BODY IN WIND WAVES (Invited Paper)

A general procedure to evaluate the electromagnetic fields generated by moving seawater through the geomagnetic field is proposed. It contains two essential steps: modeling of velocity vector of seawater according to its dynamic mechanism, and solution of Maxwell equations under a stratified ocean configuration. Two kinds of motions are considered in this work, wind-driven waves and wakes due to a moving body. The ocean is taken to be infinitely deep at the moment. Both the velocity vector and magnetic field are expressed as superposition of sinusoidal waves. Simulation results show that the magnetic fields produced by moderate wind waves or a typical size body moving at moderate speed are on the order of a few hundred pico-Tesla near the sea level. The spectrum characteristics of the two kind magnetic anomalies are distinct.Engineering, Electrical &amp; ElectronicPhysics, AppliedTelecommunicationsSCI(E)[email protected]

TIME DOMAIN INTEGRAL EQUATION APPROACH FOR ANALYSIS OF TRANSIENT RESPONSES BY METALLIC-DIELECTRIC COMPOSITE BODIES

A time domain integral equation approach for analysis of transient responses by 3D composite metallic-dielectric bodies is proposed, which is formulated using the surface equivalent polarization and magnetization as unknown functions. The time domain electric field integral equation is adopted for the metallic part, while the time domain Piggio-Miller-Chang-Harrington-Wu integral equations are adopted for the dielectric part-The spatial and temporal basis functions are the Rao-Wilton-Glisson functions and quadratic Bspline functions, respectively-Numerical examples are provided to demonstrate the stability and accuracy of the proposed method-No late-time instability is encountered, and the results are found in good agreements with analytical or moment method solutions.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000265387700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, Electrical &amp; ElectronicPhysics, AppliedTelecommunicationsSCI(E)EI14ARTICLE1-148

USING WAVE-COEFFICIENTS AS FEATURE VECTORS TO IDENTIFY AEROSPACE TARGETS

An original target identification method using Wave-Coefficients (WCs) as feature vector is proposed. The scattering fields of arbitrary shaped targets are expressed as a sum of spherical waves and the distinctive coefficients are exploited as the target feature. Decision rule based on correlation coefficient is established, and some analyses on the properties of the WCs are conducted. Numerical simulations of four targets are carried out and the recognition performances without and with noise are provided and discussed.Engineering, Electrical &amp; ElectronicPhysics, AppliedTelecommunicationsSCI(E)EI0ARTICLE465-48013

Towards an Optimized Distributed Message Queue System for AIoT Edge Computing: A Reinforcement Learning Approach

The convergence of artificial intelligence and the Internet of Things (IoT) has made remarkable strides in the realm of industry. In the context of AIoT edge computing, where IoT devices collect data from diverse sources and send them for real-time processing at edge servers, existing message queue systems face challenges in adapting to changing system conditions, such as fluctuations in the number of devices, message size, and frequency. This necessitates the development of an approach that can effectively decouple message processing and handle workload variations in the AIoT computing environment. This study presents a distributed message system for AIoT edge computing, specifically designed to address the challenges associated with message ordering in such environments. The system incorporates a novel partition selection algorithm (PSA) to ensure message order, balance the load among broker clusters, and enhance the availability of subscribable messages from AIoT edge devices. Furthermore, this study proposes the distributed message system configuration optimization algorithm (DMSCO), based on DDPG, to optimize the performance of the distributed message system. Experimental evaluations demonstrate that, compared to the genetic algorithm and random searching, the DMSCO algorithm can provide a significant improvement in system throughput to meet the specific demands of high-concurrency AIoT edge computing applications