Advances in ultrasound-targeted microbubble-mediated gene therapy for liver fibrosis

Hepatic fibrosis develops as a wound-healing scar in response to acute and chronic liver inflammation and can lead to cirrhosis in patients with chronic hepatitis B and C. The condition arises due to increased synthesis and reduced degradation of extracellular matrix (ECM) and is a common pathological sequela of chronic liver disease. Excessive deposition of ECM in the liver causes liver dysfunction, ascites, and eventually upper gastrointestinal bleeding as well as a series of complications. However, fibrosis can be reversed before developing into cirrhosis and has thus been the subject of extensive researches particularly at the gene level. Currently, therapeutic genes are imported into the damaged liver to delay or prevent the development of liver fibrosis by regulating the expression of exogenous genes. One technique of gene delivery uses ultrasound targeting of microbubbles combined with therapeutic genes where the time and intensity of the ultrasound can control the release process. Ultrasound irradiation of microbubbles in the vicinity of cells changes the permeability of the cell membrane by its cavitation effect and enhances gene transfection. In this paper, recent progress in the field is reviewed with emphasis on the following aspects: the types of ultrasound microbubbles, the construction of an ultrasound-mediated gene delivery system, the mechanism of ultrasound microbubble–mediated gene transfer and the application of ultrasound microbubbles in the treatment of liver fibrosis

Molecular regulatory mechanism of LILRB4 in the immune response

Immune diseases are caused by the imbalance of immune regulation. This imbalance is regulated by many factors, both negative and positive. Leukocyte immunoglobulin-like receptor B4 (LILRB4) is a member of leukocyte immunoglobulin-like receptors (LILRs). LILRs are expressed constitutively on the surface of multiple immune cells which associate with membrane adaptors to signal through multi- ple cytoplasmic immunoreceptor tyrosine-based inhibitory motifs (ITIMs) or immunoreceptor tyro-sine-based activation motifs (ITAMs). Through ITIM, LILRB4 could recruit the src homology domain type-2-containing tyrosine phosphatase 1 or 2 (SHP-1 or SHP-2) into the cell membrane. In addition, many factors can induce the expression of LILRB4, such as vitamin D, interferon and so on. Studies have demonstrated that LILRB4 had a negative regulatory role in various of immune diseases. The present review intends to expound the structure and function of LILRB4, as well as its regulators and receptors in the immune cells, so as to provide a theoretical basis for immune disease therapy

The diabetes medication canagliflozin promotes mitochondrial remodelling of adipocyte via the AMPK-Sirt1-Pgc-1α signalling pathway

The diabetes medication canagliflozin (Cana) is a sodium glucose cotransporter 2 (SGLT2) inhibitor acting by increasing urinary glucose excretion and thus reducing hyperglycaemia. Cana treatment also reduces body weight. However, it remains unclear whether Cana could directly work on adipose tissue. In the present study, the pharmacological effects of Cana and the associated mechanism were investigated in adipocytes and mice. Stromal-vascular fractions (SVFs) were isolated from subcutaneous adipose tissue and differentiated into mature adipocytes. Our results show that Cana treatment directly increased cellular energy expenditure of adipocytes by inducing mitochondrial biogenesis independently of SGLT2 inhibition. Along with mitochondrial biogenesis, Cana also increased mitochondrial oxidative phosphorylation, fatty acid oxidation and thermogenesis. Mechanistically, Cana promoted mitochondrial biogenesis and function via an Adenosine monophosphate-activated protein kinase (AMPK) – silent information regulator 1 (Sirt1) – peroxisome proliferator-activated receptor γ coactivator-1α (Pgc-1α) signalling pathway. Consistently, in vivo study demonstrated that Cana increased AMPK phosphorylation and the expression of Sirt1 and Pgc-1α. The present study reveals a new therapeutic function for Cana in regulating energy homoeostasis. Abbreviations: Ucp-1, uncoupling protein 1; cAMP, cyclic adenosine monophosphate; PKA, cAMP-dependent protein kinase A; SGLT, sodium glucose cotransporter; Cana, canagliflozin; T2DM: type 2 diabetes; Veh, vehicle; Pgc-1α, peroxisome proliferator-activated receptor γ coactivator-1α; SVFs, stromal-vascular fractions; FBS, bovine serum; Ad, adenovirus; mtDNA, mitochondrial DNA; COX2, cytochrome oxidase subunit 2; RT-PCR, real-time PCR; SDS-PAGE, sodium dodecyl sulphate-polyacrylamide gel electrophoresis; Prdm16, PR domain zinc finger protein 16; Cidea, cell death inducing DFFA-like effector A; Pgc-1β, peroxisome proliferator-activated receptor γ coactivator-1β; NRF1, nuclear respiratory factor 1; Tfam, mitochondrial transcription factor A; OXPHOS, oxidative phosphorylation; FAO, fatty acid oxidation; AMPK, Adenosine monophosphate-activated protein kinase; p-AMPK, phosphorylated AMPK; Sirt1, silent information regulator 1; mTOR, mammalian target of rapamycin; WAT, white adipose tissue; Fabp4, fatty acid binding protein 4; Lpl, lipoprotein lipase; Slc5a2, solute carrier family 5 member 2; ERRα, oestrogen related receptor α; Uqcrc2, ubiquinol-cytochrome c reductase core protein 2; Uqcrfs1, ubiquinol-cytochrome c reductase, Rieske iron-sulphur polypeptide 1; Cox4, cytochrome c oxidase subunit 4; Pparα, peroxisome proliferator activated receptor α; NAD+, nicotinamide adenine dinucleotide; Dio2, iodothyronine deiodinase 2; Tmem26, transmembrane protein 26; Hoxa9, homeobox A9; FCCP, carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone; Rot/AA, rotenone/antimycin A; OCR, oxygen consumption rate; Pparγ, peroxisome proliferator activated receptor γ; C/ebp, CCAAT/enhancer binding protein; LKB1, liver kinase B1; AUC, area under the cure; Vd, apparent volume of distribution

Technology roadmap for flexible sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.Agency for Science, Technology and Research (A*STAR)National Research Foundation (NRF)Submitted/Accepted versionY.L., Z.L., M.Z., and X.C. acknowledge the National Research Foundation, Singapore (NRF) under NRF’s Medium Sized Centre: Singapore Hybrid-Integrated Next-Generation μElectronics (SHINE) Centre funding programme, and AME programming funding scheme of Cyber Physiochemical Interface (CPI) project (no. A18A1b0045). Y.L. acknowledges National Natural Science Foundation of China (62201243). C.J. acknowledges funding support from the National Key R&D Program of China (no. 2019YFA0706100), the National Natural Science Foundation of China (82151305), Lingang Laboratory (LG-QS-202202-09). T.Q.T. and N.E.L. acknowledge support by the Basic Science Research Program (no. 2020R1A2C3013480) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT. A.F. acknowledges the AFOSR (grant FA9550-22-1-0423). Y.L. and Y.Z. would like to acknowledge the NSF (award no. 2134664) and NIH (award no. R01HD108473) for financial support. X.F. acknowledges the support from the National Natural Science Foundation of China (grant no. U20A6001). L.Y. would like to thank the A*STAR Central Research Fund (CRF) and the AME Programmatic A18A1b0045 (Cyber Physiochemical Interfaces) for funding support. C.F.G. acknowledges the National Natural Science Foundation of China (no. T2225017). T.Q.T. acknowledges the Brain Pool Program (No. 2020H1D3A2A02111068) through the National Research Foundation (NRF) funded by the Ministry of Science. Z.L. acknowledges the support from RIE2020 AME Programmatic Grant funded by A*STAR-SERC, Singapore (Grant No. A18A1b0045). X.G. acknowledges funding support through the Shanghai Science and Technology Commission (grant no. 19JC1412400), the National Science Fund for Excellent Young Scholars (grant no. 61922057). C.D. acknowledges National Science Foundation CAREER: Conformable Piezoelectrics for Soft Tissue Imaging (grant no. 2044688) and MIT Media Lab Consortium funding. D.K. and O.G.S. acknowledge Leibniz Association and the German Research Foundation DFG (Gottfried Wilhelm Leibniz Program SCHM 1298/22-1, KA5051/1-1 and KA 5051/3-1), as well as the Leibniz association (Leibniz Transfer Program T62/2019). C.W. acknowledges the National Key Research and Development Program of China (grant no. 2021YFA1202600), National Natural Science Foundation of China (grant no. 62174082). A.V.-Y.T., E.Z., Y.Z., X.Z., and J.P. acknowledge the National Research Foundation, Singapore (NRF) under NRF’s Medium Sized Centre: Singapore Hybrid-Integrated Next-Generation μElectronics (SHINE) Centre funding programme, and AME programming funding scheme of Cyber Physiochemical Interface (CPI) project (no. A18A1b0045). R.Z. acknowledges National Natural Science Foundation of China (grant no. 51735007) and Beijing Natural Science Foundation (grant no. 3191001). N.M. acknowledges the support by JST PRESTO Grant Number JPMJPR20B7 and JST Adaptable and Seamless Technology transfer Program through Target-driven R&D (ASTEP) grant number JPMJTM22BK. C.P. acknowledges the Korean government (Ministry of Science and ICT, MSIT) (2022R1A4A3032923). M.W. acknowledges the National Key R&D Program of China under Grant (2021YFB3601200). X.Z. acknowledges National Natural Science Foundation of China (no. 62074029). S.X. acknowledges the 3M nontenured faculty award. T.-W.L. and D.-G.S. acknowledge the Pioneer Research Center Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (grant no. NRF-2022M3C1A3081211). C.T.L. would like to acknowledge support from the Institute for Health Innovation and Technology (iHealthtech), the MechanoBioEngineering Laboratory at the Department of Biomedical Engineering and the Institute for Functional Intelligent Materials (I-FIM) at the National University of Singapore (NUS). C.T.L. also acknowledges support from the National Research Foundation and A*STAR, under its RIE2020 Industry Alignment Fund − Industry Collaboration Projects (IAF-ICP) (grant no. I2001E0059) − SIA-NUS Digital Aviation Corp Lab and the NUS ARTIC Research (grant no. HFM-RP1). X.Y. acknowledges funding support by City University of Hong Kong (grant no. 9667221). T.X. and X.Z. acknowledge National Natural Science Foundation of China (22234006). B.C.K.T. acknowledges Cyber-Physiochemical Interfaces CPI, A*STAR A18A1b0045. H.G. acknowledges a research start-up grant (002479-00001) from Nanyang Technological University and the Agency for Science, Technology and Research (A*STAR) in Singapore. W.G. acknowledges National Science Foundation grant 2145802. D.J.L. acknowledges support from the US National Science Foundation grant number CBET-2223566. G.Y. acknowledges support from The Welch Foundation award F-1861, and Camille Dreyfus Teacher-Scholar Award. M.D.D. acknowledges funding support from NSF (grant no. EEC1160483). J.-H.A acknowledges the National Research Foundation of Korea (NRF-2015R1A3A2066337). J.C. acknowledges the Henry Samueli School of Engineering & Applied Science and the Department of Bioengineering at the University of California, Los Angeles for startup support and a Brain & Behavior Research Foundation Young Investigator Grant. K.T. acknowledges JST AIP Accelerated Program (no. JPMJCR21U1) and JSPS KAKENHI (grant no. JP22H00594). P.S.W. acknowledges the National Science Foundation (CMMI1636136) for support. A.M.A., M.C.H., and P.S.W. thank the National Institute on Drug Abuse (DA045550) for support. S.M. and X.C. appreciated the support from the Smart Grippers for Soft Robotics (SGSR) Programme under the National Research Foundation, Prime Minister’s Office, Singapore under its Campus of Research Excellence and Technological Enterprise (CREATE) programme