Innate immune cells are critical for transplant response. As an important cellular component of innate immune cells, macrophages are the predominate infiltrated cells in allografts, and macrophage accumulation in allografts is negatively associated with the short- and long-term outcomes of organ transplantation. Macrophages are functionally heterogeneous and plastic. They participate in organ graft rejection through multiple pathways, including antigen presentation, the expression of costimulatory molecules and cytokines, and direct cytotoxicity and injury ability to allografts. However, some macrophage subpopulations, such as regulatory macrophages, can protect allografts from immune rejection and promote transplant immune tolerance with their immune regulatory properties. Although researchers recognize the potential roles macrophages play in allograft injury, they pay insufficient attention to the diverse roles of macrophages in allograft rejection. We herein briefly summarize the distinctive roles of macrophages in acute transplant immune response and the effect of immunosuppressive drugs on macrophages. Greater attention should be paid to the complex and critical function of macrophages in allograft rejection, and more effort should be put into developing immunosuppressive drugs that specifically target macrophages, which would ultimately improve the long-term survival of organ grafts in patients.
Chimeric antigen receptors (CARs) are a breakthrough in genetic engineering that have revolutionized the field of adoptive cellular therapy (ACT). Cells expressing these receptors are rerouted to a predefined target by the inclusion of an antigen-specific binding region within the synthetic CAR construct. The advantage of cells with programmed specificity has been demonstrated clinically in the field of oncology, and it is clear that such cells have greater accuracy, potency, and reduced off-target therapeutic effects compared with their unmodified counterparts. In contrast to conventional T cells (Tconvs), regulatory T cells (Tregs) play a major role in suppressing immune activation and regulating the host immune response. CAR expression within Tregs has been proposed as a therapy for autoimmune and inflammatory diseases, graft-versus-host disease (GvHD), and organ transplant rejection. In the latter, they hold immense potential as mediators of immune tolerance for recipients of allotransplants. However, current research into CAR-Treg engineering is extremely limited, and there is uncertainty regarding optimal design for therapeutic use. This review examines the rationale behind the development of CAR-Tregs, their significance for human transplantation, potential designs, safety considerations, and comparisons of CAR-Tregs in transplantation models to date.
Organ transplant rejection (OTR) is a complex immune reaction involving multiple cells, and it determines graft survival and patient prognosis. At present, most transplant recipients are administered a combination of immunosuppressive and biological agents to protect them from OTR. However, immunosuppressive agents negatively impact the immune system of the patients, causing them to suffer from serious complications, such as chronic infection and malignant tumors. Therefore, a thorough understanding of the mechanisms involved in immune tolerance and immune rejection with regard to organ transplant (OT) is essential for developing better treatment options and improving patient outcomes. This article reviews the role of immune cells in OTR and organ transplant tolerance (OTT), including the novel cell therapies that are currently under clinical trials for transplant recipients.
Hepatic malignancy is a major indication for liver transplantation; however, post-transplant cancer recurrence is an emerging clinical challenge affecting long-term outcomes. Pre-transplant tumor biology, staging, and post-transplant immunosuppression regimens have been elucidated as risk factors for recurrent liver cancer. However, increasing evidence indicates that hepatic ischemia and reperfusion (IR) injury to allografts are crucial to providing a favorable immunologic microenvironment for cancer cell invasiveness and metastasis after liver transplantation. The association of severe graft injury in marginal grafts, such as small-for-size or fatty grafts, with lower recurrence-free survival rates in living donor liver transplantations, substantiates the correlation between hepatic IR injury and cancer recurrence. IR have been demonstrated to trigger intrahepatic immunological microenvironment remodeling, including pro-inflammatory responses exacerbating graft injury and anti-inflammatory responses promoting tissue repair. However, the role of regional immunity in post-transplant cancer recurrence is not comprehensively understood. This review describes the up-to-date evidence of the intrahepatic humoral microenvironment and regional regulatory immunological microenvironment induced by IR injury, as well as their roles in cancer recurrence after liver transplantation. A comprehensive understanding of regional immunity will provide novel precise diagnostic, therapeutic, and prognostic strategies for post-transplant cancer recurrence.
Controlling the immune response with only clinically approved immunosuppressant drugs is difficult in renal heterotransplantation from pigs to nonhuman primates. Moreover, to the best of our knowledge, no reports exist on the use of fetal pigs as kidney donors. This study aimed to compare the degree of transplant rejection between neonatal and fetal kidneys, with genetically unmodified pigs as donors and cynomolgus monkeys as recipients. The left kidneys of the recipient monkeys were removed, followed by transplantation of neonatal as well as fetal pig kidneys, which had undergone vascular anastomosis at the same site, into the retroperitoneum. Immunosuppression was performed with only US Food and Drug Administration-approved drugs. The fetal kidneys were transplanted into the omentum and paraaortic regions of cynomolgus monkeys. Consequently, the engraftment and development of the transplanted tissues were pathologically examined by sampling over time (twice in each experiment). An acute rejection was observed after a few weeks in neonatal renal grafts with vascular anastomosis. However, fetal pig kidneys were spared from rejection despite the administration of the same immunosuppressive protocol to the monkeys and the recipient blood vessels flowing into the fetal kidneys. The immunogenicity of fetal kidneys in pig–monkey renal heterotransplantation was lower than that of neonatal kidneys.
In this paper, we perform two-layer high-throughput calculations. In the first layer, which involves changing the crystal structure and/or chemical composition, we analyze selected III–V semiconductors, filled and unfilled skutterudites, as well as rock salt and layered chalcogenides. The second layer searches the full Brillouin zone (BZ) for critical points within 1.5 eV (1 eV = 1.602176 × 10−19 J) of the Fermi level and characterizes those points by computing the effective masses. We introduce several methods to compute the effective masses from first principles and compare them to each other. Our approach also includes the calculation of the density-of-states effective masses for warped critical points, where traditional approaches fail to give consistent results due to an underlying non-analytic behavior of the critical point. We demonstrate the need to consider the band structure in its full complexity and the value of complementary approaches to compute the effective masses. We also provide computational evidence that warping occurs only in the presence of degeneracies.
High-throughput powder X-ray diffraction (XRD) with white X-ray beam and an energy-dispersive detector array are demonstrated in this work on a CeO2 powder sample on a bending magnet synchrotron beamline at the Shanghai Synchrotron Radiation Facility (SSRF), using a simulated energy-dispersive array detector consisting of a spatially scanning silicon-drift detector (SDD). Careful analysis and corrections are applied to account for various experimental hardware-related and diffraction angle-related factors. The resulting diffraction patterns show that the relative strength between different diffraction peaks from energy-dispersive XRD (EDXRD) spectra is consistent with that from angle-resolved XRD (ARXRD), which is necessary for analyzing crystal structures for unknown samples. The X-ray fluorescence (XRF) signal is collected simultaneously. XRF counts from all pixels are integrated directly by energy, while the diffraction spectra are integrated by d-spacing, resulting in a much improved peak strength and signal-to-noise (S/N) ratio for the array detector. In comparison with ARXRD, the diffraction signal generated by a white X-ray beam over monochromic light under the experimental conditions is about 104 times higher. The full width at half maximum (FWHM) of the peaks in q-space is found to be dependent on the energy resolution of the detector, the angle span of the detector, and the diffraction angle. It is possible for EDXRD to achieve the same or even smaller FWHM as ARXRD under the energy resolution of the current detector if the experimental parameters are properly chosen.
Building processing, structure, and property (PSP) relations for computational materials design is at the heart of the Materials Genome Initiative in the era of high-throughput computational materials science. Recent technological advancements in data acquisition and storage, microstructure characterization and reconstruction (MCR), machine learning (ML), materials modeling and simulation, data processing, manufacturing, and experimentation have significantly advanced researchers' abilities in building PSP relations and inverse material design. In this article, we examine these advancements from the perspective of design research. In particular, we introduce a data-centric approach whose fundamental aspects fall into three categories: design representation, design evaluation, and design synthesis. Developments in each of these aspects are guided by and benefit from domain knowledge. Hence, for each aspect, we present a wide range of computational methods whose integration realizes data-centric materials discovery and design.
Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error. Herein, a methodology combining domain knowledge, a machine learning algorithm, and experiments is presented for accelerating the discovery of novel energetic materials. A high-throughput virtual screening (HTVS) system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established. With the proposed HTVS system, candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25 112 molecules. Furthermore, a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results, thus verifying the effectiveness of the proposed methodology. This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.
Cell rotation is one of the most important techniques for cell manipulation in modern bioscience, as it not only permits cell observation from any arbitrary angle, but also simplifies the procedures for analyzing the mechanical properties of cells, characterizing cell physiology, and performing microsurgery. Numerous approaches have been reported for rotating cells in a wide range of academic and industrial applications. Among them, the most popular are micro-robot-based direct contact manipulation and field-based non-contact methods (e.g., optical, magnetic, electric, acoustic, and hydrodynamic methods). This review first summarizes the fundamental mechanisms, merits, and demerits of these six main groups of approaches, and then discusses their differences and limitations in detail. We aim to bridge the gap between each method and illustrate the development progress, current advances, and prospects in the field of cell rotation.
Regulatory science is a discipline that uses comprehensive methods of natural science, social science, and humanities to provide support for administrative decision-making through the development of new tools, standards, and approaches to assess the safety, efficacy, quality, and performance of regulated products. During the pandemics induced by infectious diseases, such as H1N1 flu, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS), regulatory science strongly supported the development of drugs and vaccines to respond to the viruses. In particular, with the support of research on drug regulatory science, vaccines have played a major role in the prevention and control of coronavirus disease 2019 (COVID-19). This review summarizes the overall state of the vaccine industry, research and development (R&D) of COVID-19 vaccines in China, and the general state of regulatory science and supervision for vaccines in China. Further, this review highlights how regulatory science has promoted the R&D of Chinese COVID-19 vaccines, with analyses from the aspects of national-level planning, relevant laws and regulations, technical guidelines, quality control platforms, and post-marketing supervision. Ultimately, this review provides a reference for the formulation of a vaccine development strategy in response to the current pandemic and the field of vaccine development in the post-pandemic era, as well as guidance on how to better respond to emerging and recurring infectious diseases that may occur in the future.
The rapid development of artificial intelligence (AI) facilitates various applications from all areas but also poses great challenges in its hardware implementation in terms of speed and energy because of the explosive growth of data. Optical computing provides a distinctive perspective to address this bottleneck by harnessing the unique properties of photons including broad bandwidth, low latency, and high energy efficiency. In this review, we introduce the latest developments of optical computing for different AI models, including feedforward neural networks, reservoir computing, and spiking neural networks (SNNs). Recent progress in integrated photonic devices, combined with the rise of AI, provides a great opportunity for the renaissance of optical computing in practical applications. This effort requires multidisciplinary efforts from a broad community. This review provides an overview of the state-of-the-art accomplishments in recent years, discusses the availability of current technologies, and points out various remaining challenges in different aspects to push the frontier. We anticipate that the era of large-scale integrated photonics processors will soon arrive for practical AI applications in the form of hybrid optoelectronic frameworks.
Klebsiella pneumoniae (K. pneumonia, KpI) is a predominate inducement of bovine mastitis, which is associated with high mortality and milk yield reduction. However, data is lacking on the molecular characteristics of bovine K. pneumoniae, limiting the risk assessment of its transmission through the food chain. Herein, we investigated the prevalence of K. pneumoniae in 6301 clinical mastitis (CM) milk samples from dairy cattle in northern area of China. In total, 183 K. pneumoniae isolates were recovered, with detection rates of 3.0% and 2.8% in 2018 and 2019, respectively. Like human clinical K. pneumoniae, all CM K. pneumoniae isolates belonged to one of three phylogroups: KpI (n = 143), Klebsiella quasipneumoniae subsp. similipneumoniae (KpII-B) (n = 37), and Klebsiella variicola (KpIII) (n = 3). We detected the extendedspectrum β-lactamase-encoding genes blaSHV-2a, blaCTX-M-14, and blaCTX-M-15, as well as clpC, lpfA, lacI, lacZ, lacY, and the fecABDEIR operon in the KpI isolates, which may contribute to their pathogenicity and host adaptability in cows. The high prevalence of KpI in dairy farms may be problematic, as it showed relatively higher rates of antibiotic resistance and virulence gene carriage than the KpII-B and KpIII isolates. Furthermore, we observed distinct differences in population structure between CM- and human infection-associated KpI isolates, with the genes associated with invasive infection in humans rarely being observed in bovine isolates, indicating that few CM-associated K. pneumoniae isolates pose a threat to human health. Nevertheless, bovine KpII-B isolates shared a high level of nucleotide sequence identity with isolates from human infections and frequently carried the nitrogen-fixation gene nif, suggesting an association between KpII-B isolates from cattle and humans, and plant-derived bacteria.
The recent outbreak of coronavirus disease 2019 (COVID-19) and concerns about several other pandemics in the 21st century have attracted extensive global attention. These emerging infectious diseases threaten global public health and raise urgent studies on unraveling the underlying mechanisms of their transmission from animals to humans. Although numerous works have intensively discussed the cross-species and endemic barriers to the occurrence and spread of emerging infectious diseases, both types of barriers play synergistic roles in wildlife habitats. Thus far, there is still a lack of a complete understanding of viral diffusion, migration, and transmission in ecosystems from a macro perspective. In this review, we conceptualize the ecological barrier that represents the combined effects of cross-species and endemic barriers for either the natural or intermediate hosts of viruses. We comprehensively discuss the key influential factors affecting the ecological barrier against viral transmission from virus hosts in their natural habitats into human society, including transmission routes, contact probability, contact frequency, and viral characteristics. Considering the significant impacts of human activities and global industrialization on the strength of the ecological barrier, ecological barrier deterioration driven by human activities is critically analyzed for potential mechanisms. Global climate change can trigger and expand the range of emerging infectious diseases, and human disturbances promote higher contact frequency and greater transmission possibility. In addition, globalization drives more transmission routes and produces new high-risk regions in city areas. This review aims to provide a new concept for and comprehensive evidence of the ecological barrier blocking the transmission and spread of emerging infectious diseases. It also offers new insights into potential strategies to protect the ecological barrier and reduce the wide-ranging risks of emerging infectious diseases to public health.
Personal thermal management is emerging as a promising strategy to provide thermal comfort for the human body while conserving energy. By improving control over the heat dissipating from the human body, personal thermal management can provide effective personal cooling and warming. Here, we propose a facile surface modification approach to tailor the thermal conduction and radiation properties based on commercially available fabric, to realize better management of the whole heat transport pathway from the human body to the ambient. A bifunctional asymmetric fabric (BAF) offering both a cooling and a warming effect is demonstrated. Due to the advantages of roughness asymmetry and surface modification, the BAF demonstrates an effective cooling effect through enhanced heat conduction and radiation in the cooling mode; in the warming mode, heat dissipation along both routes is reduced for personal warming. As a result, a 4.6 °C skin temperature difference is measured between the cooling and warming BAF modes, indicating that the thermal comfort zone of the human body can be enlarged with one piece of BAF clothing. We expect this work to present new insights for the design of personal thermal management textiles as well as a novel solution for the facile modification of available fabrics for both personal cooling and warming.
Secondary amyloid A amyloidosis, a lethal complication, is induced when acute or chronic infection coexists with over-secretion of the serum amyloid A 1 (SAA1) protein and deposition in key internal organs. Previously, using the whole-exome sequencing method, we identified a novel deleterious mutation SAA1.2 in rheumatoid arthritis (RA) patients. However, the role of SAA1 in RA pathogenesis and its complications remains unknown. The purpose of this study was to determine the pathogenetic roles of SAA1 protein isoforms in RA progression. We modified an experimental adenovirus infection protocol to introduce SAA1.2 gene alleles into the knee joints of mice and used SAA1.3 and SAA1.5 as controls. Micro-computed tomography analysis was applied to determine changes in bone morphology and density. Immunohistochemical (IHC) analysis, flow cytometry, enzyme-linked immunosorbent assay (ELISA), and real-time polymerase chain reaction (RT-PCR) were used to investigate disease progression and cytokine alterations in the course of adenoviral SAA-induced knee joint inflammation and bone destruction. We found that the arthritis-inducing effect of SAA1.2 transcription in the knee joints and mutant SAA1 protein secretion in blood resulted in the stimulation of immune responses, leading to CD8+ T cell and pro-inflammatory cytokine elevation, such as interleukin (IL)-6, IL-22, matrix metalloproteinase (MMP)-3, MMP-9, with subsequent synovial inflammation and bone destruction. These findings indicate that SAA1 protein isoforms, particularly SAA1.2, play a significant role in the induction and progression of RA and may have potential value in the early diagnosis and severity prediction of RA.