Mast cell ontogeny: From fetal development to life‐long health and disease

Summary Mast cells (MCs) are evolutionarily ancient innate immune cells with important roles in protective immunity against bacteria, parasites, and venomous animals. They can be found in most organs of the body, where they also contribute to normal tissue functioning, for example by engaging in crosstalk with nerves. Despite this, they are most widely known for their detrimental roles in allergy, anaphylaxis, and atopic disease. Just like macrophages, mast cells were conventionally thought to originate from the bone marrow. However, they are already present in fetal tissues before the onset of bone marrow hematopoiesis, questioning this dogma. In recent years, our view of myeloid cell ontogeny has been revised. We now know that the first mast cells originate from progenitors made in the extra‐embryonic yolk sac, and later get supplemented with mast cells produced from subsequent waves of hematopoiesis. In most connective tissues, sizeable populations of fetal‐derived mast cells persist into adulthood, where they self‐maintain largely independently from the bone marrow. These developmental origins are highly reminiscent of macrophages, which are known to have critical functions in development. Mast cells too may thus support healthy development. Their fetal origins and longevity also make mast cells susceptible to genetic and environmental perturbations, which may render them pathological. Here, we review our current understanding of mast cell biology from a developmental perspective. We first summarize how mast cell populations are established from distinct hematopoietic progenitor waves, and how they are subsequently maintained throughout life. We then discuss what functions mast cells may normally have at early life stages, and how they may be co‐opted to cause, worsen, or increase susceptibility to disease

Community-onset bacteremia in kidney transplant recipients: The recipients fare well in terms of mortality and kidney injury

BackgroundBloodstream infection is not uncommon in kidney transplant recipients (KTRs) and is associated with mortality, graft loss, and increased medical expenses. Whether these septic patients are more vulnerable to serious complications, resistant strains, or worse clinical outcomes than other patient groups in the community-onset settings remains undetermined.MethodsA retrospective study was conducted at a medical center in southern Taiwan. Community-onset bacteremia in the KTRs and a control population at the emergency department were identified. Demographic data, clinical characteristics, bacteremic pathogens, antimicrobial resistance, and clinical outcomes were recorded.ResultsForty-one bacteremic episodes in the KTRs and 82 episodes in control patients were studied. The KTR group had younger age, fewer malignancies, more urosepsis (61% vs. 22%, p = 0.004), and fewer biliary tract infections (0% vs. 13.4%, p = 0.018). Escherichia coli was the most commonly isolated pathogen in both the groups (51.2% and 41.5%, respectively). No Klebsiella pneumoniae bacteremia was noted in the KTRs, compared with 14 (17.1%) episodes in the control group (p = 0.010). Antimicrobial resistance profiles of bacteremic pathogens were similar (all p > 0.6). The KTRs with community-onset bacteremia did not have a worse outcome (in-hospital mortality rate: 2.4% vs. 10%, p = 0.172) nor more incomplete resolution of kidney injury after acute kidney injury events (21.1% vs. 25%, p > 0.99) than the control group.ConclusionKTRs with community-onset bacteremia did not fare worse in terms of clinical outcome and kidney injury

An Artificial Neural Network Embedded Position and Orientation Determination Algorithm for Low Cost MEMS INS/GPS Integrated Sensors

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated

Inferring nonneutral evolution from contrasting patterns of polymorphisms and divergences in different protein coding regions of enterovirus 71 circulating in Taiwan during 1998-2003

<p>Abstract</p> <p>Background</p> <p>Enterovirus (EV) 71 is one of the common causative agents for hand, foot, and, mouth disease (HFMD). In recent years, the virus caused several outbreaks with high numbers of deaths and severe neurological complications. Despite the importance of these epidemics, several aspects of the evolutionary and epidemiological dynamics, including viral nucleotide variations within and between different outbreaks, rates of change in immune-related structural regions vs. non-structural regions, and forces driving the evolution of EV71, are still not clear.</p> <p>Results</p> <p>We sequenced four genomic segments, i.e., the 5' untranslated region (UTR), VP1, 2A, and 3C, of 395 EV71 viral strains collected from 1998 to 2003 in Taiwan. The phylogenies derived from different genomic segments revealed different relationships, indicating frequent sequence recombinations as previously noted. In addition to simple recombinations, exchanges of the P1 domain between different species/genotypes of human enterovirus species (HEV)-A were repeatedly observed. Contrasting patterns of polymorphisms and divergences were found between structural (VP1) and non-structural segments (2A and 3C), i.e., the former was less polymorphic within an outbreak but more divergent between different HEV-A species than the latter two. Our computer simulation demonstrated a significant excess of amino acid replacements in the VP1 region implying its possible role in adaptive evolution. Between different epidemic seasons, we observed high viral diversity in the epidemic peaks followed by severe reductions in diversity. Viruses sampled in successive epidemic seasons were not sister to each other, indicating that the annual outbreaks of EV71 were due to genetically distinct lineages.</p> <p>Conclusions</p> <p>Based on observations of accelerated amino acid changes and frequent exchanges of the P1 domain, we propose that positive selection and subsequent frequent domain shuffling are two important mechanisms for generating new genotypes of HEV-A. Our viral dynamics analysis suggested that the importation of EV71 from surrounding areas likely contributes to local EV71 outbreaks.</p

The prediction of Alzheimer’s disease through multi-trait genetic modeling

To better capture the polygenic architecture of Alzheimer’s disease (AD), we developed a joint genetic score, MetaGRS. We incorporated genetic variants for AD and 24 other traits from two independent cohorts, NACC (n = 3,174, training set) and UPitt (n = 2,053, validation set). One standard deviation increase in the MetaGRS is associated with about 57% increase in the AD risk [hazard ratio (HR) = 1.577, p = 7.17 E-56], showing little difference from the HR for AD GRS alone (HR = 1.579, p = 1.20E-56), suggesting similar utility of both models. We also conducted APOE-stratified analyses to assess the role of the e4 allele on risk prediction. Similar to that of the combined model, our stratified results did not show a considerable improvement of the MetaGRS. Our study showed that the prediction power of the MetaGRS significantly outperformed that of the reference model without any genetic information, but was effectively equivalent to the prediction power of the AD GRS