Experimental Evidence For the Peptide Competition Between Type 1 Diabetes Associated HLA-DQ8 and DR4 Molecules

Among the public health relevant disorders, Type 1 Diabetes (T1D) is a degenerative disease affecting almost 2 million Americans. It is characterized by the loss of insulin-producing b-cells due to a T cell-mediated autoimmune response. The risk to develop T1D is HLA associated. HLA-DQ8-DR4 has been identified as the most prevalent HLA haplotype in the Caucasian T1D population. Although DQ8 has been demonstrated to be the primary genetic determinant of disease susceptibility, its predisposing effect is likely modulated by the expression of closely linked DR4 alleles. As one of hypotheses to explain the role of DR4 molecules in T1D etiology, the peptide competition model holds that DR4 competes to bind diabetogenic peptides with DQ8 and thus affects DQ8-restricted autoreactive CD4 T cell responses. However, the evidence of the competition is insufficient due to the lack of detection reagents and the difficulty of segregating the expression of DR4 from DQ8. In this study, we investigated the competition of peptides derived from Glutamic Acid Decarboxylase 65 (GAD65) - a putative b-cell autoantigen. A panel of DQ8-restricted T cell lines was generated to serve as detection reagents to evaluate the peptide occupancy of DQ8. After demonstrating that a single peptide derived from GAD65 could bind both HLA-DQ8 and HLA-DR4, we compared CD4 T cell responses elicited by antigen presenting cells expressing DQ8 alone with those expressing DQ8 and DR4 simultaneously. Results indicated that the co-expression of HLA-DR4 diminished DQ8-restricted T cell responses. In addition, distinct DR4 subtypes were demonstrated to affect DQ8-restricted T cell responses differently, suggesting the variable degrees of peptide competition potentials. Taken together, this study provides the evidence that DR4 is able to compete for peptides with DQ8. The outcome of this competition decreases DQ8-restricted CD4 T cell responses, which may hence contribute to a peripheral tolerance mechanism and explain the modulating role of DR4 to the DQ8-conferred T1D susceptibility

Peptide-MHC Cellular Microarray with Innovative Data Analysis System for Simultaneously Detecting Multiple CD4 T-Cell Responses

Peptide:MHC cellular microarrays have been proposed to simultaneously characterize multiple Ag-specific populations of T cells. The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation. T cell cultures. A novel statistical methodology was also developed to facilitate batch processing of raw array-like data into standardized endpoint scores, which linearly correlated with total Ag-specific T cell inputs. Applying these methods to analyze Influenza A viral antigen-specific T cell responses, we not only revealed the most prominent viral epitopes, but also demonstrated the heterogeneity of anti-viral cellular responses in healthy individuals. Applying these methods to examine the insulin producing beta-cell autoantigen specific T cell responses, we observed little difference between autoimmune diabetic patients and healthy individuals, suggesting a more subtle association between diabetes status and peripheral autoreactive T cells.The data analysis system is reliable for T cell specificity and functional testing. Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings

Association between dietary habits and the risk of migraine: a Mendelian randomization study

ObjectiveThe important contribution of dietary triggers to migraine pathogenesis has been recognized. However, the potential causal roles of many dietary habits on the risk of migraine in the whole population are still under debate. The objective of this study was to determine the potential causal association between dietary habits and the risk of migraine (and its subtypes) development, as well as the possible mediator roles of migraine risk factors.MethodsBased on summary statistics from large-scale genome-wide association studies, we conducted two-sample Mendelian randomization (MR) and bidirectional MR to investigate the potential causal associations between 83 dietary habits and migraine and its subtypes, and network MR was performed to explore the possible mediator roles of 8 migraine risk factors.ResultsAfter correcting for multiple testing, we found evidence for associations of genetically predicted coffee, cheese, oily fish, alcohol (red wine), raw vegetables, muesli, and wholemeal/wholegrain bread intake with decreased risk of migraine, those odds ratios ranged from 0.78 (95% CI: 0.63–0.95) for overall cheese intake to 0.61 (95% CI: 0.47–0.80) for drinks usually with meals among current drinkers (yes + it varies vs. no); while white bread, cornflakes/frosties, and poultry intake were positively associated with the risk of migraine. Additionally, genetic liability to white bread, wholemeal/wholegrain bread, muesli, alcohol (red wine), cheese, and oily fish intake were associated with a higher risk of insomnia and (or) major depression disorder (MDD), each of them may act as a mediator in the pathway from several dietary habits to migraine. Finally, we found evidence of a negative association between genetically predicted migraine and drinking types, and positive association between migraine and cups of tea per day.SignificanceOur study provides evidence about association between dietary habits and the risk of migraine and demonstrates that some associations are partly mediated through one or both insomnia and MDD. These results provide new insights for further nutritional interventions for migraine prevention

Low-voltage overhead lines topology identification method based on high-frequency signal injection

The topology of low-voltage distribution systems changes with the load or the on/off position of the circuit switch. This will affect power flows, losses, and so on. This paper submits a new method to identify the topology of a low-voltage feeder using the injection high-frequency signal. An inductor can block the high-frequency signal. It can change the propagation direction of the injected high-frequency signal to make it propagate unidirectionally along the low-voltage feeder. By injecting a 5 MHz sinusoidal signal from the upstream direction of the low-voltage feeder, all the line segments and devices on the feeder can be identified. The wavelength of the high-frequency signal is short. The wavelength of the 5 MHz signal is 60 meters. Through the delay of different observation points on the feeder, the length of the line section can be roughly calculated. The high- frequency signal has an obvious reflection on the feeder. Using this feature, we can roughly calculate the length of the line segment. The correctness of the method is demonstrated by MATLAB simulation verification

Topology identification of low voltage distribution network based on current injection method

The structure of the low-voltage distribution network often changes. The change of topology will affect fault detection, fault location, line loss calculation, etc. It leads to fault detection error, inaccurate positioning and abnormal line loss calculation. This paper presents a new method to automatically identify the topology of a low-voltage power grid by using the injection current signal. When the disturbance current signal is injected into the low-voltage line, the current upstream of the injection point will change, and the current downstream of the injection point will not be affected. It is proved theoretically by using the superposition principle. With this method, the disturbance current signal can be injected into the line in turn, and the topology can be identified by observing the change of the current in line. The correctness of the method is proved by Matlab simulation and laboratory verification

Feeder Topology Configuration and Application Based on IEC 61850

Distribution automation (DA) and Internet of Things (IoT) all need the topology information of power distribution network to support some applications, such as fault diagnosis, network reconfiguration and optimization. IEC 61850 is a general communication model and standard for information exchange between intelligent electronic devices (IEDs). However, it has no mechanism for feeder topology information exchange. This paper solves this problem by developing the corresponding information model. Firstly, a feeder model is established as a container of the equipment along a distribution line. Secondly, logical models, such as terminal and connection nodes, are added to describe the physical connection relationship between the electrical equipment. Taking a circuit breaker as an example, this paper introduces how to add the terminal attribute to an existing logical node (XCBR). The physical connection between the circuit breaker and other electrical equipment is described by adding the logic node LCNN. Then, a new logical node LTPN is added to describe the logical connection between the devices. A new logical node, FTPA, is added to describe the status of the topology analysis and the topology results. Based on these new logical nodes, this paper proposes the mechanism of topology information exchange between IEDs. Three IEDs and the IEEE 13-node model are used to build an experimental environment. The result verifies the effectiveness of this method. More distributed applications can be used to test the validity and interoperability of the proposed model

Do biodegradable microplastics cause soil inorganic carbon loss in calcareous soils?

The presence of biodegradable microplastics (MPs) has the potential to affect soil pH, and possibly accelerate or inhibit the loss of soil inorganic carbon (SIC) in calcareous soils. However, most researchers have focused on the release of biotic carbon dioxide (CO2) from soils following MP amendments, and few studies have investigated SIC-derived CO2. In this experiment, three typical biodegradable MPs were applied to three calcareous soils amended with 1 % 13C-labeled (99 % atom) carbonate, and the release of CO2 originating from SIC was quantified. The total CO2 emissions, soil pH, and microbial functional genes involved in soil nitrification and denitrification were also detected. Throughout the experiment, the contribution of 13C-labeled carbonate to total CO2 emissions ranged from 0.42 % to 3.31 %. The impact of biodegradable MPs on SIC-derived CO2 varied with incubation period. At the early stage (≤20 days), the amendment of three biodegradable MPs increased the abiotic CO2 in some cases, and the CO2 emissions from 13C-labeled SIC were positively correlated with the total CO2 originating from the decomposition of SOC and MPs. At the late stage (20–70 days), the presence of biodegradable MPs inhibited the release of CO2 from 13C-labeled carbonate in most treatments. Moreover, there were negative relationships of SIC-derived CO2 with soil pH and the amoA gene of ammonia-oxidizing archaea (AOA), but positive correlations of SIC-derived CO2 with amoA of ammonia oxidizing bacteria (AOB) and nirK and nirS genes encoding nitrate reductase in denitrification. Our results indicate that long-term exposure to biodegradable MPs probably regulates the release of H+ in the nitrification process by controlling AOB, and then controlling the dynamics of SIC in calcareous soils

Assessment of Seasonal Influenza A Virus-Specific CD4 T-Cell Responses to 2009 Pandemic H1N1 Swine-Origin Influenza A Virus▿ †

Very limited evidence has been reported to show human adaptive immune responses to the 2009 pandemic H1N1 swine-origin influenza A virus (S-OIV). We studied 17 S-OIV peptides homologous to immunodominant CD4 T epitopes from hemagglutinin (HA), neuraminidase (NA), nuclear protein (NP), M1 matrix protein (MP), and PB1 of a seasonal H1N1 strain. We concluded that 15 of these 17 S-OIV peptides would induce responses of seasonal influenza virus-specific T cells. Of these, seven S-OIV sequences were identical to seasonal influenza virus sequences, while eight had at least one amino acid that was not conserved. T cells recognizing epitopes derived from these S-OIV antigens could be detected ex vivo. Most of these T cells expressed memory markers, although none of the donors had been exposed to S-OIV. Functional analysis revealed that specific amino acid differences in the sequences of these S-OIV peptides would not affect or partially affect memory T-cell responses. These findings suggest that without protective antibody responses, individuals vaccinated against seasonal influenza A may still benefit from preexisting cross-reactive memory CD4 T cells reducing their susceptibility to S-OIV infection