Differential Signal Research Articles

The characteristics of differentiated yeast subpopulations depend on their lifestyle and available nutrients

Yeast populations can undergo diversification during their growth and ageing, leading to the formation of different cell-types. Differentiation into two major subpopulations, differing in cell size and density and exhibiting distinct physiological and metabolic properties, was described in planktonic liquid cultures and in populations of colonies growing on semisolid surfaces. Here, we compare stress resistance, metabolism and expression of marker genes in seven differentiated cell subpopulations emerging during cultivation in liquid fermentative or respiratory media and during colony development on the same type of solid media. The results show that the more-dense cell subpopulations are more stress resistant than the less-dense subpopulations under all cultivation conditions tested. On the other hand, respiratory capacity, enzymatic activities and marker gene expression differed more between subpopulations. These characteristics are more influenced by the lifestyle of the population (colony vs. planktonic cultivation) and the medium composition. Only in the population growing in liquid respiratory medium, two subpopulations do not form as in the other conditions tested, but all cells exhibit a range of characteristics of the more-dense subpopulations. This suggests that signals for cell differentiation may be triggered by prior metabolic reprogramming or by an unknown signal from the structured environment in the colony.

A Spatial Signal of Niche Differentiation in Tropical Forests.

AbstractExplaining diversity in tropical forests remains a challenge in community ecology. Theory tells us that species differences can stabilize communities by reducing competition, while species similarities can promote diversity by reducing fitness differences and thus prolonging the time to competitive exclusion. Combined, these processes may lead to clustering of species such that species are niche differentiated across clusters and share a niche within each cluster. Here, we characterize this partial niche differentiation in a tropical forest in Panama by measuring spatial clustering of woody plants and relating these clusters to local soil conditions. We find that species were spatially clustered and the clusters were associated with specific concentrations of soil nutrients, reflecting the existence of nutrient niches. Species were almost twice as likely to recruit in their own nutrient niche. A decision tree algorithm showed that local soil conditions correctly predicted the niche of the trees with up to 85% accuracy. Iron, zinc, phosphorus, manganese, and soil pH were among the best predictors of species clusters.

Development of Biocompatible Digital Light Processing Resins for Additive Manufacturing Using Visible Light-Induced RAFT Polymerization.

Patients with bone diseases often experience increased bone fragility. When bone injuries exceed the body's natural healing capacity, they become significant obstacles. The global rise in the aging population and the escalating obesity pandemic are anticipated to lead to a notable increase in acute bone injuries in the coming years. Our research developed a novel DLP resin for 3D printing, utilizing poly(ethylene glycol diacrylate) (PEGDA) and various monomers through the PET-RAFT polymerization method. To enhance the performance of bone scaffolds, triply periodic minimal surfaces (TPMS) were incorporated into the printed structure, promoting porosity and pore interconnectivity without reducing the mechanical resistance of the printed piece. The gyroid TPMS structure was the one that showed the highest mechanical resistance (0.94 ± 0.117 and 1.66 ± 0.240 MPa) for both variants of resin composition. Additionally, bioactive particles were introduced to enhance the material's biocompatibility, showcasing the potential for incorporating active compounds for specific applications. The inclusion of bioceramic particles produces an increase of 13% in bioactivity signal for osteogenic differentiation (alkaline phosphatase essay) compared to that of control resins. Our findings highlight the substantial improvement in printing precision and resolution achieved by including the photoabsorber, Rose Bengal, in the synthesized resin. This enhancement allows for creating intricately detailed and accurately defined 3D-printed parts. Furthermore, the TPMS gyroid structure significantly enhances the material's mechanical resistance, while including bioactive compounds significantly boosts the polymeric resin's biocompatibility and bioactivity (osteogenic differentiation).

Soft measurement model for wet gas flow rate based on ultrasonic and differential pressure sensing

Non-separation measurement of gas–liquid two-phase flow is of great significance to industrial production and theoretical research on two-phase flow. In this paper, a soft measurement method of wet gas flow rate based on ultrasonic and differential pressure (DP) sensors is proposed. A total of 129 sets of experimental data are obtained in DN50 horizontal pipe, the superficial velocity of gas and liquid ranging from 5 m s−1 to 33 m s−1 and 0.015 m s−1 to 0.6 m s−1, respectively. Ten feature parameters of ultrasonic signals such as the time difference between two echoes and kurtosis factor are proposed from time and frequency domain. As well as the power spectral density, mean value and standard deviation value are analyzed based on DP signals. Furthermore, the Spearman correlation coefficient is introduced to evaluate these feature parameters quantitatively. And nine parameters which are highly correlated to gas–liquid flow rate are selected as the inputs of the soft measurement model. Finally, Decision Tree, least square support vector machines and artificial neural network (ANN) models are established through training with the experimental data. Comparison results show that ANN has the lowest prediction errors on the test set, with the mean absolute percentage errors of 1.49% and 3.2% for gas and liquid, respectively.

Zero crossing detection algorithm based on an MLP neural network for differential confocal microscopy

Differential confocal microscopy is widely used because of its ultra-high axial resolution. The surface gradient results in light loss, which decreases the slope of the differential response signal at zero crossing. At this point, when the signal-to-noise ratio is fixed, the traditional linear fitting method to determine the position of zero crossing is subject to significant error influence. To solve these issues, this paper proposes a zero crossing detection algorithm based on a multilayer perceptron (MLP) neural network. Experimental results reveal that the proposed algorithm is more robust and capable of better zero crossing extraction. When numerical aperture (NA)=0.4, the average error is 16.9 nm, which is 55.4 % higher than that of the traditional linear fitting algorithm. The proposed algorithm has a high potential for use with the differential confocal sensor to measure unknown steep surfaces.

Network Pharmacology Study to Reveal the Mechanism of Zuogui Pill for Treating Osteoporosis.

To our knowledge, there is still a lack of scientific reports on the pharmacological mechanism of the Zuogui Pill (ZGP) for treating osteoporosis (OP). This study aimed to explore it via network pharmacology and molecular docking. We identified active compounds and associated targets in ZGP via two drug databases. Disease targets of OP were obtained utilizing five disease databases. Networks were established and analyzed through the Cytoscape software and STRING databases. Enrichment analyses were performed using the DAVID online tools. Molecular docking was performed using Maestro, PyMOL, and Discovery Studio software. 89 drug active compounds, 365 drug targets, 2514 disease targets, and 163 drug-disease common targets were obtained. Quercetin, kaempferol, phenylalanine, isorhamnetin, betavulgarin, and glycitein may be the crucial compounds of ZGP in treating OP. AKT1, MAPK14, RELA, TNF, and JUN may be the most important therapeutic targets. Osteoclast differentiation, TNF, MAPK, and thyroid hormone signaling pathways may be the critical therapeutic signaling pathways. The potential therapeutic mechanism mainly relates to osteoblastic or osteoclastic differentiation, oxidative stress, and osteoclastic apoptosis. This study has revealed the anti-OP mechanism of ZGP, which offers objective evidence for relevant clinical application and further basic research.

Software-architectural configuration of the multifunctional audio digital signal processor module for signal mediatesting of audio devices

Objectives. The aim of this study is to develop and analyze parameters for a multifunctional audio module based on the ADAU1701 audio digital signal processor in the SigmaStudio environment. This will be used for testing audio devices in the following modes: routing of balanced and unbalanced audio channels according to the differential scheme Di-Box/R Di-Box; spatiotemporal and dynamic audio processing; three-band monochannel cross-separation with independent equalization; and correction of the frequency response of the audio channel with tracking notch auto-suppression of electro-acoustic positive feedback in a given spectral band.Methods. Visual-graphical architectural programming of audio modules in the SigmaStudio and Flowstone, as well as algorithms for real-time signal audio measurements and analysis of experimental data in the REW and Soundcard Oscilloscope are used.Results. The characteristics of the Di-Box/R Di-Box circuit were studied, in order to estimate the effect of differential signal conversion on the signal-to-noise ratio in the audio signal path. The characteristics of the reverberation and saturation submodules were established. Furthermore, the effect of equalization modes on the frequency response correction of a studio audio monitor was determined. The paper also studied the effect of an audio compressor on the dynamic range and the level of the output signal. The experimental results of the submodule for compensating the frequency response of an audio monitor using matched filtering were established, and the spectral characteristics of the submodule for automatic suppression of electro-acoustic positive feedback were obtained.Conclusions. The software architecture of a multifunctional audio module based on the ADAU1701 audio digital signal processor for testing and debugging media devices in a given spectral-dynamic and spectral-temporal ranges was designed. Balanced routing allows the effect of noise induced into the audio channel to be reduced 20-fold, thus enabling calibration of pickup audio devices. The audio signal processing submodule provides: compression response in the dynamic range from −27 to 18.6 dB with the possibility of equalization parameterization in the range of 0.04–18 kHz; reverberation response in the range from 0.5–3000 ms; audio-channel cross-division into 3 with the ability to adjust the amplitude-frequency response in the dynamic range from −30 to 30 dB. The auto-correction submodule of the amplitude-frequency response allows the dynamic nonuniformity of the amplitude-frequency response to be reduced by 40 dB. The auto-suppression submodule of electro-acoustic positive feedback provides notch formant suppression up to −100 dB with an input dynamic range from −50 to 80 dB.

Wavelength-Resolved Janus Biosensing Interface for Ratiometric Electrochemical Analysis.

The Janus interface, comprising multiple functional heterointerfaces with contrasting functionalities within a single interface, has recently garnered widespread research interest. Herein, a Janus biosensing interface is obtained via wavelength-resolved laser illumination. Deoxyribonucleic acid bridges the electrochemical probe of methylene blue (MB) and plasmonic gold nanoparticles (AuNPs), achieving a sensitive detection performance. MB shows differential electrochemical signals under front (I532front) and back (I650back) laser illumination at 532 and 650 nm, respectively, owing to the selective wavelength-resolved effect. Thus, the presence of a wavelength-resolved laser enabled the design of a biosensing interface with Janus properties. The change in the distance between MB and AuNPs induced by aflatoxin B1 (AFB1) indicates that a sensitive response of the Janus biosensing interface can be achieved. A ratiometric strategy is introduced to describe the electrochemical signals of the I532front and I650back for improved robustness. The obtained linear range is 0.0005-50 ng mL-1, with a detection limit of 0.175 pg mL-1. Our study demonstrated that the wavelength-resolved Janus interface enables an electrochemical biosensor with excellent sensitivity. This finding provides an efficient approach for improving biosensor performance.

Current Distortion and Sensitivity Calibration Problems of Rogowski Coil

Driven by technology, China's power system has been greatly improved, and has been gradually transformed and upgraded, bringing great improvements to performance in all aspects. Current distortion and sensitivity misalignment of Rogowski coils have always been the key problems to be solved in practical applications. This paper summarizes the methods of calibrating the sensitivity of the Rogowski coil in the shape of the single ring arbitrary skeleton, the Rogowski coil of the double ring skeleton and the Rogowski coil in the shape of the round skeleton, which provides the basis for other improvements of the Rogowski coils. The existing method to solve the current distortion of the Rogowski coil has a single method in the output of the differential current signal, which will reduce the limitation of the measurement range, and the suppression problem still cannot be solved well. This paper summarizes the solutions to current distortion in Rogowski coils, introduces the causes and solutions of current sensor and transistor current distortion, and puts forward certain correlations to provide reference and direction for follow-up research.

DOP84 Colonic CD4+ T cell senescence is implicated in the progression of experimental colitis in aged mice

Abstract Background Evidence from recent epidemiological data suggests that the burden of IBD in the elderly is increasing globally. However, the mechanisms underlying the age-related IBD susceptibility remain elusive. Aging leads to a progressive functional decline of the immune system, rendering the elderly increasingly susceptible to autoimmune disease. Herein, we sought to determine the role of immunosenescence in age-dependent colitis and to explore the underlying mechanisms. Methods Young (2-3 months), middle-aged (10-12 months), and aged (20-24 months) mice were established models of colitis by 2% dextran sulfate sodium salt (DSS) treatment. Weight loss, colon length, disease activity indexes (DAI) and histological scores were evaluated to assess the severity of colitis. Using a second-generation fluorogenic substrate for β-galactosidase and multi-parameter flow cytometry, we detected the senescence-associated β-galactosidase (SA-βGal) activity in lymphocytes isolated from colon, including CD4+ T cells, CD8+ T cells, B cells, natural killer cells, microphages, neutrophils and dendritic cells. Based on the immunocytes that exhibit greatest age-related increases in SA-βGal activity, inflammatory cytokines such as TNF-α、IFN-γ、IL-17 were evaluated in senescent immunocytes through flow cytometry. Single-cell and bulk RNA-seq of colonic immune cells in mice with different ages were performed to further investigate the precise molecular mechanisms. Results Ageing increased the severity of DSS-induced colitis wherein aged mice exhibited worsened weight loss, shortened colon length, higher DAI and histological scores compared to young mice. The greatest age-associated increases of SA-βGal activity were observed in colonic CD4+ T cell populations. Additionally, aging resulted in systemic activation of CD4+ T cells, exhibiting an expansion of CD4+ effector memory T (TEM) cells in colon, as well as in spleen. Aged colonic CD4+ T cells generate higher levels of IFN-γ and IL-17 comparing to young colonic CD4+ T cells, especially in status of colitis. Moreover, the accumulated CD4+ TEM cells in the aged colon were the main source of IL-17 production. Single-cell analysis revealed that aging increased colonic CD4+ TEM cells, which were associated with T cell-mediated cytotoxicity and cytokine-mediated signaling pathway. Splenic CD4+ TEM cells isolated from aged colitis mice were confirmed to involve in cellular senescence, Th17 differentiation and inflammatory signaling pathway through bulk RNA-seq. Conclusion These results provide a significant insight into the contribution of senescent CD4+ T cells to age-dependent colitis and provide an attractive possibility that targeting T cell specifically might be a potential strategy to treat elderly IBD patients.

Silencing ANGPTL8 reduces mouse preadipocyte differentiation and insulin signaling

ANGPTL8, expressed mainly in the liver and adipose tissue, regulates the activity of lipoprotein lipase (LPL) present in the extracellular space and triglyceride (TG) metabolism through its interaction with ANGPTL3 and ANGPTL4. Whether intracellular ANGPTL8 can also exert effects in tissues where it is expressed is uncertain. ANGPTL8 expression was low in preadipocytes and much increased during differentiation. To better understand the role of intracellular ANGPTL8 in adipocytes and assess whether it may play a role in adipocyte differentiation, we knocked down its expression in normal mouse subcutaneous preadipocytes. ANGPTL8 knockdown reduced adipocyte differentiation, cellular TG accumulation and also isoproterenol-stimulated lipolysis at day 7 of differentiation. RNA-Seq analysis of ANGPTL8 siRNA or control siRNA transfected SC preadipocytes on days 0, 2, 4 and 7 of differentiation showed that ANGPTL8 knockdown impeded the early (day 2) expression of adipogenic and insulin signaling genes, PPARγ, as well as genes related to extracellular matrix and NF-κB signaling. Insulin mediated Akt phosphorylation was reduced at an early stage during adipocyte differentiation. This study based on normal primary cells shows that ANGPTL8 has intracellular actions in addition to effects in the extracellular space, like modulating LPL activity. Preadipocyte ANGPTL8 expression modulates their differentiation possibly via changes in insulin signaling gene expression.

Phase Separation through Screen Channel Liquid Acquisition Devices in Microgravity

To enable future deep space exploration, orbital refueling of spacecraft is essential. However, transferring liquid in a microgravity environment is a complex process dependent on various factors. One of the basic and critical tasks is to separate phases to allow the supply of gas-free liquid from one tank to another. For this purpose, a liquid acquisition device is essential. In this work, a screen channel liquid acquisition device was designed and used to investigate phase separation and liquid removal from an experiment tank in a microgravity environment. The experiments were performed using the drop tower facility at the University of Bremen, with HFE-7500 as the test liquid under isothermal conditions. This investigation explored the interdependent effects of various phenomena, including the reorientation of liquid in the tank, capillary rise between parallel plates, flow through screen pressure variation, and bubble point breakthrough. Under subcritical conditions, the SC-LAD was found to supply gas-free liquid at the outlet, as long as the pressure drop across the screen was lower than the bubble point threshold. At the critical point, the screen started to ingest bubbles, resulting in a sharp peak in the differential pressure signal. The wetted area of the screen was obtained by analyzing images captured with a high-speed camera and used to calculate the analytical pressure drop. The experimental results were compared with the analytical solution and discussed in detail.

High-precision and high-speed surface topography measurement method of microstructures based on laser scanning transverse differential confocal

The manufacturing of microstructured devices requires higher performance regarding the increasing development of finer structures and more complex structural shapes, which poses a challenge for existing measurement techniques in terms of anti-scattering, high-precision and high-speed. Accordingly, this study proposes a new technology for surface topography measurement of microstructures based on laser scanning transverse differential confocal (LSTDCM), which inserts a D-shaped aperture into the existing confocal system, and performs split-focal spot detection on the focal plane. This method exhibits improved axial resolution by performing differential phase subtraction of the front- and back-focal signals to obtain a highly sensitive axial response signal. Further normalization of the transverse differential confocal signal eliminates the multiplicative noise of the system, avoids the impact of changes in roughness on the measurement results, and achieves an anti-scattering measurement. The linear region of the axial response signal around the zero-crossing point were used to achieve a “non-axial scanning” height measurement, which was combined with high-speed beam lateral scanning to achieve a high-speed areal topography measurement. Theoretical analysis and experimental results indicate that, for samples with height changes within the linear region of axial response, the method can complete areal topography measurement in 1.7 s with the axial resolution of 1 nm and the measurement range of 128 × 128 μm. A microstructured device processed using a nanoform single-point diamond machine tool and a semiconductor wafer were employed in the application validation experiment. And achieve a wide range stitching measurement of 1 mm × 1 mm under a 100 × objective along with the transverse scanning stage. The measurement efficiency is about three times higher than that of Olympus OLS4100 confocal microscope. The method provides a new and effective technical approach that is not limited by the surface roughness and complex structure of the tested devices, and can achieve high-precision as well as high-speed optical nondestructive measurement without moving the tested device. Thus, this work is expected to has important practical applications in the field of ultra-precision measurement.

Features selection for recognition of severe slugging in a long pipeline with an S-shaped riser by decision tree

In deep-sea oil and gas, S-shaped riser is the key equipment to transport the multiphase working substance produced underwater to the surface platform. The occurrence of severe slugging will seriously threaten the safe production of offshore oil and gas fields. Therefore, accurate and rapid recognition of hazardous flow patterns such as severe slugging is an urgent need to ensure the safety of multiphase flow in deep-sea long-distance pipelines. This paper has built a set of long S-shaped riser with industrial parameters, including 1687 m horizontal and downward inclined pipelines and 16.7 m S-shaped riser. The gas-liquid two-phase flow patterns, including severe slugging, oscillating flow and stable flow, are studied in this system. The pressure and differential pressure features of different signals are extracted from different positions along the pipeline, and a more comprehensive and reasonable evaluation criterion of signal performance is established. Making use of the advantages of visualization of the structure of decision tree, a new method to evaluate the recognition effect of features is proposed based on its classification principle. The original signal is decomposed into components of different scales through wavelet multi-scale analysis, and then the statistical features with good flow pattern differentiation ability are calculated. It is found that the mean of wavelet approximate component has the best recognition effect among all features. On the basis of feature correlation analysis, 7 features with high recognition rate applicable to 22 signals along the pipeline are optimally selected from 13 original features. For the water differential pressure signal DP13, the recognition rate obtained by using its 4 optimal features is 91.4 %, and the error between the recognition rate obtained by using all features is only 0.2 %. The overall recognition rate of the signal is the highest and the practicability is the best. When the sample duration is 6.2s, the recognition rate using the optimal feature reaches 90.8 %, thus ensuring the real-time recognition of the flow pattern while obtaining a high recognition rate.

Concepts in B-cell Acute Lymphoblastic Leukemia Pathogenesis.

B-cell acute lymphoblastic leukemia (B-ALL) arises from genetic alterations impacting B-cell progenitors, ultimately leading to clinically overt disease. Extensive collaborative efforts in basic and clinical research have significantly improved patient prognoses. Nevertheless, a subset of patients demonstrate resistance to conventional chemotherapeutic approaches and emerging immunotherapeutic interventions. This review highlights the mechanistic underpinnings governing B-ALL transformation. Beginning with exploring normative B-cell lymphopoiesis, we delineate the influence of recurrent germline and somatic genetic aberrations on the perturbation of B-cell progenitor differentiation and pro-tumorigenic signaling, thereby facilitating the neoplastic transformation underlying B-ALL progression. Additionally, we highlight recent advances in the multifaceted landscape of B-ALL, encompassing metabolic reprogramming, microbiome influences, inflammation, and the discernible impact of socioeconomic and racial disparities on B-ALL transformation and patient survival.

Longitudinal vibration estimation of a mine hoist using a hybrid signal fusion method combining UKF, ND and improved DE

The monitoring of cage longitudinal vibration can directly indicate the operational status of mine hoists. However, it is always challenging to collect the sensor signals of moving cages with high dynamic characteristics in real time from complex working environments using traditional monitoring methods. In this study, a more practical hybrid signal fusion approach is proposed to realize estimation of cage longitudinal vibration from a low sampling rate acceleration acquisition signal and a low cost encoder signal for state estimation. A nonlinear differentiator is applied to extract encoder differential signals and expand observation variables. An unscented Kalman observer based on nonlinear mine hoist model is designed to estimate the unknown state. To overcome the influence of the uncertain parameters, an improved differential evolution (DE) algorithm combining parameter adaptive method, reverse learning competition scheme and multiple parallel populations strategy is proposed to find unknown parameters of the observation model and autotune the parameters of the algorithms by using low sampling rate acceleration. Sensor data of the simulated experiment platform were collected and processed by the xPC system to validate the effectiveness of the proposed strategy. The experimental results showed that the improved DE (IDE) algorithm had a faster mean time for parameter tuning and the smallest fitness value compared to the standard DE, the particle swarm optimization algorithm and the genetic algorithm. Moreover, the longitudinal vibration estimation system, after parameter tuning by the IDE optimization algorithm, could achieve the purpose of signal estimation, with a smaller estimation error and a better estimation effect.

A power transformer differential protection method based on variational mode decomposition and CNN‐BiLSTM techniques

AbstractPower transformers play a critical role in the performance of power systems. This equipment is costly due to significant copper and iron prices and manufacturing costs. Therefore, maintenance and protection of such equipment is essential. Despite its robust performance, maloperation of differential protection (DP) in transformers may cause operational challenges to power system operators. The differential relay may operate incorrectly after the transformer energization leads to an inrush current (IC) and the relay identifies the event as an internal fault, and consequently issues the trip command. The other case of maloperation includes, but not limited to, a moment when the current transformer saturates due to an external fault. In this paper, a novel approach for DP is proposed, that is based on signal processing methods. In this paper, variational mode decomposition (VMD) and the deep neural network are implemented by using the convolutional neural network (CNN) and bi‐directional long short‐term memory (BiLSTM) models. The VMD decomposes differential current signal (DCS) to intrinsic mode functions with corresponding narrow‐band property frequency spectrums, which provides more detailed information about signal characteristics in different frequency bands. At the next stage, an effective feature for the BiLSTM is extracted by the CNN with the convolutional layers to classify events and proper discrimination. Extensive simulations on a 500 MVA transformer in MATLAB demonstrate the effectiveness of the proposed protection approach to differentiate ICs from internal and external faults with 99.8% accuracy in less than 1/8th of a power cycle.

Differential perovskite hemispherical photodetector for intelligent imaging and location tracking

Advanced photodetectors with intelligent functions are expected to take an important role in future technology. However, completing complex detection tasks within a limited number of pixels is still challenging. Here, we report a differential perovskite hemispherical photodetector serving as a smart locator for intelligent imaging and location tracking. The high external quantum efficiency (~1000%) and low noise (10−13 A Hz−0.5) of perovskite hemispherical photodetector enable stable and large variations in signal response. Analysing the differential light response of only 8 pixels with the computer algorithm can realize the capability of colorful imaging and a computational spectral resolution of 4.7 nm in a low-cost and lensless device geometry. Through machine learning to mimic the differential current signal under different applied biases, one more dimensional detection information can be recorded, for dynamically tracking the running trajectory of an object in a three-dimensional space or two-dimensional plane with a color classification function.

Differential Interferon Signaling Regulation and Oxidative Stress Responses in the Cerebral Cortex and Cerebellum Could Account for the Spatiotemporal Pattern of Neurodegeneration in Niemann-Pick Disease Type C.

Niemann-Pick disease type C (NPC) is a fatal neurodegenerative condition caused by genetic mutations of the NPC1 or NPC2 genes that encode the NPC1 and NPC2 proteins, respectively, which are believed to be responsible for cholesterol efflux from late-endosomes/lysosomes. The pathogenic mechanisms that lead to neurodegeneration in NPC are not well understood. There are, however, well-defined spatiotemporal patterns of neurodegeneration that may provide insight into the pathogenic process. For example, the cerebellum is severely affected from early disease stages, compared with cerebral regions, which remain relatively spared until later stages. Using a genome-wide transcriptome analysis, we have recently identified an aberrant pattern of interferon activation in the cerebella of pre-symptomatic Npc1-/- mice. Here, we carried out a comparative transcriptomic analysis of cerebral cortices and cerebella of pre-symptomatic Npc1-/- mice and age-matched controls to identify differences that may help explain the pathological progression within the NPC brain. We report lower cerebral expression of genes within interferon signaling pathways, and significant differences in the regulation of oxidative stress, compared with the cerebellum. Our findings suggest that a delayed onset of interferon signaling, possibly linked to lower oxidative stress, may account for the slower onset of cerebral cortical pathology in the disease.

Defect detection of metallic samples by electromagnetic tomography using closed-loop fuzzy PID-controlled iterative Landweber method

ABSTRACT Electromagnetic tomography (EMT) uses the mutual inductance of the coil to visualise the conductivity distribution of interesting regions. Since the conductivity of defects and metal samples are different, the metal samples with defects can be treated as binary-valued material distributions. This paper investigates the closed-loop fuzzy proportional, integral and derivative (PID)-controlled iterative Landweber method. The whole method includes fuzzy PID controller, the Landweber reconstruction method, and the Dirichlet-to-Neumann map. Specifically, the differential signal between the mutual inductance of the coil and the feedback signal is used as the input of the fuzzy PID controller. The fuzzy controller can automatically adjust three parameters ( K p , K i and K d ) of PID controller. Subsequently, the output of the PID controller can serve as the input of the Landweber algorithm to reconstruct the distribution of conductivity. Furthermore, the Dirichlet-to-Neumann map is used to calculate the mutual inductance, acting as the feedback signal based on the reconstruction conductivity distribution. Finally, both the numerical simulation and experiments are applied to verify the proposed method. The results indicate that the proposed method can reconstruct the image with a clear edge, and the average correlation coefficient can reach 0.792.