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Background Acupuncture is widely used for therapeutic purposes, but the neural mechanisms underlying its effects are not fully understood. This study aims to investigate the neural projections from acupoints and subcutaneous (sham acupoints) sites to the central nervous system, using retrograde tracing technology, to clarify the specificity of acupuncture's neural pathways. Methods Adult C57BL/6J mice were injected with the retrograde tracer PRV‐CAG‐3 × mScarlet at seven acupoints (LI4, GV20, LI11, BL23, LR3, ST25, ST36) and their corresponding subcutaneous sites (sham acupoints). After 120 h, the brains were processed to assess viral expression and neural projections using histological analysis and imaging techniques. Results The results revealed differences in neural projections between the acupoint groups and their corresponding subcutaneous sites. Acupoints exhibited common neural projections to regions such as the primary motor cortex (M1), secondary motor cortex (M2), gigantocellular reticular nucleus (Gi), and ventrolateral periaqueductal gray (VLPAG), while subcutaneous sites showed more diffuse and less specific projections. Conclusions Compared to subcutaneous injection sites (sham acupoints), acupoints exhibit common neural projections in the brain. In contrast to the more diffuse neural projection patterns observed in subcutaneous sites (sham acupoints), acupoints display more numerous and specific neural projections in the brain. Retrograde viral tracing reveals that acupoints project to common and specific brain regions, while subcutaneous (sham) sites display more diffuse and inconsistent patterns, highlighting the neural specificity of acupuncture pathways.

Given a complex simple Lie algebra g and a positive integer ℓ , under the assumption λ ≫ μ , we show that irreducible representations of g of the form V ( λ + w μ ) , w ∈ W , with level at most ℓ appear in the fusion product of V ( λ ) and V ( μ ) . This verifies the existence of PRV components for the fusion product in this special case.

Despite the notable recent developments in the field of remote photoplethysmography (rPPG), extracting a reliable pulse rate variability (PRV) signal still remains a challenge. In this study, eight image-based photoplethysmography (iPPG) extraction methods (GRD, AGRD, PCA, ICA, LE, SPE, CHROM, and POS) were compared in terms of pulse rate (PR) and PRV features. The algorithms were made robust for motion and illumination artifacts by using ad hoc pre- and postprocessing steps. Then, they were systematically tested on the public dataset UBFC-RPPG, containing data from 42 subjects sitting in front of a webcam (30 fps) while playing a time-sensitive mathematical game. The performances of the algorithms were evaluated by statistically comparing iPPG-based and finger-PPG-based PR and PRV features in terms of Spearman’s correlation coefficient, normalized root mean square error (NRMSE), and Bland–Altman analysis. The study revealed POS and CHROM techniques to be the most robust for PR estimation and the assessment of overall autonomic nervous system (ANS) dynamics by using PRV features in time and frequency domains. Furthermore, we demonstrated that a reliable characterization of the vagal tone is made possible by computing the Poincaré map of PRV series derived from the POS and CHROM methods. This study supports the use of iPPG systems as promising tools to obtain clinically useful and specific information about ANS dynamics.

The non-invasiveness of photoplethysmographic (PPG) acquisition systems, together with their cost-effectiveness and easiness of connection with IoT technologies, is opening up to the possibility of their widespread use. For this reason, the study of the reliability of PPG and pulse rate variability (PRV) signal quality has become of great scientific, technological, and commercial interest. In this field, sensor location has been demonstrated to play a crucial role. The goal of this study was to investigate PPG and PRV signal quality acquired from two body locations: finger and wrist. We simultaneously acquired the PPG and electrocardiographic (ECG) signals from sixteen healthy subjects (aged 28.5 ± 3.5, seven females) who followed an experimental protocol of affective stimulation through visual stimuli. Statistical tests demonstrated that PPG signals acquired from the wrist and the finger presented different signal quality indexes (kurtosis and Shannon entropy), with higher values for the wrist-PPG. Then we propose to apply the cross-mapping (CM) approach as a new method to quantify the PRV signal quality. We found that the performance achieved using the two sites was significantly different in all the experimental sessions (p < 0.01), and the PRV dynamics acquired from the finger were the most similar to heart rate variability (HRV) dynamics.

Cardiac monitoring based on wearable photoplethysmography (PPG) is widespread because of its usability and low cost. Unfortunately, PPG is negatively affected by various types of disruptions, which could introduce errors to the algorithm that extracts pulse rate variability (PRV). This study aims to identify the nature of such artifacts caused by various types of factors under the conditions of precisely planned experiments. We also propose methods for their reduction based solely on the PPG signal while preserving the frequency content of PRV. The accuracy of PRV derived from PPG was compared to heart rate variability (HRV) derived from the accompanying ECG. The results indicate that filtering PPG signals using the discrete wavelet transform and its inverse (DWT/IDWT) is suitable for removing slow components and high-frequency noise. Moreover, the main benefit of amplitude demodulation is better preparation of the PPG to determine the duration of pulse cycles and reduce the impact of some other artifacts. Post-processing applied to HRV and PRV indicates that the correction of outliers based on local statistical measures of signals and the autoregressive (AR) model is only important when the PPG is of low quality and has no effect under good signal quality. The main conclusion is that the DWT/IDWT, followed by amplitude demodulation, enables the proper preparation of the PPG signal for the subsequent use of PRV extraction algorithms, particularly at rest. However, post-processing in the proposed form should be applied more in the situations of observed strong artifacts than in motionless laboratory experiments.

Porcine pseudorabies (PR) is an important infectious disease caused by pseudorabies virus (PRV), which poses a major threat to food safety and security. Vaccine immunization has become the main means to prevent and control the disease. However, since 2011, a new PRV variant has caused huge economic losses to the Chinese pig industry. Panax notoginseng polysaccharides have immunomodulatory activity and other functions, but the antiviral effect has not been reported. We studied the anti-PRV activity of Panax notoginseng polysaccharides in vitro. A less cytopathic effect was observed by increasing the concentration of Panax notoginseng polysaccharides. Western blot, TCID50, plaque assay, and IFA revealed that Panax notoginseng polysaccharides could significantly inhibit the infectivity of PRV XJ5 on PK15 cells. In addition, we also found that Panax notoginseng polysaccharides blocked the adsorption and replication of PRV to PK15 cells in a dose-dependent manner. These results show that Panax notoginseng polysaccharides play an antiviral effect mainly by inhibiting virus adsorption and replication in vitro. Therefore, Panax notoginseng polysaccharides may be a potential anti-PRV agent.

Porcine circovirus 2 (PCV2) and pseudorabies virus (PRV) are economically important pathogens in swine. PCV2 and PRV coinfection can cause more severe neurological and respiratory symptoms and higher mortality of piglets. However, the exact mechanism involved in the coinfection of PRV and PCV2 and its pathogenesis remain unknown. Here, porcine kidney cells (PK-15) were infected with PCV2 and/or PRV, and then the activation of immune and inflammatory pathways was evaluated to clarify the influence of the coinfection on immune and inflammatory responses. We found that the coinfection of PCV2 and PRV can promote the activation of nuclear factor-κB (NF-κB), c-Jun N-terminal protein kinases (JNK), p38, and nod-like receptor protein 3 (NLRP3) pathways, thus enhancing the expression of interferon-γ (IFN-γ), interferon-λ1 (IFN-λ1), interferon-stimulated gene (ISG15), interleukin 6 (IL6), and interleukin 1β (IL1β). Meanwhile, PCV2 and PRV also inhibit the expression and signal transduction of IFN-β, tumor necrosis factor α (TNFα), and the Janus kinase-signal transducer and activator of transcription (JAK/STAT) pathway. In addition, PCV2 and PRV infection can also weaken extracellular-signal-regulated kinase (ERK) activity. These results indicate that the regulations of cellular antiviral immune responses and inflammatory responses mediated by NF-κB, JAK/STAT, mitogen-activated protein kinase (MAPK), and NLRP3 pathways, contribute to immune escape of PCV2 and PRV and host antiviral responses.

Pressure reducing valves (PRVs) are essentially used to reduce operational pressures in water distribution systems (WDSs) to minimize water leakage. However, water age in a WDS is an important variable describing the water quality and should be kept as low as possible. Therefore, the aim of this study is to investigate the possibility and potential of simultaneously minimizing both pressure and water age by using PRVs. To determine the optimal location and setting of PRVs, a mixed-integer nonlinear programming (MINLP) problem is formulated with minimization of the sum of the weighted total water age and pressure as the objective function, where the weighting factor can be defined by the user’s preference. The equality constraints consist of the hydraulic equations and water age functions to describe pressure and water age in the distribution network, while the inequality constraints ensure them in the defined operating ranges, respectively. Applying the proposed approach to two case studies, the results show that both water age and pressure can indeed be significantly reduced by the optimized position and setting of the PRVs.

Pseudorabies virus (PRV) establishes persistent latent infections by effectively evading the host’s antiviral innate immune response. PRV has developed sophisticated strategies to bypass immune surveillance through coevolution with its host. Currently, no effective vaccine exists to prevent or treat infections caused by emerging PRV variants, and the interactions between PRV and the host’s innate immune defenses remain incompletely understood. Nevertheless, ongoing research is uncovering insights that may lead to novel treatments and preventive approaches for herpesvirus-related diseases. This review summarizes recent advances in understanding how PRV disrupts key adaptors in immune signaling pathways to evade antiviral immunity. Additionally, we explored the intrinsic cellular defenses that play crucial roles in combating viral invasion. A deeper understanding of the immune evasion strategies of PRV could inform the development of new therapeutic targets and vaccines.

Managing Non-Revenue Water (NRW) and especially leakage reduction in water distribution networks is a critical challenge for water companies worldwide. Pressure management is widely accepted as an efficient, cost-effective and quickly applicable method for leakage reduction, which also supports the reduction of asset fatigue and subsequent failures. However, an important challenge in the design and evaluation of pressure management strategies is the realistic spatio-temporal distribution, and modelling of leakages which accounts for the association between leakages and pipe characteristics, such as material, age etc., as well as operational conditions. This work demonstrates a bottom-up approach for the realistic modelling of leakages and the exploration of optimal pressure management settings to achieve leakage reduction, while meeting regulatory requirements and maintaining the expected levels of service. In the first step a methodology for leakage modelling and spatial distribution is incorporated that models leakage at pipe level separately than consumption through fictional nodes and directly associates leakages with the pipes’ physical and operational characteristics along with the creation of network-specific nomograms for different leakage rates, offering insight on the pattern of systemic-specific background leakage parameters. Subsequently, the pressure management scheme explores optimal solutions by utilising existing infrastructures and avoiding the cost of new installments, while preserving satisfactory supply services. A case study demo network called KY11 is used to demonstrate the application of this framework, though it is applicable to any network with known losses. Two optimisation scenarios are explored, one assuming all system PRVs are of fixed setting and one with PRVs of time modulated setting. In both scenarios total volume of leakages is reduced by approximately 11%, however differences in spatial distribution of leakage reduction and the network’s operation are noticed. This coupled approach offers an adaptable tool for cost-free leakage reduction, allowing for spatially targeted leakage reduction interventions under current or future system configurations.