Mechanistic study of acupuncture on the pterygopalatine ganglion to improve allergic rhinitis: analysis of multi-target effects based on bioinformatics/network topology strategie.

One of the prevalent chronic inflammatory disorders of the nasal mucosa, allergic rhinitis (AR) has become more widespread in recent years. Acupuncture pterygopalatine ganglion (aPPG) is an emerging alternative therapy that is used to treat AR, but the molecular mechanisms underlying its anti-inflammatory effects are unclear. This work methodically demonstrated the multi-target mechanisms of aPPG in treating AR based on bioinformatics/topology using techniques including text mining, bioinformatics, and network topology, among others. A total of 16 active biomarkers and 108 protein targets related to aPPG treatment of AR were obtained. A total of 345 Gene Ontology terms related to aPPG of AR were identified, and 135 pathways were screened based on Kyoto Encyclopedia of Genes and Genomes analysis. Our study revealed for the first time the multi-targeted mechanism of action of aPPG in the treatment of AR. In animal experiments, aPPG ameliorated rhinitis symptoms in OVA-induced AR rats; decreased serum immunoglobulin E, OVA-sIgE, and substance P levels; elevated serum neuropeptide Y levels; and modulated serum Th1/Th2/Treg/Th17 cytokine expression by a mechanism that may be related to the inhibition of activation of the TLR4/NF-κB/NLRP3 signaling pathway. In vivo animal experiments once again validated the results of the bioinformatics analysis. This study revealed a possible multi-target mechanism of action between aPPG and AR, provided new insights into the potential pathogenesis of AR, and proved that aPPG was a promising complementary alternative therapy for the treatment of AR.

In-situ tool wear condition monitoring during the end milling process based on dynamic mode and abnormal evaluation.

Rapid tool wear conditions during the manufacturing process are crucial for the enhancement of product quality. As an extension of our recent works, in this research, a generic in-situ tool wear condition monitoring during the end milling process based on dynamic mode and abnormal evaluation is proposed. With the engagement of dynamic mode decomposition, the real-time response of the sensing physical quantity during the end milling process can be predicted. Besides, by constructing the graph structure of the time series and calculating the difference between the predicted signal and the real-time signal, the anomaly can be acquired. Meanwhile, the tool wear state during the end milling process can be successfully evaluated. The proposed method is validated in milling tool wear experiments and received positive results (the mean relative error is recorded as 0.0507). The research, therefore, paves a new way to realize the in-situ tool wear condition monitoring.

Acupuncture at "Die E acupoint" alleviates inflammatory reaction via inhibiting TLR4/MyD88/NF-κB signaling in rats with allergic rhinitis. / 基于Tollæ ·å—ä½“4/é«“æ ·åˆ†åŒ–å› å­88/æ ¸è½¬å½•å› å­κB信号通路探讨针刺"è¶è ­ç©´"æ”¹å–„å˜åº”æ€§é¼»ç‚Žå¤§é¼ å ç–«ç‚Žæ€§ååº”çš„æœºåˆ¶.

OBJECTIVES: To observe effects of acupuncture at "Die E acupoint" on the protein expression levels of Toll-like receptor 4 (TLR4), myeloid differentiation factor 88 (MyD88), nuclear transcription factor κB (NF-κB), transcription factor T-bet (T-bet), and GATA-binding protein-3 (GATA-3) in the nasal mucosa and the serum contents of related inflammatory cytokines in rats with allergic rhinitis, so as to explore the mechanism of acupuncture in treating allergic rhinitis. METHODS: Twenty-four healthy SD rats were randomly divided into blank, model, acupuncture, and sham acupuncture groups, with 6 rats in each group. The rat model of allergic rhinitis was established by using ovalbumin induction. The rats in the acupuncture group received bilateral acupuncture at the "Die E acupoint" with a depth of 15-20 mm, while the rats in the sham acupuncture group received only sham acupuncture (light and shallow acupunture of the skin at the "Die E acupoint" ). Both interventions were performed once daily for a total of 6 days. Behavioral scores of rats in each group were recorded. Pathological changes of nasal mucosa were observed by H.E. staining. Serum contents of IgE, ovalbumin-specific IgE (OVA-sIgE), interferon(IFN)-γ, interleukin(IL)-4, IL-10 and IL-17 were measured by ELISA and the protein expression levels of T-bet, GATA-3, TLR4, MyD88 and NF-κB p65 in the nasal mucosa were detected by Western blot. RESULTS: After modeling, compared with the blank group, rats in the model group showed increased behavioral scores, serum IgE, OVA-sIgE, IL-4, and IL-17 contents, and nasal mucosal GATA-3, TLR4, MyD88, and NF-κB p65 protein expression levels (P<0.05), whereas the contents of serum IFN-γ, IL-10 and the protein expression level of T-bet in the nasal mucosa were decreased (P<0.05). Comparison between the EA and model groups showed that acupuncture intervention can decrease the behavioral scores of rats with allergic rhinitis, the contents of serum IgE, OVA-sIgE, IL-4, IL-17, and the protein expression levels of GATA-3, TLR4, MyD88, and NF-κB p65 in the nasal mucosa (P<0.05), and up-regulate the contents of serum IFN-γ, IL-10, and the nasal mucosal T-bet protein expression level. Sham acupuncture did not have a significant modulating effect on the above indicators. Inflammatory infiltration of nasal mucosa was seen in the model group and sham acupuncture, and the inflammatory reaction was milder in the acupuncture group. CONCLUSIONS: Acupuncture at "Die E acupoint" can alleviate the symptoms of allergic rhinitis and suppress the inflammation of nasal mucosa in rats, which may be related to inhibiting the TLR4/MyD88/NF-κB signaling and balancing the levels of cytokines of Th1/Th2 and Treg/Th17, and T-bet/GATA-3.

Alternatives Exert Higher Health Risks than Bisphenol A on Indo-Pacific Humpback Dolphins.

The detrimental effects of bisphenol (BP) exposure are a concern for vulnerable species, Indo-Pacific humpback dolphins (Sousa chinensis). To investigate the characteristics of BP profiles and their adverse impact on humpback dolphins, we assessed the concentrations of six BPs, including bisphenol A (BPA), bisphenol S (BPS), bisphenol F (BPF), bisphenol AF (BPAF), bisphenol B (BPB), and bisphenol P (BPP) in blubber (n = 26) and kidney (n = 12) of humpback dolphins stranded in the Pearl River Estuary, China. BPS accounted for the largest proportion of the total bisphenols (∑BPs) in blubber (55%) and kidney (69%). The concentration of ∑BP in blubber was significantly higher than that in the kidney and liver. The EC50 values of five BPA alternatives were lower than those of BPA in humpback dolphin skin fibroblasts (ScSF) and human skin fibroblasts (HSF). ScSF was more sensitive to BPS, BPAF, BPB, and BPP than HSF. The enrichment pathway of BPA was found to be associated with inflammation and immune dysregulation, while BPP and BPS demonstrated a preference for genotoxicity. BPA, BPP, and BPS, which had risk quotients (RQs) > 1, were found to contribute to subhealth and chronic disease in humpback dolphins. According to the EC50-based risk assessment, BPS poses a higher health risk than BPA for humpback dolphins. This study successfully evaluated the risks of bisphenols in rare and endangered cetacean cell lines using a noninvasive method. More in vivo and in field observations are necessary to know whether the BPA alternatives are likely to be regrettable substitutions.

Electroencephalogram-Based Motor Imagery Classification Using Deep Residual Convolutional Networks.

The classification of electroencephalogram (EEG) signals is of significant importance in brain-computer interface (BCI) systems. Aiming to achieve intelligent classification of motor imagery EEG types with high accuracy, a classification methodology using the wavelet packet decomposition (WPD) and the proposed deep residual convolutional networks (DRes-CNN) is proposed. Firstly, EEG waveforms are segmented into sub-signals. Then the EEG signal features are obtained through the WPD algorithm, and some selected wavelet coefficients are retained and reconstructed into EEG signals in their respective frequency bands. Subsequently, the reconstructed EEG signals were utilized as input of the proposed deep residual convolutional networks to classify EEG signals. Finally, EEG types of motor imagination are classified by the DRes-CNN classifier intelligently. The datasets from BCI Competition were used to test the performance of the proposed deep learning classifier. Classification experiments show that the average recognition accuracy of this method reaches 98.76%. The proposed method can be further applied to the BCI system of motor imagination control.

Automatic Seizure Classification Based on Domain-Invariant Deep Representation of EEG.

Accurate identification of the type of seizure is very important for the treatment plan and drug prescription of epileptic patients. Artificial intelligence has shown considerable potential in the fields of automated EEG analysis and seizure classification. However, the highly personalized representation of epileptic seizures in EEG has led to many research results that are not satisfactory in clinical applications. In order to improve the clinical adaptability of the algorithm, this paper proposes an adversarial learning-driven domain-invariant deep feature representation method, which enables the hybrid deep networks (HDN) to reliably identify seizure types. In the train phase, we first use the labeled multi-lead EEG short samples to train squeeze-and-excitation networks (SENet) to extract short-term features, and then use the compressed samples to train the long short-term memory networks (LSTM) to extract long-time features and construct a classifier. In the inference phase, we first adjust the feature mapping of LSTM through the adversarial learning between LSTM and clustering subnet so that the EEG of the target patient and the EEG in the database obey the same distribution in the deep feature space. Finally, we use the adjusted classifier to identify the type of seizure. Experiments were carried out based on the TUH EEG Seizure Corpus and CHB-MIT seizure database. The experimental results show that the proposed domain adaptive deep feature representation improves the classification accuracy of the hybrid deep model in the target set by 5%. It is of great significance for the clinical application of EEG automatic analysis equipment.

Adaptive Sparse Detector for Suppressing Powerline Component in EEG Measurements.

Powerline interference (PLI) is a major source of interference in the acquisition of electroencephalogram (EEG) signal. Digital notch filters (DNFs) have been widely used to remove the PLI such that actual features, which are weak in energy and strongly connected to brain states, can be extracted explicitly. However, DNFs are mathematically implemented via discrete Fourier analysis, the problem of overlapping between spectral counterparts of PLI and those of EEG features is inevitable. In spite of their effectiveness, DNFs usually cause distortions on the extracted EEG features, which may lead to incorrect diagnostic results. To address this problem, we investigate an adaptive sparse detector for reducing PLI. This novel approach is proposed based on sparse representation inspired by self-adaptive machine learning. In the coding phase, an overcomplete dictionary, which consists of redundant harmonic waves with equally spaced frequencies, is employed to represent the corrupted EEG signal. A strategy based on the split augmented Lagrangian shrinkage algorithm is employed to optimize the associated representation coefficients. It is verified that spectral components related to PLI are compressed into a narrow area in the frequency domain, thus reducing overlapping with features of interest. In the decoding phase, eliminating of coefficients within the narrow band area can remove the PLI from the reconstructed signal. The sparsity of the signal in the dictionary domain is determined by the redundancy factor. A selection criteria of the redundancy factor is suggested via numerical simulations. Experiments have shown the proposed approach can ensure less distortions on actual EEG features.

Health State Monitoring of Bladed Machinery with Crack Growth Detection in BFG Power Plant Using an Active Frequency Shift Spectral Correction Method.

Power generation using waste-gas is an effective and green way to reduce the emission of the harmful blast furnace gas (BFG) in pig-iron producing industry. Condition monitoring of mechanical structures in the BFG power plant is of vital importance to guarantee their safety and efficient operations. In this paper, we describe the detection of crack growth of bladed machinery in the BFG power plant via vibration measurement combined with an enhanced spectral correction technique. This technique enables high-precision identification of amplitude, frequency, and phase information (the harmonic information) belonging to deterministic harmonic components within the vibration signals. Rather than deriving all harmonic information using neighboring spectral bins in the fast Fourier transform spectrum, this proposed active frequency shift spectral correction method makes use of some interpolated Fourier spectral bins and has a better noise-resisting capacity. We demonstrate that the identified harmonic information via the proposed method is of suppressed numerical error when the same level of noises is presented in the vibration signal, even in comparison with a Hanning-window-based correction method. With the proposed method, we investigated vibration signals collected from a centrifugal compressor. Spectral information of harmonic tones, related to the fundamental working frequency of the centrifugal compressor, is corrected. The extracted spectral information indicates the ongoing development of an impeller blade crack that occurred in the centrifugal compressor. This method proves to be a promising alternative to identify blade cracks at early stages.

An Intelligent Gear Fault Diagnosis Methodology Using a Complex Wavelet Enhanced Convolutional Neural Network.

As a typical example of large and complex mechanical systems, rotating machinery is prone to diversified sorts of mechanical faults. Among these faults, one of the prominent causes of malfunction is generated in gear transmission chains. Although they can be collected via vibration signals, the fault signatures are always submerged in overwhelming interfering contents. Therefore, identifying the critical fault's characteristic signal is far from an easy task. In order to improve the recognition accuracy of a fault's characteristic signal, a novel intelligent fault diagnosis method is presented. In this method, a dual-tree complex wavelet transform (DTCWT) is employed to acquire the multiscale signal's features. In addition, a convolutional neural network (CNN) approach is utilized to automatically recognise a fault feature from the multiscale signal features. The experiment results of the recognition for gear faults show the feasibility and effectiveness of the proposed method, especially in the gear's weak fault features.

[Comparative study of serum levels of BMP-2 and heterotopic ossification in traumatic brain injury and fractures patients].

OBJECTIVE: To investigate the relationship between serum level of bone morphogenetic proteins-2 (BMP-2) and heterotopic ossification (HO) in traumatic brain injury (TBI) and fractures patients, providing the theoretical evidence for the clinical prevention of HO. METHODS: From December 2007 to January 2009, 145 with trama patients were selected. There were 96 closed primary traumatic brain injury patients, 1 penetrating primary traumatic brain injury, 29 fractures of the radius and ulna, 11 fractures of the humerus, 32 fractures of the tibia and fibula, 27 fractures of the femur. All patients were divided into three groups (i.e., group A, group B and group C) by the type of fracture. Fifty-seven patients in group A (TBI only), including 37 males and 20 females, ranged in the age from 29 to 61 years, with an average age of (43.91 +/- 11.09) years. The disease course was from 13 to 67 d, with an average duration of (18.96 +/- 10.46) d. Forty-eight patients in group B (fractures only), 25 males and 23 females, ranged in age from 31 to 54 years, with an average age of (41.73 +/- 8.41) years. The disease course was from 6 to 48 d, with an average duration of (16.02 +/- 8.71) d. Forty patients in group C (TBI combined with extremities fractures), including 23 males and 17 females, ranged in age from 30 to 60 years, with an average age of (45.87 +/- 14.15) years. The disease course was from 18 to 76 d, with an average of (21.28 +/- 13.02) d. Thirty-one extremities fractures with no significant separations or displacements of fragments were treated with traction reductions, cast immobilization or splint fixations. Sixty-eight fractures with significant separations and displacements of fragments were treated with intramedullary nail fixations or screw internal fixations. Sixty-three TBI patients were treated with open-skull surgeries immediately while 34 TBI patients were treated with stanching bleeding, reducing intracranial pressure and improving cerebral blood circulation. All patients were also divided into two groups (group D and group E) according to the 14-to 16-month follow-up X-ray film results. Seventeen patients in group D (HO had been found), including 11 males and 6 females, ranged in age from 29 to 55 years old, with an average age of (46.88 +/- 7.13) years. The disease course was from 6 to 30 d, with an average of (20.18 +/- 9.78) d. All 128 patients in group E (HO had been not found), including 74 males and 54 females, ranged in age from 33 to 61 years, with an average age of (43.31 +/- 12.94) years. The disease course was from 15 to 76 d, with an average of (18.42 +/- 11.58) d. The 49 subjects in group F (normal controls), 29 males and 20 females, ranged in age from 31 to 60 years, average (43.50 +/- 14.40) years. Peripheral blood samples were taken for the determination of BMP-2 in blood serum on 0.5, 3, 15 d and 30 d after fractures by enzyme-linked immunosorbent assay (ELISA). Analysis of variance and least significant difference test were done with the help of SPSS 13.0 statistic software. RESULTS: The incidence rates of HO between the TBI only patients (21.05%, 12/57) and the fractures only patients(4.17%, 2/48) were significant different (chi2=5.05, P<0.05). Serum levels of BMP-2 at 0.5, 3 d and 15 d between group A and group B were significant different. Serum levels of BMP-2 at 0.5, 3, 15 d and 30 d between group D and group E were significant different. Serum levels of BMP-2 at each time in each group were higher than the control group (51.30 +/- 23.41 ng/L) (P<0.01). CONCLUSION: High serum levels of BMP-2 in TBI only group is one of factors in causing HO. Serum level of BMP-2 at 15 d since fractures may be the obvervational index of HO prevention.

[Finite element analysis of adolescent idiopathic scoliosis of PUMC II d2 surgical treatment with different fusion levels].

OBJECTIVE: To explore the best surgical fusion level for adolescent idiopathic scoliosis (AIS) of PUMC II d(2) with finite element model (FEM). METHODS: FEM (T(5)-S) of PUMC II d(2) idiopathic scoliosis was used to simulate upper thoracic curve, lower lumbar curve and double curve fusion manners. The pedicle of concave vertebral arch received 50, 100 and 150 N load respectively. Displacement of T(5) and T(11) on upper sagittal plane (displacement of Z axis positive value on upper sagittal plane, displacement of negative value on lower sagittal plane) and their different values were compared. T(5) displacement represented the outcomes of double curve orthopedics. T(11) displacement represented the outcomes of lower lumbar curve orthopedics. Their difference (T(5)-T(11)) represented the outcomes of upper thoracic curve orthopedics. Different fusion segments and displacement of T(5) and T(11) under different orthopedic forces were measured. RESULTS: In PUMC II d(2) lateral curvature, T(5) displacement on Z axis: fusion displacement of double curve was greater than the upper or lower curve alone (F = 8, P < 0.01). Difference of T(5)-T(11) displacement: double curve orthopedics > upper thoracic curve orthopedics alone > lower lumbar curve orthopedics alone (F = 8, P < 0.01). Displacement of T(11) on Z axis: double curve orthopedics > lower lumbar curve orthopedics alone > upper thoracic curve orthopedics alone (F = 8, P < 0.01). CONCLUSION: Fusing two curves achieves the best effect on the AIS of PUMC II d(2) in comparison with upper or lower curve fusion alone. Effects of 3 kinds of load on correction of upper thoracic curve: double curve orthopedics > upper thoracic curve orthopedics alone > lower lumbar curve orthopedics alone. Effect of 3 kinds of load on correction of lower lumbar curve orthopedics alone: double curve orthopedics > lower lumbar curve orthopedics alone > upper thoracic curve orthopedics alone. Three-dimensional finite element analysis is an effective method to analyze the biomechanics of scoliosis deformity correction and provides a virtually non-invasive verification manner. And it may optimize the surgical protocol.

[Reverse fasciocutaneous flap pedicled with perforator branch of anterior medial malleolus artery for soft tissue defect on the dorsal side of foot].

OBJECTIVE: To report the therapeutic effect of reverse fasciocutaneous flap pedicled with perforator branch of anterior medial malleolus artery for soft tissue defect on the dorsal side of foot. METHODS: The perforator branch was located under the guidance of Doppler flowmeter. The flap was designed along the saphenous neurovascular axis. Then the flap was transferred reversely with the perforator branch as rotation point. RESULTS: From Feb. 2002 to Mar. 2008, 12 cases were treated and followed up for 6 - 18 months. All the flaps survived completely. The flap size ranged from 13.5 cm x 3.0 cm to 8 cm x 3 cm. The perforator branch located at 0.5 - 1.5 cm anterior-inferior to the medial malleolus. Both the cosmetic and functional results were satisfactory. CONCLUSIONS: The flap has a reliable blood supply and a flexible design. It is easily performed for soft tissue defect on the dorsal side of foot. It is a new type flap which combined neurocutaneous vascular flap with the perforator flap.