Lower limb sensory disturbance can be a false localizing sign of cervical spondylotic myelopathy. It may lead to delayed or missed diagnosis, resulting in an inappropriate management plan, especially ...in the presence of concurrent lumbar lesions. Three Asian patients with lower limb sensory disturbance were ineffectively treated in the lumbar region. Magnetic resonance imaging showed cervical disc herniation and cervical spinal cord compression. The patients underwent anterior cervical discectomy and interbody fusion using a stand-alone cervical interbody fusion cage. Postoperative imaging showed that the spinal cord compression was relieved. On the first postoperative day, the lower limb sensory disturbance was also relieved. The patients showed good recovery at the 3-month postoperative follow-up. These three cases of cervical cord compression with lower limb sensory disturbance were easily misdiagnosed as lumbar spondylosis. Anterior cervical discectomy and fusion had a good therapeutic effect. Therefore, the presence of lower limb sensory disturbance in a non-radicular classic pattern should always raise suspicion of a possible cord compression at a higher level.
Postoperative discal pseudocyst (PDP) is a rare complication that can occur after percutaneous endoscopic lumbar discectomy (PELD), microendoscopic discectomy, and laminectomy. The PDP pathogenesis ...and pathological process remain unclear. We described two PDP cases following PELD, with long-term follow-up results. The first patient was an Asian male, 30 years old, who experienced unbearable low back pain with right lower limb radiating pain for 2 years. The second patient was also an Asian male, 21 years old, who experienced low back pain with bilateral lower limb numbness. Both patients were diagnosed with lumbar disc herniation, underwent PELD, and relapsed after discharge. The diagnosis was PDP in each case, and conservative treatment was initiated with oral anti-inflammatory drugs and rest. Eventually, the symptoms in both patients resolved. Magnetic resonance imaging showed that the discal cysts had disappeared. The follow-up of these two PDP cases after PELD showed good results, demonstrating that PDP may be a self-healing disease. Conservative treatment is effective, and surgery should be performed only in an emergency. These case reports and literature review can help improve the understanding of PDP.
Background: Cytokines in synovial fluid (SF) play a crucial role in knee osteoarthritis (KOA). Exosomes are nanovesicles that are abundant in SF and carry a large quantity of signaling molecules. The ...purpose of this study was to evaluate the cytokine profiles of SF-derived exosomes and try to explore its biological function.
Methods: Twenty-four KOA patients who were scheduled for their first intra-articular injection or knee replacement surgery were enrolled and divided into the KL1-2 group and the KL3-4 group according to the Kellgren and Lawrence (KL) classification. SF was collected from the patient's knee for the isolation of exosomes. A multiplex cytokine assay was performed to detect the 21 cytokines in the exosomes. The SF derived-exosomes were exposed to PBMCs and chondrocytes to assess their immunomodulatory potential.
Results: Exosomes were successfully extracted from the SF, with an average diameter of 92 nm. Most cytokines were detectable in the SF-derived exosomes. Twelve inflammatory cytokines and eight chemokines were elevated in the exosomes of the KL3-4 group compared to that of the KL1-2 group (p < .05). A higher number of PBMCs were chemo attracted and the proliferation of chondrocytes was restrained by the SF-derived exosomes from the KL3-4 group in comparison with the KL1-2 group (p < .05).
Conclusion: Our data indicated that most cytokines in SF are not only in a free form but also associated with and enriched in exosomes. Exosomes from end-stage KOA patients have a higher level of cytokines, especially chemokines, in comparison with the cytokine profiles of the soluble SF. SF-derived exosomes recruit inflammatory cells and inhibit cartilage proliferation, thus promoting joint degeneration. These data provide a new perspective for understanding the changes in the inner environment of KOA.
Objective
Knee osteoarthritis (KOA) is a chronic inflammatory disease. The monocyte–lymphocyte ratio (MLR) was reported to be a non-invasive, cost-effective marker in various systemic diseases, but ...it has not yet been investigated in KOA. This cross-sectional study evaluated the diagnostic value of MLR in KOA.
Methods
Two hundred and five KOA patients and 120 healthy control subjects were enrolled. Patient data, including age, sex, blood cell counts, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) levels, red blood cell distribution width, and the Kellgren–Lawrence (KL) score were recorded.
Results
One hundred nineteen patients (55 men, 64 women) were included, with a mean age of 55.47 ± 9.23 years. KOA patients showed a significantly higher MLR, neutrophil–lymphocyte ratio (NLR), and platelet–lymphocyte ratio (PLR) than controls. The MLR area under the curve was 0.81, which was higher than that of NLR and PLR. Multiple logistic regression analysis revealed blood MLR as an independent predictor of KOA. Correlation analysis showed that MLR was positively correlated with ESR and CRP levels. MLR and NLR were significantly higher in KL4 patients than in KL1–3 patients.
Conclusions
MLR has a high diagnostic value for KOA, so could be a reliable disease marker.
Antibiotic resistance is one of the biggest threats to public health, and new antibacterial agents hence are in an urgent need to combat infectious diseases caused by multidrug-resistant (MDR) ...pathogens. Utilizing dimerization strategy, we rationally designed and efficiently synthesized a new series of small molecule dimeric lysine alkylamides as mimics of AMPs. Evaluation of these mimics against a panel of Gram-positive and Gram-negative bacteria including MDR strains was performed, and a broad-spectrum and potent compound 3d was identified. This compound displayed high specificity toward bacteria over mammalian cell. Time–kill kinetics and mechanistic studies suggest that compound 3d quickly eliminated bacteria in a bactericidal mode by disrupting bacterial cell membrane. In addition, lead compound 3d could inhibit biofilm formation and did not develop drug resistance in S. aureus and E. coli over 14 passages. These results suggested that dimeric lysine nonylamide has immense potential as a new type of novel small molecular agent to combat antibiotic resistance.
Real-time detection of gait events can be applied as a reliable input to control drop foot correction devices and lower-limb prostheses. Among the different sensors used to acquire the signals ...associated with walking for gait event detection, the accelerometer is considered as a preferable sensor due to its convenience of use, small size, low cost, reliability, and low power consumption. Based on the acceleration signals, different algorithms have been proposed to detect toe off (TO) and heel strike (HS) gait events in previous studies. While these algorithms could achieve a relatively reasonable performance in gait event detection, they suffer from limitations such as poor real-time performance and are less reliable in the cases of up stair and down stair terrains. In this study, a new algorithm is proposed to detect the gait events on three walking terrains in real-time based on the analysis of acceleration jerk signals with a time-frequency method to obtain gait parameters, and then the determination of the peaks of jerk signals using peak heuristics. The performance of the newly proposed algorithm was evaluated with eight healthy subjects when they were walking on level ground, up stairs, and down stairs. Our experimental results showed that the mean F1 scores of the proposed algorithm were above 0.98 for HS event detection and 0.95 for TO event detection on the three terrains. This indicates that the current algorithm would be robust and accurate for gait event detection on different terrains. Findings from the current study suggest that the proposed method may be a preferable option in some applications such as drop foot correction devices and leg prostheses.
Objective
Synovitis is a joint disease that seriously affects patient quality of life, but there are currently no diagnostic markers. The albumin to fibrinogen ratio (AFR) and monocyte to lymphocyte ...ratio (MLR) are non-invasive and cost-effective markers for various systemic inflammatory diseases. However, these markers have not yet been investigated for synovitis. This cross-sectional study evaluated the predictive ability of AFR and MLR in patients with non-specific knee synovitis.
Methods
One hundred fifty-five patients with knee synovitis and 108 healthy control patients were enrolled. Patient characteristics, blood parameters, AFRs, and MLRs were assessed, and the diagnostic value of these factors was determined.
Results
Among 125 patients included, patients with synovitis had a lower AFR and higher MLR than control subjects. The diagnostic values of AFR and MLR were 0.86 and 0.84, respectively, and higher compared with other parameters by receiver operating characteristic curve assessments. Additionally, MLR was negatively correlated with AFR. Late-stage patients showed significantly lower AFRs and significantly higher MLRs than early-stage patients. Binary logistic regression analyses indicated that AFR was an independent predictor for synovitis severity.
Conclusions
The AFR and MLR had high diagnostic value for knee synovitis. The AFR was an independent predictor for synovitis severity.
In order to mine information from medical health data and develop intelligent application-related issues, the multi-modal medical health data feature representation learning related content was ...studied, and several feature learning models were proposed for disease risk assessment. In the aspect of medical text feature learning, a medical text feature learning model based on convolutional neural network is proposed. The convolutional neural network text analysis technology is applied to the disease risk assessment application. The medical data feature representation adopts the deep learning method. The learning and extraction of different disease characteristics use the same method to realize the versatility of the model. A simple preprocessing of the experimental data samples, including its power frequency denoising and lead convolution regularization, constructs a convolutional neural network for medical data feature advancement and intelligent recognition. On the basis of it, several sets of experiments were carried out to discuss the influence of the convolution kernel and the choice of learning rate on the experimental results. In addition, comparative experiments with support vector machine, BP neural network and RBF neural network are carried out. The results show that the convolutional neural network used in this paper shows obvious advantages in recognition rate and training speed compared with other methods. In the aspect of time series data feature learning, a multi-channel convolutional self-encoding neural network is proposed. Analyze the connection between fatigue and emotional abnormalities and define the concept of emotional fatigue. The proposed multi-channel convolutional neural network is used to learn the data features, and the convolutional self-encoding neural network is used to learn the facial image data features. These two characteristics and the collected physiological data are combined to perform emotional fatigue detection. An emotional fatigue detection demonstration platform for multi-modal data feature fusion is established to realize data acquisition, emotional fatigue detection and emotional feedback. The experimental results verify the validity, versatility and stability of the model.
In this paper, we aim to explore the relationship between the carbon emissions and oil prices from 2014 to 2021 in China using the Morlet continuous wavelet and the maximal overlap discrete wavelet ...transform. The results indicate that there is a positive correlation in the period from 2014 to 2018 with carbon prices leading. After 2019, the two series show a positive correlation in the medium and high-frequency domains with oil prices leading.
•There is relationship between carbon emission rights and crude oil prices in China.•The leading and lagging relationship of interaction is different in different periods.•The Morlet continuous wavelet and maximal overlap discrete wavelet transform are used.
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