TRIM29 acts as a potential senescence suppressor with epigenetic activation in nasopharyngeal carcinoma.

Epigenetic alterations marked by DNA methylation are frequent events during the early development of nasopharyngeal carcinoma (NPC). We identified that TRIM29 is hypomethylated and overexpressed in NPC cell lines and tissues. TRIM29 silencing not only limited the growth of NPC cells in vitro and in vivo, but also induced cellular senescence, along with reactive oxygen species (ROS) accumulation. Mechanistically, we found that TRIM29 interacted with voltage-dependent anion-selective channel 1 (VDAC1) to activate mitophagy clearing up damaged mitochondria, which are the major source of ROS. In patients with NPC, high levels of TRIM29 expression are associated with an advanced clinical stage. Moreover, we detected hypomethylation of TRIM29 in patient nasopharyngeal swab DNA. Our findings indicate that TRIM29 depends on VDAC1 to induce mitophagy and prevents cellular senescence by decreasing ROS. Detection of aberrantly methylated TRIM29 in the nasopharyngeal swab DNA could be a promising strategy for the early detection of NPC

Comparative transcriptome analysis revealed key factors for differential cadmium transport and retention in roots of two contrasting peanut cultivars

Abstract Background Peanut is the world’s fourth largest oilseed crop that exhibits wide cultivar variations in cadmium (Cd) accumulation. To establish the mechanisms of Cd distribution and accumulation in peanut plants, eight cDNA libraries from the roots of two contrasting cultivars, Fenghua 1 (low-Cd cultivar) and Silihong (high-Cd cultivar), were constructed and sequenced by RNA-sequencing. The expression patterns of 16 candidate DEGs were validated by RT-qPCR analysis. Results A total of 75,634 genes including 71,349 known genes and 4484 novel genes were identified in eight cDNA libraries, among which 6798 genes were found to be Cd-responsive DEGs and/or DEGs between these two cultivars. Interestingly, 183 DEGs encoding ion transport related proteins and 260 DEGs encoding cell wall related proteins were identified. Among these DEGs, nine metal transporter genes (PDR1, ABCC4 and ABCC15, IRT1, ZIP1, ZIP11, YSL7, DTX43 and MTP4) and nine cell wall related genes (PEs, PGIPs, GTs, XYT12 CYP450s, LACs, 4CL2, C4H and CASP5) showed higher expression in Fenghua 1 than in Silihong. Conclusions Both the metal transporters and cell wall modification might be responsible for the difference in Cd accumulation and translocation between Fenghua 1 and Silihong. These findings would be useful for further functional analysis, and reveal the molecular mechanism responsible for genotype difference in Cd accumulation

Video-based discomfort detection for infants

Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use

Detecting discomfort in infants through facial expressions

OBJECTIVE: Detecting discomfort status of infants is particularly clinically relevant. Late treatment of discomfort infants can lead to adverse problems such as abnormal brain development, central nervous system damage and changes in responsiveness of the neuroendocrine and immune systems to stress at maturity. In this study, we exploit deep convolutional neural network (CNN) algorithms to address the problem of discomfort detection for infants by analyzing their facial expressions. APPROACH: A dataset of 55 videos about facial expressions, recorded from 24 infants, is used in our study. Given the limited available data for training, we employ a pre-trained CNN model, which is followed by fine-tuning the networks using a public dataset with labeled facial expressions (the shoulder-pain dataset). The CNNs are further refined with our data of infants. MAIN RESULTS: Using a two-fold cross-validation, we achieve an area under the curve (AUC) value of 0.96, which is substantially higher than the results without any pre-training steps (AUC  =  0.77). Our method also achieves better results than the existing method based on handcrafted features. By fusing individual frame results, the AUC is further improved from 0.96 to 0.98. SIGNIFICANCE: The proposed system has great potential for continuous discomfort and pain monitoring in clinical practice

Sequential Detection of Superoxide Anion and Hydrogen Polysulfides under Hypoxic Stress via a Spectral-Response-Separated Fluorescent Probe Functioned with a Nitrobenzene Derivative

Chronic hypoxic stress disrupts the intracellular redox homeostasis, leads to a series of physiological dysfunction, and finally results in many diseases including cancer and inflammatory and cardiovascular diseases. The intracellular redox status is related to the homeostasis between reactive oxygen species (ROS) and cellular antioxidant species. Superoxide anion (O-2(center dot-) is considered to be a precursor of ROS. As a member of reactive sulfur species, hydrogen polysulfides (H2Sn) are a class of antioxidants in cells, which act as an important regulator for the intracellular redox state. Therefore, trapping the cross-talk of O-2(center dot-) and H2Sn is a benefit for further understanding the physiological and pathological effects. Herein, we conceive a fluorescent probe HCy-ONO for sequential detection of O-2(center dot-) and H2Sn in cells and in mouse models. Based on a tandem reaction, the probe HCy-ONO can be used to detect O-2(center dot-) and H2Sn in different fluorescence collection windows without spectral overlap interference with limits of detection 90 and 100 nM, respectively. The strategy affords high sensitivity and selectivity for our detection in living cell models under continuous hypoxic and intermittent hypoxic conditions, revealing the reason for ischemia-reperfusion injury. Moreover, the probe can distinguish the inflamed tissue from normal tissue in acute peritonitis mouse model. Finally, our probe is successfully applied for imaging of O-2(center dot-) and H2Sn in the SH-SYSY tumor-bearing mouse model, which is helpful to elucidate the physiological and pathological processes. These data demonstrated that different hypoxic status lead to different concentrations between H2Sn and O-2(center dot-)

Respiration monitoring for premature neonates in NICU

In this paper, we investigate an automated pipeline to estimate respiration signals from videos for premature infants in neonatal intensive care units (NICUs). Two flow estimation methods, namely the conventional optical flow- and deep learning-based flow estimation methods, were employed and compared to estimate pixel motion vectors between adjacent video frames. The respiratory signal is further extracted via motion factorization. The proposed methods were evaluated by comparing our automated extracted respiration signals to that extracted from chest impedance on videos of five premature infants. The overall average cross-correlation coefficients are 0.70 for the optical flow-based method and 0.74 for the deep flow-based method. The average root mean-squared errors are 6.10 and 4.55 for the optical flow- and the deep flow-based methods, respectively. The experimental results are promising for further investigation and clinical application of the video-based respiration monitoring method for infants in NICU

Zhuifeng Tougu capsules in the treatment of knee osteoarthritis (cold dampness obstruction syndrome): a randomized, double blind, multicenter clinical study

Abstract Background In Traditional Chinese Medicine (TCM) theory, cold dampness obstruction is one of the common syndromes of osteoarthritis. Therefore, in clinical practice, the main treatment methods are to dispel wind, remove dampness, and dissipate cold, used to treat knee osteoarthritis (KOA). This report describes a mulitercenter clinical study to assess Zhuifeng Tougu Capsule’s efficacy and safety in the treatment of patients who are cold dampness obstruction syndrome in KOA, and to provide evidence-based medical for the rational use of Zhuifeng Tougu Capsules in clinical practice. Methods This randomized, parallel group controlled, double-blind, double dummy trial will include a total of 215 KOA patients who meet the study criteria. 215 patients underwent 1:1 randomisation, with 107 cases assigned the experimental group (Zhuifeng Tougu Capsules + Glucosamine Sulfate Capsules Simulator) and 108 assigned the control group (Glucosamine Sulfate Capsules + Zhuifeng Tougu Capsules Simulator). After enrolment, patients received 12 weeks of treatment. The main efficacy measure is the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) pain score. Visual analogue scale (VAS) pain score, Self-condition assessment VAS score, WOMAC KOA score, TCM syndrome score and TCM syndrome efficacy, ESR level, CRP level, suprapatellar bursa effusion depth, use of rescue drugs, and safety indicators are secondary efficacy indicators. Results Compared with before treatment, WOMAC pain score, VAS pain score, Self-condition assessment VAS score, WOMAC KOA score, and TCM syndrome score decreased significantly in both groups (P  0.05). No any serious adverse effects showed in the experimental group and control group. Conclusions Zhuifeng Tougu Capsules can effectively improve knee joint function and significantly alleviate the pain of KOA. Trial registration: Clinical trial registration was completed with the China Clinical Trial Registration Center for this research protocol (No. ChiCTR2000028750) on January 2, 2020

Automated discomfort detection for premature infants in NICU using time-frequency feature-images and CNNs

Pain or discomfort exposure during hospitalization of preterm infants has an adverse effect on brain development. Contactless monitoring has been considered to be a promising approach for detecting infant pain and discomfort moments continuously. In this study, our main objective is to develop an automated discomfort detection system based on video monitoring, allowing caregivers to provide timely and appropriate treatments. The system first employs the optical ow to estimate infant body motion trajectories across video frames. Following the movement estimation, Log Mel-spectrogram, Mel Frequency Cepstral Coefficients (MFCCs) and Spectral Subband Centroid Frequency (SSCF) features are calculated from the One-Dimensional (1D) motion signal. These features enable the representation of the 1D motion signals by Two-Dimensional (2D) time-frequency representations of the distribution of signal energy. Finally, deep Convolutional Neural Networks (CNNs) are applied on the 2D images for the binary - comfort/discomfort classification. The performance of the model is assessed using leave-one-infant- out cross-validation. Our algorithm was evaluated on a dataset containing 183 video segments recorded from 11 infants during 17 heel prick events, which is a pain stimulus associated with a routine care procedure. Experimental results showed an area under the receiver operating characteristic curve of 0.985 and an accuracy of 94.2%, which offers a promising possibility to deploy the proposed system in clinical practice