Sinus rhythm restoration reverses tricuspid regurgitation in patients with atrial fibrillation: a systematic review and meta-analysis.

BACKGROUND: Tricuspid regurgitation (TR) is a common valvular heart disease worldwide, and current guidelines for TR treatment are relatively conservative, as well as with detrimental outcomes. Restoration of sinus rhythm was reported to improve the TR severity in those TR patients with atrial fibrillation (AF). However, relevant research was limited. The aim of this meta-analysis was to evaluate the clinical outcomes of restoration of sinus rhythm in TR patients with AF. METHODS: In this study, PubMed, Web of Science, and Scopus databases were searched for study enrollment until July 2023. This study was designed under the guidance of Preferred Reporting Items for Systematic Reviews and Meta-Analyses. These studies containing the patient's baseline characteristics, surgical procedure, and at least one of the clinical outcomes were included. The primary endpoint was TR grade during follow-up after restoration of sinus rhythm. RESULTS: Out of 1074 records, 6 were enrolled. Restoration of sinus rhythm is associated with a reduction of TR severity (TR grade, odds ratio 0.11, 95% confidence interval (CI): 0.01 to 1.28, P = 0.08, I2 = 83%; TR area, mean difference (MD) -2.19 cm2, 95% CI: -4.17 to -0.21 cm2, P = 0.03, I2 = 96%). Additionally, remolding of right heart with a significant reduction of tricuspid valve annulus diameter (MD -0.36 cm, 95%CI: -0.47 to -0.26 cm, P < 0.00001, I2 = 29%) and right atrium volume index (MD -11.10 mL/m2, 95%CI: -16.81 to -5.39 mL/m2, P = 0.0001, I2 = 79%) was observed during follow-up. CONCLUSIONS: In conclusion, rhythm-control therapy could reduce TR severity in AF patients with TR and is associated with right heart remodeling.

Multimodal Dual-Embedding Networks for Malware Open-Set Recognition.

Malware open-set recognition (MOSR) is an emerging research domain that aims at jointly classifying malware samples from known families and detecting the ones from novel unknown families, respectively. Existing works mostly rely on a well-trained classifier considering the predicted probabilities of each known family with a threshold-based detection to achieve the MOSR. However, our observation reveals that the feature distributions of malware samples are extremely similar to each other even between known and unknown families. Thus, the obtained classifier may produce overly high probabilities of testing unknown samples toward known families and degrade the model performance. In this article, we propose the multi \ modal dual-embedding networks, dubbed MDENet, to take advantage of comprehensive malware features from different modalities to enhance the diversity of malware feature space, which is more representative and discriminative for down-stream recognition. Concretely, we first generate a malware image for each observed sample based on their numeric features using our proposed numeric encoder with a re-designed multiscale CNN structure, which can better explore their statistical and spatial correlations. Besides, we propose to organize tokenized malware features into a sentence for each sample considering its behaviors and dynamics, and utilize language models as the textual encoder to transform it into a representable and computable textual vector. Such parallel multimodal encoders can fuse the above two components to enhance the feature diversity. Last, to further guarantee the open-set recognition (OSR), we dually embed the fused multimodal representation into one primary space and an associated sub-space, i.e., discriminative and exclusive spaces, with contrastive sampling and ρ -bounded enclosing sphere regularizations, which resort to classification and detection, respectively. Moreover, we also enrich our previously proposed large-scaled malware dataset MAL-100 with multimodal characteristics and contribute an improved version dubbed MAL-100 + . Experimental results on the widely used malware dataset Mailing and the proposed MAL-100 + demonstrate the effectiveness of our method.

Long Non-coding RNA LINC01119 Promotes Neuropathic Pain by Stabilizing BDNF Transcript.

Neuropathic pain (NP) is caused by primary injury or dysfunction of the peripheral and the central nervous system. Long non-coding RNAs were critical regulators involved in nervous system diseases, however, the precise regulatory mechanism remains unclear. This study aims to uncover the essential role of LINC01119 in NP progression and further clarify the underlying regulatory mechanism at post-transcriptional level. LINC01119 was significantly upregulated in rats of spare nerve injury (SNI) group compared to sham group. Functionally, silencing of LINC01119 significantly alleviated the neuropathic pain-induced hypersensitivity and reduced the increase in IL-6, IL-1ß, and TNF-α caused by SNI. Mechanistically, Brain-derived neurotrophic factor (BDNF) was identified as the functional target of LINC01119. Besides, an RNA binding protein, ELAVL1 could directly interact with LINC01119, and this formed LINC01119- ELAVL1 complex binds to BDNF mRNA, strengthening its RNA stability and increasing the expression level of BDNF at both transcript and protein levels. Clinically, serum LINC01119 was verified as a promising diagnostic biomarker for NP patients. LINC01119 induces NP progression via binding with ELAVL1 and increasing BDNF mRNA stability and expression level. Therefore, LINC01119 may serve as a promising diagnostic marker and therapeutic target for NP treatment.

Contribution of BDNF/TrkB signalling in the rACC to the development of pain-related aversion via activation of ERK in rats with spared nerve injury.

The rostral anterior cingulate cortex (rACC) is a key structure in mediating the negative affective component of chronic pain. Brain-derived neurotrophic factor (BDNF) is known to play a critical role in activity-dependent synaptic plasticity, learning and memory. It has been shown that BDNF signalling in the rACC might be involved in spontaneous pain-related aversion, but its underlying mechanism is still largely unknown. To address this question, we measured the mRNA and protein levels of BDNF in the rACC after nerve injury and found that BDNF expression was markedly higher in nerve-injured rats than in controls. Moreover, we found that conditioned place avoidance (CPA), a behavioural phenotype reflecting pain-related aversion, was acquired in rats with partial sciatic nerve transection. However, a local injection of a BDNF-tropomyosin receptor kinase B (TrkB) antagonist into the rACC completely suppressed this process. Importantly, we found that administration of exogenous BDNF into the rACC of intact rats was sufficient to produce CPA, while selectively blocking phosphorylated extracellular signal regulated kinase (p-ERK) with a mitogen-activated protein kinase (MAPK) inhibitor U0126 completely abolished the acquisition of BDNF-induced CPA. In conclusion, we demonstrate, for the first time, that ERK is an important downstream effector of the BDNF/TrkB-mediated signalling pathway in the rACC that contributes to the development of neuropathic pain-related aversion.

Brain-derived neurotrophic factor (BDNF) in the rostral anterior cingulate cortex (rACC) contributes to neuropathic spontaneous pain-related aversion via NR2B receptors.

The rostral anterior cingulate cortex (rACC) plays an important role in pain affect. Previous investigations have reported that the rACC mediates the negative affective component of inflammatory pain and contributed to the aversive state of nerve injury-induced neuropathic pain. Brain-derived neurotrophic factor (BDNF), an activity-dependent neuromodulator in the adult brain, is believed to play a role in the development and maintenance of inflammatory and neuropathic pain in the spinal cord. However, whether and how BDNF in the rACC regulates pain-related aversion due to peripheral nerve injury is largely unknown. Behaviorally, using conditioned place preference (CPP) training in rats, which is thought to reveal spontaneous pain-related aversion, we found that CPP was acquired following spinal clonidine in rats with partial sciatic nerve transection. Importantly, BDNF was upregulated within the rACC in of rats with nerve injury and enhanced the CPP acquisition, while a local injection of a BDNF-tropomyosin receptor kinase B (TrkB) antagonist into the rACC completely blocked this process. Finally, we demonstrated that the BDNF/TrkB pathway exerted its function by activating the NR2B receptor, which is widely accepted to be a crucial factor contributing to pain affect. In conclusion, our results demonstrate that the BDNF/TrkB-mediated signaling pathway in the rACC is involved in the development of neuropathic spontaneous pain-related aversion and that this process is dependent upon activation of NR2B receptors. These findings suggest that suppression of the BDNF-related signaling pathway in the rACC may provide a novel strategy to overcome pain-related aversion.