Single-cell RNA sequencing reveals the transcriptomic characteristics of peripheral blood mononuclear cells in hepatitis B vaccine non-responders

The emergence of a vaccine against hepatitis B has proven to be an important milestone in the prevention of this disease; however, 5%–10% of vaccinated individuals do not generate an immune response to the vaccine, and its molecular mechanism has not been clarified. In this study, single-cell RNA sequencing was performed on peripheral blood mononuclear cells (PBMCs) from three volunteers with a high immune response (HR) and three with no immune response (NR) to the hepatitis B vaccine. We found that the antigen-presenting activity scores of various antigen-presenting cells, the mitogen-activated protein kinase (MAPK) pathway activity scores of naive B cells, and the cell activity scores of three types of effector T cells were significantly decreased, whereas the cytotoxicity scores of CD3highCD16lowKLRG1high natural killer T (NKT) cells were significantly increased in the NR group compared with those in the HR group. Additionally, the expression levels of some classical molecules associated with distinct signaling pathways—including HLA-B, HLA-DRB5, BLNK, BLK, IL4R, SCIMP, JUN, CEBPB, NDFIP1, and TXNIP—were significantly reduced in corresponding subsets of PBMCs from the NR group relative to those of the HR group. Furthermore, the expression of several cytotoxicity-related effector molecules, such as GNLY, NKG7, GZMB, GZMM, KLRC1, KLRD1, PRF1, CST7, and CTSW, was significantly higher in CD3highCD16lowKLRG1high NKT cells derived from non-responders. Our study provides a molecular basis for the lack of response to the hepatitis B vaccine, including defective antigen presentation, decreased T cell activity, and reduced IL-4 secretion, as well as novel insight into the role of NKT cells in the immune response to the hepatitis B vaccine

Toward Understanding the Relationship between Bitcoin Mixing Services and Circular Transactions

The anonymity of Bitcoin is always accompanied with illegal transactions and criminals’ evasion of legal prosecution. Furthermore, the recent introduction of a mixing service, an anonymous enhancement technology, has intensified the difficulty of analyzing user identity by using traditional methods. Actually, Bitcoin historical transactions are open and traceable. Therefore, these can be used to identify trading entities participating in mixing services. In this paper, we formally describe the mechanism of mixing services and the discovery of its correlation with circular trading. Then, a graph-clustering-based transaction network analysis algorithm is proposed to complete the detection of transaction cycles through three steps: address clustering, transaction graph construction and cycle detection. Through experiments with 1,500,000 real transaction records, we verify the correlation between the mixing service and circular transactions and the validity of the proposed detection algorithm. The work provides a basis for the regulatory authorities to crack down on illegal trading

STNet: A Time-Frequency Analysis-Based Intrusion Detection Network for Distributed Optical Fiber Acoustic Sensing Systems

Distributed optical fiber acoustic sensing (DAS) is promising for long-distance intrusion-anomaly detection tasks. However, realistic settings suffer from high-intensity interference noise, compromising the detection performance of DAS systems. To address this issue, we propose STNet, an intrusion detection network based on the Stockwell transform (S-transform), for DAS systems, considering the advantages of the S-transform in terms of noise resistance and ability to detect disturbances. Specifically, the signal detected by a DAS system is divided into space–time data matrices using a sliding window. Subsequently, the S-transform extracts the time-frequency features channel by channel. The extracted features are combined into a multi-channel time-frequency feature matrix and presented to STNet. Finally, a non-maximum suppression algorithm (NMS), suitable for locating intrusions, is used for the post-processing of the detection results. To evaluate the effectiveness of the proposed method, experiments were conducted using a realistic high-speed railway environment with high-intensity noise. The experimental results validated the satisfactory performance of the proposed method. Thus, the proposed method offers an effective solution for achieving high intrusion detection rates and low false alarm rates in complex environments

Label-Free Anomaly Detection Using Distributed Optical Fiber Acoustic Sensing

Deep learning anomaly detection is important in distributed optical fiber acoustic sensing (DAS). However, anomaly detection is more challenging than traditional learning tasks, due to the scarcity of true-positive data and the vast imbalance and irregularity within datasets. Furthermore, it is impossible to catalog all types of anomalies, therefore, the direct application of supervised learning is deficient. To overcome these problems, an unsupervised deep learning method that only learns the normal data features from ordinary events is proposed. First, a convolutional autoencoder is used to extract DAS signal features. A clustering algorithm then locates the feature center of the normal data, and the distance to the new signal is used to determine whether it is an anomaly. The efficacy of the proposed method was evaluated in a real high-speed rail intrusion scenario, and considered all behaviors that may threaten the normal operation of high-speed trains as abnormal. The results show that the threat detection rate of this method reaches 91.5%, which is 5.9% higher than that of the state-of-the-art supervised network and, at 7.2%, the false alarm rate is 0.8% lower than the supervised network. Moreover, using a shallow autoencoder reduces the parameters to 1.34 K, which is significantly lower than the 79.55 K of the state-of-the-art supervised network

Relation between neuroticism and tendency of mobile phone addiction among nursing undergraduates： the mediating role of perceived stress and self-control

BackgroundNegative effects of mobile phone addiction on undergraduate students have led to several health problems including depression， anxiety， attention deficit disorder， cognitive impairment and sleep disturbance. The undergraduate nursing students serve as an important reserve force of the clinical nursing work， and their poor psychological health would have a non-ignorable impact on the quality of the nursing work and the nurse-patient relationship in the future.ObjectiveTo investigate the relation between neuroticism and tendency of mobile phone addiction among undergraduate nursing students， and to examine the pathways through which perceived stress and self-control play a role in the relation by constructing a chain-mediated model.MethodsFrom February to March 2023， a total of 900 undergraduate nursing students across 10 universities in Xi'an， Shaanxi Province were selected through convenient sampling method. Several scales were adopted to assess undergraduate nursing students respectively， including the neuroticism subscale of Eysenck Personality Questionnaire-Revised Short Scale for Chines （EPQ-RSC）， Perceived Stress Scale （PSS）， Self-Control Scale （SCS） and Mobile Phone Addiction Tendency Scale （MPATS）. The assessment were conducted on multiple aspects of these students including neurotic personality， subjective stress， self-control and mobile phone addiction tendency. Model 6 in the SPSS Macro Process 4.1 was used to examine the mediating effect of perceived stress and self-control between neuroticism and mobile phone addiction tendency among undergraduate nursing students.Results① Among the 900 students， 314 cases （34.89%） were found to be addicted to mobile phones. ② The score of neuroticism subscale in EPQ-RSC of nursing undergraduates was positively correlated with the total scores of PSS and MPATS （r=0.400， 0.287， P<0.01）， and negatively correlated with score of SCS （r=-0.364， P<0.01）. The total score of MPATS was positively correlated with the total score of PSS （r=0.362， P<0.01）， and negatively correlated with the total score of SCS （r=-0.468， P<0.01）. The total score of SCS was negatively correlated with the total score of PSS （r=-0.515， P<0.01）. ③ Perceived stress and self-control performed partial mediation between neuroticism personality and mobile phone addiction tendency （with indirect effect values of 0.056 and 0.065， respectively， accounting for 19.72% and 22.89% of the total effect）. Perceived stress and self-control played a chain mediating role between neuroticism personality and mobile phone addiction tendency （with an indirect effect value of 0.064， accounting for 22.54% of the total effect）.ConclusionNeuroticism personality， perceived stress and self-control are confirmed to play important roles in mobile phone addiction tendency among undergraduate nursing students. Neuroticism personality not only directly affects the tendency of mobile phone addiction， but also affects their mobile phone addiction tendency through the chain mediating effect of perceived stress and self-control.［Funded by The 2020 Annual Project of the 13th Five-Year Plan of Education Science in Shaanxi Province （number， SGH20Y1386）

Plasmon-Assisted Trapping of Single Molecules in Nanogap

The manipulation of single molecules has attracted extensive attention because of their promising applications in chemical, biological, medical, and materials sciences. Optical trapping of single molecules at room temperature, a critical approach to manipulating the single molecule, still faces great challenges due to the Brownian motions of molecules, weak optical gradient forces of laser, and limited characterization approaches. Here, we put forward localized surface plasmon (LSP)-assisted trapping of single molecules by utilizing scanning tunneling microscope break junction (STM-BJ) techniques, which could provide adjustable plasmonic nanogap and characterize the formation of molecular junction due to plasmonic trapping. We find that the plasmon-assisted trapping of single molecules in the nanogap, revealed by the conductance measurement, strongly depends on the molecular length and the experimental environments, i.e., plasmon could obviously promote the trapping of longer alkane-based molecules but is almost incapable of acting on shorter molecules in solutions. In contrast, the plasmon-assisted trapping of molecules can be ignored when the molecules are self-assembled (SAM) on a substrate independent of the molecular length

Effects of coronary artery disease in patients with permanent left bundle branch area pacing: A retrospective study

Aims: Myocardial ischemia can affect traditional right ventricular (RV) pacing parameters, but it is unclear whether coronary artery disease (CAD) impact the pacing parameters and electrophysiological characteristics of left bundle branch area pacing (LBBaP) as a physiological pacing representative. Methods: Patients who underwent coronary angiography (CAG) after/before the LBBaP procedure and underwent percutaneous coronary intervention after LBBaP procedure were divided into CAD group and Non-CAD group according to visual CAG. Pacing parameters and electrophysiological characteristics were recorded at LBBaP implantation. Multivariate logistic regression analysis was implemented to evaluate the association between CAD and higher capture threshold. Sensitivity analyses were conducted to verify result stability. Results: A total of 176 patients met inclusion criteria (115 Non-CAD patients and 61 CAD patients) with a mean age of 71.1 ± 9.0 years. Compared with the Non-CAD patients, CAD patients had the higher capture threshold (0.67 ± 0.22 V vs. 0.82 ± 0.28 V, P < 0.001) and lower R-wave amplitude (12.5 ± 4.8 mV vs. 10.1 ± 2.7 mV, P = 0.001). Moreover, CAD was independently associated with higher capture threshold (adjusted Odds ratio (OR) 3.418, 95% confidence interval (CI): 1.621–7.206, P = 0.001), which was further validated through sensitivity analyses. Conclusion: Patients without CAD might have safer pacing parameters in the LBBaP procedure. Besides, CAD might be the risk factor of capture threshold increase during permanent LBBaP implantation

Plasmonic phenomena in molecular junctions: principles and applications

Molecular junctions are building blocks for constructing future nanoelectronic devices that enable the investigation of a broad range of electronic transport properties within nanoscale regions. Crossing both the nanoscopic and mesoscopic length scales, plasmonics lies at the intersection of the macroscopic photonics and nanoelectronics, owing to their capability of confining light to dimensions far below the diffraction limit. Research activities on plasmonic phenomena in molecular electronics started around 2010, and feedback between plasmons and molecular junctions has increased over the past years. These efforts can provide new insights into the near-field interaction and the corresponding tunability in properties, as well as resultant plasmon-based molecular devices. This Review presents the latest advancements of plasmonic resonances in molecular junctions and details the progress in plasmon excitation and plasmon coupling. We also highlight emerging experimental approaches to unravel the mechanisms behind the various types of light–matter interactions at molecular length scales, where quantum effects come into play. Finally, we discuss the potential of these plasmonic–electronic hybrid systems across various future applications, including sensing, photocatalysis, molecular trapping and active control of molecular switches. [Figure not available: see fulltext.]

Aberrant Cyclin D1 splicing in cancer: from molecular mechanism to therapeutic modulation

Abstract Cyclin D1 (CCND1), a crucial mediator of cell cycle progression, possesses many mutation types with different mutation frequencies in human cancers. The G870A mutation is the most common mutation in CCND1, which produces two isoforms: full-length CCND1a and divergent C-terminal CCND1b. The dysregulation of the CCND1 isoforms is associated with multiple human cancers. Exploring the molecular mechanism of CCND1 isoforms has offer new insight for cancer treatment. On this basis, the alterations of CCND1 gene are described, including amplification, overexpression, and mutation, especially the G870A mutation. Subsequently, we review the characteristics of CCND1 isoforms caused by G870A mutation. Additionally, we summarize cis-regulatory elements, trans-acting factors, and the splice mutation involved in splicing regulation of CCND1. Furthermore, we highlight the function of CCND1 isoforms in cell cycle, invasion, and metastasis in cancers. Importantly, the clinical role of CCND1 isoforms is also discussed, particularly concerning prognosis, chemotherapy, and radiotherapy. Last, emphasis is given to the corrective strategies that modulate the cancerous CCND1 isoforms. Thus, it is highlighting significance of aberrant isoforms of CCND1 as targets for cancer therapy