Transactivation of Human Endogenous Retroviruses by Tumor Viruses and Their Functions in Virus-Associated Malignancies.

Human endogenous retroviruses (HERVs), viral-associated sequences, are normal components of the human genome and account for 8–9% of our genome. These original provirus sequences can be transactivated to produce functional products. Several reactivated HERVs have been implicated in cancers and autoimmune diseases. An emerging body of literature supports a potential role of reactivated HERVs in viral diseases, in particular viral-associated neoplasms. Demystifying studies on the mechanism(s) of HERV reactivation could provide a new framework for the development of treatment and prevention strategies targeting virus-associated tumors. Although available data suggest that coinfection by other viruses, such as Kaposi’s Sarcoma-associated herpesvirus (KSHV) and Epstein–Barr virus (EBV), may be a crucial driving force to transactivate HERV boom, the mechanisms of action of viral infection-induced HERV transactivation and the contributions of HERVs to viral oncogenesis warrant further studies. Here, we review viral coinfection contributes to HERVs transactivation with focus on human viral infection associated oncogenesis and diseases, including the abilities of viral regulators involved in HERV reactivation, and physiological effects of viral infection response on HERV reactivation

CyFormer: Accurate State-of-Health Prediction of Lithium-Ion Batteries via Cyclic Attention

Predicting the State-of-Health (SoH) of lithium-ion batteries is a fundamental task of battery management systems on electric vehicles. It aims at estimating future SoH based on historical aging data. Most existing deep learning methods rely on filter-based feature extractors (e.g., CNN or Kalman filters) and recurrent time sequence models. Though efficient, they generally ignore cyclic features and the domain gap between training and testing batteries. To address this problem, we present CyFormer, a transformer-based cyclic time sequence model for SoH prediction. Instead of the conventional CNN-RNN structure, we adopt an encoder-decoder architecture. In the encoder, row-wise and column-wise attention blocks effectively capture intra-cycle and inter-cycle connections and extract cyclic features. In the decoder, the SoH queries cross-attend to these features to form the final predictions. We further utilize a transfer learning strategy to narrow the domain gap between the training and testing set. To be specific, we use fine-tuning to shift the model to a target working condition. Finally, we made our model more efficient by pruning. The experiment shows that our method attains an MAE of 0.75\% with only 10\% data for fine-tuning on a testing battery, surpassing prior methods by a large margin. Effective and robust, our method provides a potential solution for all cyclic time sequence prediction tasks

KSHV-Encoded MicroRNAs: Lessons for Viral Cancer Pathogenesis and Emerging Concepts

The human genome contains microRNAs (miRNAs), small noncoding RNAs that orchestrate a number of physiologic processes through regulation of gene expression. Burgeoning evidence suggests that dysregulation of miRNAs may promote disease progression and cancer pathogenesis. Virus-encoded miRNAs, exhibiting unique molecular signatures and functions, have been increasingly recognized as contributors to viral cancer pathogenesis. A large segment of the existing knowledge in this area has been generated through characterization of miRNAs encoded by the human gamma-herpesviruses, including the Kaposi's sarcoma-associated herpesvirus (KSHV). Recent studies focusing on KSHV miRNAs have led to a better understanding of viral miRNA expression in human tumors, the identification of novel pathologic check points regulated by viral miRNAs, and new insights for viral miRNA interactions with cellular (“human”) miRNAs. Elucidating the functional effects of inhibiting KSHV miRNAs has also provided a foundation for further translational efforts and consideration of clinical applications. This paper summarizes recent literature outlining mechanisms for KSHV miRNA regulation of cellular function and cancer-associated pathogenesis, as well as implications for interactions between KSHV and human miRNAs that may facilitate cancer progression. Finally, insights are offered for the clinical feasibility of targeting miRNAs as a therapeutic approach for viral cancers

The prognostic value of tumor-associated macrophages detected by immunostaining in diffuse large B cell lymphoma: A meta-analysis

BackgroundThe prognostic implication of tumor-associated macrophages (TAMs) in the microenvironment of diffuse large B cell lymphoma (DLBCL) remains controversial.MethodsA systematic and comprehensive search of relevant studies was performed in PubMed, Embase and Web of Science databases. The quality of the included studies was estimated using Newcastle-Ottawa Scale (NOS).ResultsTwenty-three studies containing a total of 2992 DLBCL patients were involved in this study. They were all high-quality studies scoring ≥ 6 points. High density of M2 TAMs in tumor microenvironment significantly associated with both advanced disease stage (OR= 1.937, 95% CI: 1.256-2.988, P = 0.003) and unfavorable overall survival (OS) (HR = 1.750, 95% CI: 1.188-2.579, P = 0.005) but not associated with poor progression free survival (PFS) (HR = 1.672, 95% CI: 0.864-3.237, P = 0.127) and international prognostic index (IPI) (OR= 1.705, 95% CI: 0.843-3.449, P = 0.138) in DLBCL patients. No significant correlation was observed between the density of CD68+ TAMs and disease stage (OR= 1.433, 95% CI: 0.656-3.130, P = 0.366), IPI (OR= 1.391, 95% CI: 0.573-3.379, P = 0.466), OS (HR=0.929, 95% CI: 0.607-1.422, P = 0.734) or PFS (HR= 0.756, 95% CI: 0.415-1.379, P = 0.362) in DLBCL patients.ConclusionThis meta-analysis demonstrated that high density of M2 TAMs in the tumor microenvironment was a robust predictor of adverse outcome for DLBCL patients.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42022343045

Fracture mechanism of air percussive rotary bit matrix based on impact stress wave theory

An air percussive rotary bit is a key component of air percussive rotary drilling technology, and its fracture failure seriously affects the safe operation and economic efficiency of drilling. This paper presents (1) theoretical analysis of the impact stress wave propagating in the air percussive rotary bit and effect of the stress wave on bit fracture and (2) finite element simulation study based on the stress wave theory which builds a model of the air hammer piston, drill and rock, defines material parameters, meshes and defines boundary conditions, clarifies propagation characteristics of the impact stress wave, analyzes stress characteristics of the bit matrix under different conditions (same drilling pressure and same piston speed, different drilling pressure and same piston speed and same drilling pressure and different piston speed) and determines the main factors of bit matrix fracture. The correctness of the theoretical analysis was verified with simulation results and fundamental ways of preventing bit fracture failure were proposed to provide a theoretical basis for the structural optimization design of a new bit. The results show that a bit section mutation is the root cause for the shock of the impact wave and the change in nature of the wave during propagation. The tensile wave is the root cause for bit matrix fracture, and a breakage is the most serious at stomatal interchanges. With increasing drilling pressure and piston speed, the rate of increase in the peak stress of the bit matrix increases, leading to early fatigue fracture of the bit matrix. The fracture of the bit matrix can be reduced, and the bit life can be extended by rationally designing the bit sectional structure parameters, ensuring that the bit withstands the effects of the compression wave so as to reduce the formation of a tensile wave, and rationally choosing drilling process parameters (such as drilling pressure and air pressure)

Evaluation on the possibility of sound conduction independent of tympanic air cavity for severe tympanic adhesion patients by finite element analysis

Background: For patients with severe tympanic adhesion, reconstructing the tympanic air cavity is often challenging, resulting in poor hearing reconstruction outcomes. Therefore, establishing a sound conduction pathway independent of the tympanic air cavity may be a viable method for reconstructing hearing in these patients.Purpose: The objective of this study was to evaluate the feasibility of sound conduction independent of the tympanic air cavity (i.e., replacing the original cavity with a tympanic vibrating material) using finite element analysis.Methods: We established a sound-structure coupling finite element model of the tympanum vibration conduction system, which included the tympanic membrane (TM), ossicular prosthesis, and tympanic vibrating material. This model was used to simulate middle ear vibrations under sound pressure, and we extracted the frequency response curve of the ossicular prosthesis’ vibration displacement amplitude to evaluate the sound conduction effect of the middle ear. Next, we adjusted the structural and mechanical parameters of the tympanic vibrating material to analyze its impact on the sound conduction effect of the middle ear. Finally, we compared the frequency response curve of the stapes footplate in normal subjects to evaluate the feasibility of sound conduction independent of the tympanic air cavity.Results: The Shell tympanic vibrating material had a better vibration conduction effect compared to solid or porous tympanic vibrating material. The vibration amplitude decreases with the increasing elastic modulus of the tympanic vibrating material. Implantation of 40 kPa-shell tympanic vibrating material had the lowest hearing loss less than 5 dB, and the hearing loss with 1 MPa-porous tympanic vibrating material was largest and less than 25 dB.Conclusion: Our study suggests that replacing the tympanic air cavity with a tympanic vibrating material is feasible. The establishment of a sound conduction pathway independent of the tympanic air cavity could potentially provide a method for hearing reconstruction in patients with severe tympanic adhesion

Vibration-based gearbox fault diagnosis using deep neural networks

Vibration-based analysis is the most commonly used technique to monitor the condition of gearboxes. Accurate classification of these vibration signals collected from gearbox is helpful for the gearbox fault diagnosis. In recent years, deep neural networks are becoming a promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data. In this paper, a study of deep neural networks for fault diagnosis in gearbox is presented. Four classic deep neural networks (Auto-encoders, Restricted Boltzmann Machines, Deep Boltzmann Machines and Deep Belief Networks) are employed as the classifier to classify and identify the fault conditions of gearbox. To sufficiently validate the deep neural networks diagnosis system is highly effective and reliable, herein three types of data sets based on the health condition of two rotating mechanical systems are prepared and tested. Each signal obtained includes the information of several basic gear or bearing faults. Totally 62 data sets are used to test and train the proposed gearbox diagnosis systems. Corresponding to each vibration signal, 256 features from both time and frequency domain are selected as input parameters for deep neural networks. The accuracy achieved indicates that the presented deep neural networks are highly reliable and effective in fault diagnosis of gearbox

Structure-based discovery of inhibitors of the YycG histidine kinase: New chemical leads to combat Staphylococcus epidermidis infections

BACKGROUND: Coagulase-negative Staphylococcus epidermidis has become a major frequent cause of infections in relation to the use of implanted medical devices. The pathogenicity of S. epidermidis has been attributed to its capacity to form biofilms on surfaces of medical devices, which greatly increases its resistance to many conventional antibiotics and often results in chronic infection. It has an urgent need to design novel antibiotics against staphylococci infections, especially those can kill cells embedded in biofilm. RESULTS: In this report, a series of novel inhibitors of the histidine kinase (HK) YycG protein of S. epidermidis were discovered first using structure-based virtual screening (SBVS) from a small molecular lead-compound library, followed by experimental validation. Of the 76 candidates derived by SBVS targeting of the homolog model of the YycG HATPase_c domain of S. epidermidis, seven compounds displayed significant activity in inhibiting S. epidermidis growth. Furthermore, five of them displayed bactericidal effects on both planktonic and biofilm cells of S. epidermidis. Except for one, the compounds were found to bind to the YycG protein and to inhibit its auto-phosphorylation in vitro, indicating that they are potential inhibitors of the YycG/YycF two-component system (TCS), which is essential in S. epidermidis. Importantly, all these compounds did not affect the stability of mammalian cells nor hemolytic activities at the concentrations used in our study. CONCLUSION: These novel inhibitors of YycG histidine kinase thus are of potential value as leads for developing new antibiotics against infecting staphylococci. The structure-based virtual screening (SBVS) technology can be widely used in screening potential inhibitors of other bacterial TCSs, since it is more rapid and efficacious than traditional screening technology

Carbon-Chain Molecules in Molecular Outflows and Lupus I Region--New Producing Region and New Forming Mechanism

Using the new equipment of the Shanghai Tian Ma Radio Telescope, we have searched for carbon-chain molecules (CCMs) towards five outflow sources and six Lupus I starless dust cores, including one region known to be characterized by warm carbon-chain chemistry (WCCC), Lupus I-1 (IRAS 15398-3359), and one TMC-1 like cloud, Lupus I-6 (Lupus-1A). Lines of HC3N J=2-1, HC5N J=6-5, HC7N J=14-13, 15-14, 16-15 and C3S J=3-2 were detected in all the targets except in the outflow source L1660 and the starless dust core Lupus I-3/4. The column densities of nitrogen-bearing species range from 10$^{12}$ to 10$^{14}$ cm$^{-2}$ and those of C$_3$S are about 10$^{12}$ cm$^{-2}$. Two outflow sources, I20582+7724 and L1221, could be identified as new carbon-chain--producing regions. Four of the Lupus I dust cores are newly identified as early quiescent and dark carbon-chain--producing regions similar to Lup I-6, which together with the WCCC source, Lup I-1, indicate that carbon-chain-producing regions are popular in Lupus I which can be regard as a Taurus like molecular cloud complex in our Galaxy. The column densities of C3S are larger than those of HC7N in the three outflow sources I20582, L1221 and L1251A. Shocked carbon-chain chemistry (SCCC) is proposed to explain the abnormal high abundances of C3S compared with those of nitrogen-bearing CCMs. Gas-grain chemical models support the idea that shocks can fuel the environment of those sources with enough $S^+$ thus driving the generation of S-bearing CCMs.Comment: 7 figures, 8 tables, accepted by MNRA