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Muscle growth stands as a pivotal economic trait within pig production, governed by a complex interplay of multiple genes, each playing a role in its quantitative manifestation. Understanding the intricate regulatory mechanisms of porcine muscle development is crucial for enhancing both pork yield and quality. This study used the GSE99749 dataset downloaded from the GEO database, conducting a detailed analysis of the RNA-seq results from the longissimus dorsi muscle (LD) of Tibetan pigs (TP), Wujin pigs (WJ) and large white pigs (LW) at 60 days of gestation, representing diverse body sizes and growth rates. Comparative analyses between TPvsWJ and TPvsLW, along with differential gene expression (DEG) analysis, functional enrichment analysis, and protein–protein interaction (PPI) network analysis, revealed 1048 and 1157 significantly differentially expressed genes (p < 0.001) in TPvsWJ and TPvsLW, respectively. With stricter screening criteria, 37 DEGs were found to overlap between the 2 groups. PPI analysis identified MYL5, MYL4, and ACTC1 as the three core genes. This article focuses on exploring the MYL4 gene. Molecular-level experimental validation, through overexpression and interference of the MYL4 gene combined with EDU staining experiments, demonstrated that overexpression of MYL4 significantly promoted the proliferation of porcine skeletal muscle satellite cells (PSMSC), while interference with MYL4 inhibited their proliferation. Furthermore, by examining the effects of overexpressing and interfering with the MYL4 gene on the muscle hypertrophy marker Fst gene and the muscle degradation marker FOXO3 gene, the pivotal role of the MYL4 gene in promoting muscle growth and preventing muscle degradation was further confirmed. These findings offer a new perspective on the molecular mechanisms behind porcine muscle growth and development, furnishing valuable data and insights for muscle biology research.

With the rapid development of 3D reconstruction, especially the emergence of algorithms such as NeRF and 3DGS, 3D reconstruction has become a popular research topic in recent years. 3D reconstruction technology provides crucial support for training extensive computer vision models and advancing the development of general artificial intelligence. With the development of deep learning and GPU technology, the demand for high-precision and high-efficiency 3D reconstruction information is increasing, especially in the fields of unmanned systems, human-computer interaction, virtual reality, and medicine. The rapid development of 3D reconstruction is becoming inevitable. This survey categorizes the various methods and technologies used in 3D reconstruction. It explores and classifies them based on three aspects: traditional static, dynamic, and machine learning. Furthermore, it compares and discusses these methods. At the end of the survey, which includes a detailed analysis of the trends and challenges in 3D reconstruction development, we aim to provide a comprehensive introduction for individuals who are currently engaged in or planning to conduct research on 3D reconstruction. Our goal is to help them gain a comprehensive understanding of the relevant knowledge related to 3D reconstruction.

Productively infected cells are generally thought to arise from HIV infection of activated CD4+ T cells, and these infected activated cells are thought to be a recurring source of latently infected cells when a portion of the population transitions to a resting state. We discovered and report here that productively and latently infected cells can instead originate from direct infection of resting CD4+ T cell populations in lymphoid tissues in Fiebig I, the earliest stage of detectable HIV infection. We found that direct infection of resting CD4+ T cells was correlated with the availability of susceptible target cells in lymphoid tissues largely restricted to resting CD4+ T cells in which expression of pTEFb enabled productive infection, and we documented persistence of HIV-producing resting T cells during antiretroviral therapy (ART). Thus, we provide evidence of a mechanism by which direct infection of resting T cells in lymphoid tissues to generate productively and latently infected cells creates a mechanism by which the productively infected cells can replenish both populations and maintain two sources of virus from which HIV infection can rebound, even if ART is instituted at the earliest stage of detectable infection.

In recent years, the concept of the negative resistor (NR) has been proposed and applied in the magnetic coupled wireless power transfer (MC-WPT) system to improve the stability of power transfer. However, it remains a fundamental challenge to find the characteristic differences and applications of the four basic NR-based MC-WPT topologies. In this paper, the circuit models of the four basic NR-based MC-WPT topologies: series-series (SS), series-parallel (SP), parallel-parallel (PP), and parallel-series (PS) are established, and their characteristics are analyzed and compared by using circuit theory, which enables engineers to determine and select topologies to suit different applications and requirements. Theoretical analysis shows that the compensation methods of the transmitter and receiver of the NR-based MC-WPT system would affect the operating frequency and output characteristics of the system. Moreover, by comparative analysis, the conditions and applicable ranges for a stable output of different topologies were provided. Finally, the experimental prototypes are set up by using the power electronic inverter and operational amplifier, and the voltage gain ratios of the four basic NR-based WPT topologies under the variations of transfer distance and load are observed. The experimental results validate the correctness of the theoretical analysis.

Interleukin-10 (IL-10) is an immunosuppressive cytokine that signals through STAT3 to regulate T follicular helper (Tfh) cell differentiation and germinal center formation. In SIV-infected macaques, levels of IL-10 in plasma and lymph nodes (LNs) were induced by infection and not normalized with antiretroviral therapy (ART). During chronic infection, plasma IL-10 and transcriptomic signatures of IL-10 signaling were correlated with the cell-associated SIV-DNA content within LN CD4+ memory subsets, including Tfh cells, and predicted the frequency of CD4+ Tfh cells and their cell-associated SIV-DNA content during ART, respectively. In ART-treated rhesus macaques, cells harboring SIV-DNA by DNAscope were preferentially found in the LN B cell follicle in proximity to IL-10. Finally, we demonstrated that the in vivo neutralization of soluble IL-10 in ART-treated, SIV-infected macaques reduced B cell follicle maintenance and, by extension, LN memory CD4+ T cells, including Tfh cells and those expressing PD-1 and CTLA-4. Thus, these data support a role for IL-10 in maintaining a pool of target cells in lymphoid tissue that serve as a niche for viral persistence. Targeting IL-10 signaling to impair CD4+ T cell survival and improve antiviral immune responses may represent a novel approach to limit viral persistence in ART-suppressed people living with HIV.

Latency reversal strategies for HIV cure using inhibitor of apoptosis protein (IAP) antagonists (IAPi) induce unprecedented levels of latent reservoir expression without immunotoxicity during suppressive antiretroviral therapy (ART). However, full targeting of the reservoir may require combinatorial approaches. A Jurkat latency model screen for IAPi combination partners demonstrated synergistic latency reversal with bromodomain (BD) and extraterminal domain protein inhibitors (BETi). Mechanistic investigations using CRISPR-CAS9 and single-cell RNA-Seq informed comprehensive ex vivo evaluations of IAPi plus pan-BET, bD-selective BET, or selective BET isoform targeting in CD4+ T cells from ART-suppressed donors. IAPi+BETi treatment resulted in striking induction of cell-associated HIV gag RNA, but lesser induction of fully elongated and tat-rev RNA compared with T cell activation–positive controls. IAPi+BETi resulted in HIV protein induction in bulk cultures of CD4+ T cells using an ultrasensitive p24 assay, but did not result in enhanced viral outgrowth frequency using a standard quantitative viral outgrowth assay. This study defines HIV transcriptional elongation and splicing as important barriers to latent HIV protein expression following latency reversal, delineates the roles of BET proteins and their BDs in HIV latency, and provides a rationale for exploration of IAPi+BETi in animal models of HIV latency.

Greater than 90% of HIV-1 proviruses are thought to be defective and incapable of viral replication. While replication competent proviruses are of primary concern with respect to disease progression or transmission, studies have shown that even defective proviruses are not silent and can produce viral proteins, which may contribute to inflammation and immune responses. Viral protein expression also has implications for immune-based HIV-1 clearance strategies, which rely on antigen recognition. Thus, sensitive assays aimed at quantifying both replication-competent proviruses and defective, yet translationally competent proviruses are needed to understand the contribution of viral protein to HIV-1 pathogenesis and determine the effectiveness of HIV-1 cure interventions. Previously, we reported a modified HIV-1 gag p24 digital enzyme-linked immunosorbent assay with single molecule array (Simoa) detection of cell-associated viral protein. Here we report a novel p24 protein enrichment method coupled with the digital immunoassay to further extend the sensitivity and specificity of viral protein detection. Immunocapture of HIV gag p24 followed by elution in a Simoa-compatible format resulted in higher protein recovery and lower background from various biological matrices and sample volumes. Quantification of as little as 1 fg of p24 protein from cell lysates from cells isolated from peripheral blood or tissues from ART-suppressed HIV participants, as well as simian–human immunodeficiency virus–infected non-human primates (NHPs), with high recovery and reproducibility is demonstrated here. The application of these enhanced methods to patient-derived samples has potential to further the study of the persistent HIV state and examine in vitro response to therapies, as well as ex vivo study of translationally competent cells from a variety of donors.

The human–machine dialogue system allows people and the machine to communicate basically. This technology is also attracting more and more attention. It is conducive to the realisation of resource sharing, inheritance, and protection of Dongba culture worldwide to analyse the Naxi speech recognition for the protection and inheritance needs of Naxi Dongba culture. The model was established for Naxi speaker recognition, and the method is studied with text-independent speaker speech voice recognition. The practical analysis method was used to compare the application effect of Gaussian mixture model (GMM) and hidden Markov model (HMM) in the processing of speaker recognition in Naxi speaker's pronunciation. It is very useful to provide a theoretical basis for the establishment of a Naxi language-based human–computer interaction system to find out the speaker's voice characteristics, personality differences, and different regions. This is a theoretically necessary analysis of ethnic minority languages and the protection of ethnic and folk cultures. It can also provide practical significance for carrying out ethnic cultural differences analysis.

It is necessary to test the reliability of the operation of the machine itself for meeting the high-speed, ultra-precision, flexible, and other modern manufacturing and processing needs. In practical applications, the obtained reliability detection information presents a variety of uncertainties such as randomness, imprecision, incompleteness and so on, due to the complexity of the machining environment, the limitations of the sensor itself and the imperfections of the information acquisition technology. The uncertainty reasoning method is proposed to test reliability and accuracy precision. Based on the multi-sensor information characteristic, the rule of the credibility sets is established to achieve the operational reliability analysis. It can realise the uncertainty reasoning for the modal and reliability rules. Examples of analysis show that during the high-end CNC machine tools operational reliability analysis, it has a practical effect to study the uncertainty reasoning method of the modal and reliability propositional rule and the analysis basis can be provided for the precision degradation and fault diagnosis.

Zinc-coated steel sheets, a kind of high-quality sheet, is widely used in all sorts of manufacturing industry. The fault on its surface is one of the factors which exert bad effects on its quality. Due to its complex texture, the experts first put forward to the defect segmentation methods of Discrete Fourier Spectrum Residuals and Gabor Filtering Image Fusion. Then, they analysed the grey form of the faults and the deficiencies of the two methods and made some improvements on them using Morphological black hat operation and eventually achieved the goal of effective defect segmentation. According to some results of experiments, the improved method is of high accuracy in the defect segmentation and to some extent can serve as the reference method to examine the faults of the zinc-coated sheets.

In order to improve the operation reliability of high-grade computer numerical control (CNC) machine tools and reduce the maintenance time of failures, the remote state monitoring and intelligent maintenance system for CNC machine tools was proposed. Through collecting the basic information of equipment, maintenance information, and the information of the vibration, temperature, main current and power of the machine tool based on soft-bus technology, the system analysed the real-time state data, got the reliability parameters, extracted the fault features and established the maintenance knowledge base. Combining the dynamic monitoring data and static data, the system evaluated the key parts of machine tools. By the fault knowledge base, the system analysed the reason for failure and recommended the maintenance method. With the function modules, the system can improve the intelligent maintenance level of CNC machine tools and improve the using efficiency of machine tools.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a secreted protein that regulates hepatic low-density lipoprotein receptor (LDLR) levels in humans. PCSK9 has also been shown to regulate the levels of additional membrane-bound proteins in vitro, including the very low-density lipoprotein receptor (VLDLR), apolipoprotein E receptor 2 (ApoER2) and the β-site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1), which are all highly expressed in the CNS and have been implicated in Alzheimer's disease. To better understand the role of PCSK9 in regulating these additional target proteins in vivo, their steady-state levels were measured in the brain of wild-type, PCSK9-deficient, and human PCSK9 overexpressing transgenic mice. We found that while PCSK9 directly bound to recombinant LDLR, VLDLR, and apoER2 protein in vitro, changes in PCSK9 expression did not alter the level of these receptors in the mouse brain. In addition, we found no evidence that PCSK9 regulates BACE1 levels or APP processing in the mouse brain. In conclusion, our results suggest that while PCSK9 plays an important role in regulating circulating LDL cholesterol levels by reducing the number of hepatic LDLRs, it does not appear to modulate the levels of LDLR and other membrane-bound proteins in the adult mouse brain.