Changchun Institute of Biological Products

Genome integrity is essential for cellular survival and adaptation across diverse physiological states. The fission yeast Schizosaccharomyces pombe relies on conserved DNA repair pathways to maintain genome stability during proliferative growth and in the absence of cell division (quiescence/G0). Using 5-fluoroorotic acid (5-FOA) counter-selection, we examined spontaneous mutation accumulation in both conditions in a wild-type prototrophic strain. Unexpectedly, we identified in growing and quiescent cells a class of 5-FOA-resistant mutants that, unlike canonical ura4 or ura5 loss-of-function mutants, retain the ability to grow without uracil supplementation. Genetic analyses showed that this phenotype is stable and segregates as a single locus. Whole-genome sequencing of tetrads from independent crosses revealed multiple hypomorphic alleles of ura6, which encodes the essential uridylate kinase. These alleles, comprising non-synonymous substitutions and an in-frame duplication, cluster within conserved regions of the protein and likely reduce production of the toxic 5-FOA-derived metabolite while preserving sufficient uracil biosynthesis.

Rabies is an acute and fatal zoonotic disease caused by the rabies virus, responsible for approximately 59,000 deaths worldwide each year. Once clinical symptoms manifest, the case fatality rate approaches 100%. Vaccination remains the only effective strategy for prevention and control. Currently, human rabies vaccines approved by regulatory authorities such as the U.S. Food and Drug Administration (FDA), and the China National Medical Products Administration (NMPA) are all inactivated, adjuvant-free formulations. These vaccines are associated with several limitations, including weak immunogenicity, delayed induction of neutralizing antibodies, complex immunization schedules, and poor patient compliance. Adjuvants, as nonspecific immunoenhancers, can potentiate the immune response even at low antigen doses and reduce the number of required doses, offering a promising approach to overcome the aforementioned challenges. This article reviews recent advances in adjuvants suitable for rabies vaccines and discusses the key challenges currently faced in the development of adjuvanted rabies vaccines.

To address the problems of large computational complexity and proneness to falling into local optima of traditional localization methods in transformer dynamic localization, a satellite signal cumulative dynamic localization method based on multi-strategy improved particle swarm optimization is proposed. A received signal model and a cost function are established through time difference and frequency difference. Then, a good point set is introduced to initialize the population to ensure uniform distribution. Nonlinear dynamic adjustment of inertia weight and learning factors is adopted to balance global and local search. Combined with the Levy flight strategy, the ability of particles to jump out of local optima is enhanced, realizing efficient optimization of the cost function. Simulation experiments show that compared with the Exhaustive Search Direct Position Determination (ES-DPD) method and the Two-Step Localization Method, the proposed method has higher localization accuracy closer to the Cramér-Rao Lower Bound (CRLB) under low signal-to-noise ratio (SNR). The computation time is only 10.0965s within a search range of 10×10×10km, and the accuracy continues to improve with the increase of observation times. It achieves a balance between localization accuracy and computational efficiency, and is suitable for engineering practice.

Toll-like receptors (TLRs) play a pivotal role in the innate immune system by recognizing pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs), thereby initiating immune responses against viral infections. TLR agonists have emerged as promising adjuvants to enhance the efficacy of viral vaccines by modulating immune responses, improving antigen presentation, and promoting both humoral and cellular immunity. This review comprehensively summarizes the classification, signaling mechanisms, and immunomodulatory functions of cell-surface and intracellular TLRs. It further discusses the application of TLR agonists as adjuvants in vaccines against major viruses, including HBV, HCV, HIV, SARS-CoV-2, influenza, and flaviviruses. Key findings from preclinical and clinical studies highlight the potential of TLR agonists to overcome immune tolerance, enhance vaccine immunogenicity, and provide broad-spectrum protection. Finally, it points toward the “integration of precision adjuvants with novel vaccine platforms” as a core future direction, laying a theoretical and applied foundation for TLR agonists to become the next generation of viral vaccine adjuvants.

Two-stage oriented object detectors exhibit high detection accuracy and hold significant application value in civilian and military domains. However, existing methods suffer from inconsistent prediction results due to feature entanglement between localization and classification tasks, severely constraining detection performance. To address this issue, we proposes a task-specific feature disentanglement for two-stage oriented object detector (TSFDet). Inspired by the neural mechanisms underlying the human visual cognitive system, the method disentangles the features for localization and classification tasks by constructing a dual-branch feature pyramid network (FPN) architecture. An edge feature guidance network (EFGN) is designed for the localization branch, which extracts target edge gradient features using the sobel operator and enhances contour modeling capability through adaptive weighted fusion. A multi-level context feature enhancement network (MCEN) is constructed for the classification branch, leveraging graph convolutional networks (GCN) to model global semantic relationships for focusing on salient target regions. Simultaneously, a feature interaction module (FIM) is designed to achieve spatial alignment of the dual branches and complementary feature fusion by learning offset maps. Finally, a two-stage oriented decoupling detection head (TODH) is employed to further separate the feature paths for classification and localization. Comprehensive and extensive evaluations on three benchmarks, including DIOR-R, MAR20, and ShipRSImageNet, indicate that TSFDet significantly surpasses existing methods, achieving state-of-the-art performance.

State space models (SSMs), particularly Mamba, have garnered significant attention from researchers owing to their efficient balance between computational efficiency and model performance, and they also provide a performance breakthrough for accurate land cover classification of hyperspectral images (HSIs). However, HSI data feature high spectral dimensionality and dense spatial information, so efficiently constructing Mamba sequences that align with the structural characteristics of HSI data remains a critical unresolved issue. To address this challenge, we propose an efficient deformable spatial-spectral Mamba network (DSS-Mamba), which aims to efficiently mine valuable spatial-spectral features from HSIs. To achieve this goal, we design a two-branch architecture consisting of a spatial deformable Mamba and a spectral bidirectional Mamba: the spatial deformable scanning Mamba (SDSM) integrates a spatial deformable state space model (SD-SSM) and adaptively focuses on salient feature regions through a dynamic scanning strategy, while the spectral bidirectional scanning Mamba (SBSM) incorporates a spectral bidirectional state space model (SB-SSM) and fully exploits spectral dimensional information via a bidirectional scanning mechanism. During feature processing, we propose a spatial-spectral complementary fusion (SSCF) module, which refines feature weights by means of a dual-threshold enhancement unit (DTEU) to realize efficient processing and dynamic fusion of spatial-spectral features. Extensive experiments demonstrate that DSS-Mamba effectively balances the fine-grained capture of spatial-spectral features and computational efficiency through the adaptive capture of spatial features by the deformable structure, the in-depth mining of spectral information via bidirectional scanning, and the complementary fusion of the spatial-spectral module. Consequently, it achieves superior classification accuracy in land cover classification.

Oncolytic virus therapy is a rapidly developing cancer treatment method. The development of oncolytic viruses often involves genetic modifications, such as increased expression of foreign proteins for enhancing the antitumor capabilities and knocking out of virulence loci for improving the safety. The wild-type coxsackievirus B5 (CV-B5/F) exhibits potent antitumor activity against non-small cell lung cancer. However, CV-B5 poses pathogenic risks to infants and young children, warranting further virulence attenuation to develop a safe strain. No attenuating locus has been reported for CV-B5. In this study, we attenuated the original strain CV-B5/F by low-temperature passage for 30 generations and identified the virulence locus N157K in the structural protein VP1 using reverse genetics analysis. The attenuated strain carrying VP1-N157K retained the antitumor capabilities as the original strain. In addition, an exploration of the potential attenuation mechanisms revealed that the VP1-N157K mutation site weakened the replication ability of CV-B5. In summary, we identified a key virulence locus of CV-B5 and constructed an attenuated strain, which retains the oncolytic activity of the wild-type strain against non-small cell lung cancer with increased safety.

In this paper, the vibration control of a flexible high-rise building system with active mass dampers (AMD) is investigated under time-varying output constraints and input quantization. Firstly, a symmetric time-varying barrier Lyapunov function (BLF) is used to keep the system errors always within the given time-varying output constraint boundaries. Secondly, aiming to make sure that the system operates properly in communication networks with limited bandwidth resources, quantizers are introduced to quantize the control inputs to alleviate the burden of signal transmission and improve the efficiency of the system. Then, based on Lyapunov direct method, it is proved that the semi-global final consistency of the closed-loop system is bounded. Finally, the effectiveness of the proposed control scheme is verified by two cases of simulation comparisons, which can verify that the proposed controller ensures the better performance of the flexible high-rise building system.

In high-throughput gene sequencing, the quality of sequencing images is critical for the accuracy of subsequent base calling. However, during practical sequencing processes, the time delay integration (TDI) camera’s push-scan imaging often leads to significant degradation of image quality along the push-scan direction. Addressing the current limitations in TDI image restoration research for gene sequencing, this study establishes an imaging spectrum model of sequencing images based on MGI’s ultra-high-throughput sequencer. We systematically analyze the causes and intrinsic mechanisms of image quality degradation, with a focus on elucidating the specific impacts of TDI push-scanning on image quality. To enhance TDI sequencing image quality, we compare the differences in power spectral projection curves between stare-mode imaging and TDI push-scan imaging and propose a power spectrum curve compensation (PSCC)-based quality optimization method alongside a novel evaluation framework for sequencing image quality. Experimental results demonstrate that compared to original H-channel images from cycle 1 to 50, the energy concentration (1/σ) of the optimized images increases by 9.13% in the TDI direction and 4.64% in the direction perpendicular to TDI. Signal-to-noise ratio (SNR) increases by 6.90% for base A and 4.99% for base C, while base calling accuracy (Q30) improves by 1.67%.