Zoological Research

1003−1014

Authors: Zhongyun Zhang, Ning Zhang, Xuancheng Lu, Min Zhou, Xiaoxiang Yan, Weiqiong Gu, Jingru Yang, Qin Zhang, Cheng Zhang, Yuhuan Gong, Mingjun Jia, Xiaoyu Zhang, Peng Ning, Mei Liu, Xiaoyan Li, Xiaomeng Shi, Wenjun Liu, George F. Gao, Guang Ning, Jiqiu Wang, Yuhai Bi

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can result in more severe syndromes and poorer outcomes in patients with diabetes and obesity. However, the precise mechanisms responsible for the combined impact of coronavirus disease 2019 (COVID-19) and diabetes have not yet been elucidated, and effective treatment options for SARS-CoV-2-infected diabetic patients remain limited. To investigate the disease pathogenesis, K18-hACE2 transgenic (hACE2Tg) mice with a leptin receptor deficiency (hACE2-Lepr-/-) and high-fat diet (hACE2-HFD) background were generated. The two mouse models were intranasally infected with a 5×105 median tissue culture infectious dose (TCID50) of SARS-CoV-2, with serum and lung tissue samples collected at 3 days post-infection. The hACE2-Lepr-/- mice were then administered a combination of low-molecular-weight heparin (LMWH) (1 mg/kg or 5 mg/kg) and insulin via subcutaneous injection prior to intranasal infection with 1×104 TCID50 of SARS-CoV-2. Daily drug administration continued until the euthanasia of the mice. Analyses of viral RNA loads, histopathological changes in lung tissue, and inflammation factors were conducted. Results demonstrated similar SARS-CoV-2 susceptibility in hACE2Tg mice under both lean (chow diet) and obese (HFD) conditions. However, compared to the hACE2-Lepr+/+ mice, hACE2-Lepr-/- mice exhibited more severe lung injury, enhanced expression of inflammatory cytokines and hypoxia-inducible factor-1α (HIF-1α), and increased apoptosis. Moreover, combined LMWH and insulin treatment effectively reduced disease progression and severity, attenuated lung pathological changes, and mitigated inflammatory responses. In conclusion, pre-existing diabetes can lead to more severe lung damage upon SARS-CoV-2 infection, and LMWH may be a valuable therapeutic approach for managing COVID-19 patients with diabetes.

1026−1038

Authors: Sen Yang, Zhi-Yuan Chen, Ke-Wei Liang, Cai-Jie Qin, Yang Yang, Wen-Xuan Fan, Chen-Lu Jie, Xi-Bo Ma

Quantification of behaviors in macaques provides crucial support for various scientific disciplines, including pharmacology, neuroscience, and ethology. Despite recent advancements in the analysis of macaque behavior, research on multi-label behavior detection in socially housed macaques, including consideration of interactions among them, remains scarce. Given the lack of relevant approaches and datasets, we developed the Behavior-Aware Relation Network (BARN) for multi-label behavior detection of socially housed macaques. Our approach models the relationship of behavioral similarity between macaques, guided by a behavior-aware module and novel behavior classifier, which is suitable for multi-label classification. We also constructed a behavior dataset of rhesus macaques using ordinary RGB cameras mounted outside their cages. The dataset included 65 913 labels for 19 behaviors and 60 367 proposals, including identities and locations of the macaques. Experimental results showed that BARN significantly improved the baseline SlowFast network and outperformed existing relation networks. In conclusion, we successfully achieved multi-label behavior detection of socially housed macaques with both economic efficiency and high accuracy.

1052−1063

Authors: Xin-Lai Wu, Dan-Ping Mu, Qi-Sen Yang, Yu Zhang, Yu-Chun Li, Anderson Feijó, Ji-Long Cheng, Zhi-Xin Wen, Liang Lu, Lin Xia, Zhi-Jun Zhou, Yan-Hua Qu, De-Yan Ge

Widespread species that inhabit diverse environments possess large population sizes and exhibit a high capacity for environmental adaptation, thus enabling range expansion. In contrast, narrow-range species are confined to restricted geographical areas and are ecologically adapted to narrow environmental conditions, thus limiting their ability to expand into novel environments. However, the genomic mechanisms underlying the differentiation between closely related species with varying distribution ranges remain poorly understood. The Niviventer niviventer species complex (NNSC), consisting of highly abundant wild rats in Southeast Asia and China, offers an excellent opportunity to investigate these questions due to the presence of both widespread and narrow-range species that are phylogenetically closely related. In the present study, we combined ecological niche modeling with phylogenetic analysis, which suggested that sister species cannot be both widespread and dominant within the same geographical region. Moreover, by assessing heterozygosity, linkage disequilibrium decay, and Tajima’s D analysis, we found that widespread species exhibited higher genetic diversity than narrow-range species. In addition, by exploring the “genomic islands of speciation”, we identified 13 genes in highly divergent regions that were shared by the two widespread species, distinguishing them from their narrow-range counterparts. Functional annotation analysis indicated that these genes are involved in nervous system development and regulation. The adaptive evolution of these genes likely played an important role in the speciation of these widespread species.

1080−1094

Authors: Cong Li, Rui Bi, Lin Wang, Yu-Hua Ma, Yong-Gang Yao, Ping Zheng

Tree shrews (Tupaia belangeri chinensis) share a close relationship to primates and have been widely used in biomedical research. We previously established a spermatogonial stem cell (SSC)-based gene editing platform to generate transgenic tree shrews. However, the influences of long-term expansion on tree shrew SSC spermatogenesis potential remain unclear. Here, we examined the in vivo spermatogenesis potential of tree shrew SSCs cultured across different passages. We found that SSCs lost spermatogenesis ability after long-term expansion (>50 passages), as indicated by the failure to colonize the seminiferous epithelium and generate donor spermatogonia (SPG)-derived spermatocytes or spermatids marking spermatogenesis. RNA sequencing (RNA-seq) analysis of undifferentiated SPGs across different passages revealed significant gene expression changes after sub-culturing primary SPG lines for more than 40 passages on feeder layers. Specifically, DNA damage response and repair genes (e.g., MRE11, SMC3, BLM, and GEN1) were down-regulated, whereas genes associated with mitochondrial function (e.g., NDUFA9, NDUFA8, NDUFA13, and NDUFB8) were up-regulated after expansion. The DNA damage accumulation and mitochondrial dysfunction were experimentally validated in high-passage cells. Supplementation with nicotinamide adenine dinucleotide (NAD+) precursor nicotinamide riboside (NR) exhibited beneficial effects by reducing DNA damage accumulation and mitochondrial dysfunction in SPG elicited by long-term culture. Our research presents a comprehensive analysis of the genetic and physiological attributes critical for the sustained expansion of undifferentiated SSCs in tree shrews and proposes an effective strategy for extended in vitro maintenance.

1115−1131

Authors: Yu-Juan Zhang, Zeyu Luo, Yawen Sun, Junhao Liu, Zongqing Chen

Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological research. This review provides an overview of the primary tasks, core models, datasets, and applications of AI in zoological research, including animal classification, resource conservation, behavior, development, genetics and evolution, breeding and health, disease models, and paleontology. Additionally, we explore the challenges and future directions of integrating AI into this field. Based on numerous case studies, this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom. As we build a bridge between beast and byte realms, this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.

1146−1151

Authors: Xiao-Long Liu, Jun-Kai Huang, Bryan L. Stuart, Ren-Da Ai, Justin M. Bernstein, Chatmongkon Suwannapoom, Siriwadee Chomdej, Jing Che, Zhi-Yong Yuan

 

1154−1155

Authors: Jing Cao, Zhen Liu