Proper feeding and nutrition are vital for maintaining the health of giant pandas (GPs), yet the impact of dietary changes and gut microbiota on their nutrient utilization remains unclear. To address these uncertainties, we investigated nutrient intake and apparent digestibility, as well as gut microbiota composition across different age groups of giant pandas: sub-adults (SGPs), adults (AGPs), and geriatrics (GGPs). Our findings revealed notable shifts in dietary patterns from SGPs to GGPs. As they aged, significantly more bamboo shoots and less bamboo were consumed. Consequently, GGPs showed significantly reduced crude fiber (CF) intake and digestibility, while crude protein (CP) did not alter significantly. In addition, 16S rRNA microbial sequencing results showed that unidentified_Enterobacteriaceae and Streptococcus were the dominant genera among all age groups. The relative abundance of the genus Enterococcus in GGPs was significantly higher than that in SGPs and AGPs (p < 0.05). Overall, our results indicated the importance of bamboo shoots as a major source of protein in GGPs’ diet, which can effectively compensate for the certain nutritional loss caused by the reduction in bamboo intake. Age-related changes in bacterial abundance have an effect on specific nutrient apparent digestibility in the gut of GPs. The data presented in this study serve as a useful reference for nutritional management in different ages of GPs under healthy conditions.

Baylisascaris schroederi is one of the main health risks threatening both wild and captive giant pandas. The administration of anthelmintics is a common method to effectively control B. schroederi infection, but there is a notable risk of anthelmintic resistance (AR) after long-term, constant use of anthelmintics. Four anthelmintics—pyrantel pamoate (PYR), mebendazole (MBZ), albendazole (ABZ), and ivermectin (IVM)—were each administered separately at intervals of 2 months to 22 enrolled giant pandas. The fecal egg count reduction (FECR) proportions were calculated by both the Markov chain Monte Carlo (MCMC) Bayesian mathematical model and the arithmetic mean. AR was assessed based on the criteria recommended by the World Association for the Advancement of Veterinary Parasitology (WAAVP). The estimated prevalence of B. schroederi infection was 34.1%. After treatment with PYR, MBZ, ABZ, and IVM, it was determined that MBZ, ABZ, and IVM were efficacious against B. schroederi, while nematodes were suspected to be resistant to PYR according to the fecal egg count reduction (FECR) proportions.

The giant panda (Ailuropoda melanoleuca), as an endemic and endangered species in China, has attracted much attention regarding its health issues. In recent years, certain diseases that affect giant pandas have gradually become important factors impacting their survival and breeding, including tumor diseases. Research on testicular cancer in giant pandas, in particular, has attracted the attention of scientific researchers because it poses a threat to individual reproductive function and population reproduction. This review systematically reviews the research progress of testicular cancer in giant pandas in recent years. Firstly, starting from case reports, the current research status of clinical manifestations, diagnostic methods and molecular mechanisms of testicular cancer in giant pandas was analyzed. Secondly, the commonly used treatment methods at present were discussed, including surgical resection, radiotherapy and chemotherapy, etc., and the advantages and disadvantages of these methods in practical applications were summarized. Furthermore, this article also conducts an in-depth exploration of the pathogenesis of testicular cancer in giant pandas, involving possible triggers such as genetic factors, environmental factors, and endocrine disorders. Based on the existing research results, this paper proposes a few future research directions, which will provide important support for the health management and population protection of giant pandas. Overall, although certain progress has been made in the research of testicular cancer in giant pandas, it still needs to be further deepened in order to provide a more powerful scientific basis for the healthcare and breeding of the endangered giant panda species.

Mate choice can vary with internal condition, but whether gut microbial variation is associated with female mate-choice-related olfactory preferences remains poorly understood. In this study, we tested whether dietary dried yeast supplementation was associated with changes in gut microbiota and odor preference in captive female giant pandas (Ailuropoda melanoleuca). Females in the dried yeast supplementation group received 10 g of dried yeast tablets daily for five consecutive days, while control females received the same diet without supplementation. Female olfactory preferences for urine from adult and senile males were assessed using odor preference tests before and after supplementation, and fecal samples were analyzed to characterize gut bacterial communities. Dried yeast supplementation altered the relative abundances of several gut bacterial taxa. Putatively beneficial taxa, including Muribaculaceae and Weissella cibaria, increased, whereas potentially pathogenic or opportunistic taxa, including Enterobacteriaceae and Campylobacter, decreased (all adjusted p < 0.05). Before supplementation, females showed no significant preference between adult and senile male urine. After supplementation, females showed a significant preference for adult male urine. Several gut bacterial genera were significantly associated with female exploratory behavior. These results suggest a possible association between dried yeast supplementation, gut microbial shifts, and female olfactory responses to male urinary cues.

Ex situ conservation in breading centers is one of the key strategies for saving giant pandas (Ailuropoda melanoleuca). Abnormal behaviors (e.g., inappetence) are key symptoms of potential health issues (e.g., Klebsiella pneumoniae) for the captives. Therefore, monitoring their normal activity patterns could set a baseline to detect these abnormalities for implementing timely interventions. However, traditional monitoring methods are labor-intensive, which often rely on manual observations. Here, we proposed a deep learning framework, termed as DeepPanda, for automatically recognizing four essential behaviors (i.e., eating, walking, resting and drinking) of giant pandas based on videos from common surveillance cameras. Experimental results demonstrated that the DeepPanda model achieved high performance on the self-established APanda dataset, with the testing mean average precision at an IoU threshold of 0.5 (mAP@0.5) of 98.8%. This methodology provides a powerful tool for monitoring the captive giant panda’s behaviors.