Background: Goats (Capra hircus) have always been a source of fiber for human use and hold an important place in international high-end textiles. Fiber diameter is the most concerning economic indicator for producers. Understanding the formation mechanism of fiber diameter and its related key proteins can help optimize and control the production of cashmere. Methods: Cashmere goats (n = 36) of the Alpas (n = 18) and Alxa (n = 18) breeds, with a similar age (2 years old) and live weight (25–26 kg), were selected from the Yiwei White Cashmere Goat Breeding Farm, Erdos, Inner Mongolia. Using phenotypic indicators, we evaluated the diameter of the cashmere fibers in Alxa and Alpas goats. We also used electron microscopy to examine the cashmere fiber’s structure and label-free liquid chromatography–tandem mass spectrometry to determine the protein content of the two cashmere fibers. The proteins affecting fiber diameter were identified and analyzed by Western blot, Co-Immunoprecipitation, and bioinformatics analysis. Results: The average diameter of the Alxa breed was smaller (p < 0.05) than that of the Alpas breed (Alxa’s cashmere vs. Alpas’ cashmere). Proteomics technology enabled the highly confident detection of 171 proteins. A total of 68 differentially expressed proteins were identified in the two types of cashmere; 131 proteins were specifically expressed in Alpas goats, and 40 proteins were specifically expressed in Alxa goats. A key protein group that could cause variations in fiber diameter was found using the protein–protein interaction network. To ascertain the reason for the variation in fiber diameter, a structural study of the major protein groups was carried out. Conclusions: KRT10, KRT14, KRT17, and KRT82 are the main proteins impacting the diameter difference, and they have a substantial effect on the average fiber diameter.

The ability to recognize the body sizes of sheep is significantly influenced by posture, especially without artificial fixation, leading to more noticeable changes. This study presents a recognition model using the Mask R-CNN convolutional neural network to identify the sides and backs of sheep. The proposed approach includes an algorithm for extracting key frames through mask calculation and specific algorithms for head-down, head-up, and jumping postures of Ujumqin sheep. The study reported an accuracy of 94.70% in posture classification. We measured the body size parameters of Ujumqin sheep of different sexes and in different walking states, including observations of head-down and head-up. The errors for the head-down position of rams, in terms of body slanting length, withers height, hip height, and chest depth, were recorded as 0.08 ± 0.06, 0.09 ± 0.07, 0.07 ± 0.05, and 0.12 ± 0.09, respectively. For rams in the head-up position, the corresponding errors were 0.06 ± 0.05, 0.06 ± 0.05, 0.07 ± 0.05, and 0.13 ± 0.07, respectively. The errors for the head-down position of ewes, in terms of body slanting length, withers height, hip height, and chest depth, were recorded as 0.06 ± 0.05, 0.09 ± 0.08, 0.07 ± 0.06, and 0.13 ± 0.10, respectively. For ewes in the head-up position, the corresponding errors were 0.06 ± 0.05, 0.08 ± 0.06, 0.06 ± 0.04, and 0.16 ± 0.12, respectively. The study observed that sheep walking through a passage exhibited a more curved knee posture compared to normal measurements, often with a lowered head. This research presents a cost-effective data collection scheme for studying multiple postures in animal husbandry.

Acupuncturing the Zusanli (ST 36) point with different types of manual acupuncture manipulations (MAs) and different frequencies can evoke a lot of neural response activities in spinal dorsal root neurons. The action potential is the basic unit of communication in the neural response process. With the rapid development of the electrode acquisition technology, we can simultaneously obtain neural electrical signals of multiple neurons in the target area. So it is crucial to extract spike trains of each neuron from raw recorded data. To solve the problem of variability of the spike waveform, this paper adopts a optimization algorithm based on model to improve the wave-cluster algorithm, which can provide higher accuracy and reliability. Further, through this optimization algorithm, we make a statistical analysis on spike events evoked by different MAs. Results suggest that numbers of response spikes under reinforcing manipulations are far more than reducing manipulations, which mainly embody in synchronous spike activities.

The composition and function of the intestinal microbiota of Xinggao mutton sheep were explored before and post-weaning using non-target metabolomics. Both 16S rDNA amplicon sequencing technology and serum non-target metabolomics were used to determine changes in sheep metabolites and intestinal flora. A random sampling method was used to collect fecal samples from 20 pre-weaning lambs and 20 lambs post-weaning. Analysis of the intestinal flora identified Firmicutes as the predominant phylum pre-weaning and Bacteroidota as the dominant phylum post-weaning. Joint multi-omics analysis revealed that Oscillospiraceae UCG-005 and Prevotella_9 were significantly correlated with serum L-tyrosine, Indole-3-acrylic acid, and taurine-related metabolites, suggesting their potential roles in modulating digestive health in Xinggao mutton sheep.