In this study, we sought to isolate telocytes (TCs) from embryonic silky fowl skin, characterize their morphological features, and establish a stable in vitro culture system. The isolated and cultured TCs exhibited canonical morphological features, including 2-3 cytoplasmic prolongations (telopodes, Tps) with a moniliform structure. Morphometric analysis using ImageJ (FIJI) software revealed that Tps had an average length of 78.56 ± 10.66 μm, while their podoms and podomers exhibited average thicknesses of 0.20 ± 0.01 μm and 0.06 ± 0.01 μm, respectively. Immunofluorescence staining confirmed the identity of the isolated cells, with positive expression of CD34 and vimentin, consistent with known TCs markers. Transmission electron microscopy (TEM) observations indicated that Tps frequently established homocellular connections. Collectively, the isolated and in vitro-cultured cells exhibited structural and immunophenotypic features characteristic of TCs, confirming their successful isolation from avian embryonic skin. These cells establish a valuable in vitro model for future studies into the physiological functions of avian skin TCs.
Chicken livers can be sustainably developed into nutraceuticals through the circular-agriculture innovation chain. A supplement (GBHP01) formulated from chicken-liver hydrolysates contains free-type hypolipidemic amino acids (threonine, valine, leucine, isoleucine, and taurine) and the imidazole-ring dipeptide (anserine). In this study, mice were assigned to four groups: (1) Control: control diet (AIN-93M formula; fat providing 9.4% of total calories), (2) HFD: high-fat diet (fat providing 46.5% of total calories), (3) GBHP01.L: HFD supplemented with GBHP01 at 133.61 mg/Kg BW/day, and (4) GBHP01.H: HFD supplemented with GBHP01 at 267.22 mg/Kg BW/day. GBHP01 was administered by oral gavage. In 20-week HFD feeding, GBHP01 supplementation significantly reduced serum lipids, ALT, AST, and hepatic tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) concentrations, while enhancing reduced GSH, TEAC, catalase, and GSH-Px levels (p<0.05). Histological analysis revealed decreased hepatic lipid accumulation, associated with decreased diacylglycerol O-acyltransferase 2 (DGAT2) and increased acyl-CoA dehydrogenase medium chain (ACADM) expression. GBHP01 also promoted fecal bile acid and triglyceride excretion, indicating reduced fat absorption. Fecal microbiota profiling showed that HFD disrupted microbial diversity, increasing detrimental genera (Desulfovibrio, Bilophila, and Lachnoclostridium) while decreasing beneficial taxa (Lactobacillus and Akkermansia). GBHP01 may contribute to shifts in gut microbial composition by elevating probiotic species (L. reuteri and L. murinus) and reducing inflammatory taxa (Bilophila and Mucispirillum), suggesting its potential as a dietary intervention against HFD-induced metabolic disorders.
Currently, palpation remains the predominant method for classifying wooden breast (WB). This approach requires considerable labor and time resources, and it fails to precisely characterize the complex internal structural distribution of the disease and lacks a rational utilization plan for WB-affected breast fillets. Thus, the scientific stratification and classification of WB must be investigated. This study aims to characterize WB severity using ultrasound-derived internal spatial information, combined with ImageJ threshold binarization and scale calibration to quantify the spatial extent of pathological features. Herein, chicken breast fillets from Arbor Acres broilers were collected (n = 240, males, 42 days old) and categorized into four categories: normal (NORM, n = 60), mild (MILD, n = 60), moderate (MOD, n = 60), and severe (SEV, n = 60) conditions. WB samples were classified via ultrasound scanning and deep learning (DL). MobileNetV3, ResNet18, and AlexNet achieved training accuracies of 99.50%, 96.62%, and 95.64%, respectively, with validation accuracies of 98.71%, 90.09%, and 92.95%. For the four aforementioned classifications, the MobileNetV3 model achieved accuracies of 95%, 100%, 100%, and 99%, respectively, and exhibited a precision of 98.25%, a recall of 98.22%, and an F1-score of 98.23%. Image analysis delineated boundaries between pathological regions and normal muscle tissues in WB, validated by bioimpedance and stress-strain measurements. Segmentation ranges for MILD, MOD, and SEV pathological severity were determined as approximately 55%, 62%, and 65%, respectively, marking the first precise internal stratification of WB. Results showed that ultrasound imaging combined with DL effectively assessed myopathy distribution within WB, enabling accurate classification and stratification for practical applications.

