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ABSTRACT: B-cell translocation genes (BTG) have been proved to play important roles in carbohydrate metabolism through modifying insulin homeostasis and glucose metabolism. This study, therefore, was conducted to investigate the effects of exogenous insulin on the expression of BTG1 and BTG2 in chickens. Twenty-four-day-old broilers and layers were fasted for 16 h and randomly assigned to insulin treatment group (subcutaneously injected with 5 IU/kg body weight) or control group (received an equivalent volume of phosphate-buffered saline). Blood glucose concentration was measured, and it showed that the blood glucose concentrations in the layers were significantly (P < 0.05) higher than that in the broilers under fasting state. Response to exogenous insulin, the blood glucose concentrations were greatly reduced in both breeds. Of note, the blood glucose concentration restored to 62% of the basal state at 240 min (P < 0.05) after insulin stimulation in layers, whereas it was still in low level until 240 min in broilers (under fast state). Tissue profiling revealed that both BTG1 and BTG2 were abundantly expressed in the skeletal muscles of broilers. A negative correlation was observed between blood glucose and BTG1 (ρ = −0.289, P = 0.031) /BTG2 (ρ = −0.500, P < 0.001) in pectoralis, and BTG1 (ρ = −0.462, P < 0.001) in pancreas. As blood glucose decreased due to exogenous insulin administration (under fast state), the expression of both BTG1 and BTG2 notably upregulated in birds’ pectoralis at 120 min and/or 240 min, meanwhile pancreas BTG1 was also upregulated. Re-feeding at 120 min elevated the blood glucose and reduced the expression of BTG genes in pectoralis generally. In addition, the change of BTG1 and BTG2 expression showed distinct difference between layers and broilers at 120 min and 240 min after insulin stimulation in pectoralis, pancreas and heart tissue; even after re-feeding at 120 min, BTG2 expression at 240 min after insulin injection was downregulated in the pectoralis of layers, while it was upregulated in that broilers. Collectively, these results indicated that response to exogenous insulin, chicken blood glucose exhibited breed-specific dynamic change, and meanwhile the expressions of both BTG1 and BTG2 genes in chickens were significantly altered by exogenous insulin in a breed- and tissue-specific manner. BTG1 and BTG2 genes may negatively regulate bird's blood glucose by promoting the glucose uptake corporately in pectoralis, and through regulating the insulin secretion in pancreas (especially BTG1).

ABSTRACT: In addition to offering methionine, 2-hydroxy-4-methylthiobutyric acid (HMTBa) is also an organic acid and shows excellent bacteriostasis. Therefore, 3 experiments were conducted to determine the influence of drinking water supplemented HMTBa in combination with acidifier on performance, intestinal development, and microflora in broilers. The addition of different concentration (0.02–0.20%) of the blend of HMTBa and other acids significantly reduced the pH of water and exerted antimicrobial activity in dose-dependent manner in vitro. The outcomes from animal trial consisting of the drinking water with blended acidifier at 0.00, 0.05, 0.10, 0.15, and 0.20% indicated that the water with 0.15 or 0.20% acidifier resulted in linear and quadratic higher body weight at 42 d, gain and water consumption during 1 to 42 d (P < 0.05). In experiment 3, responding to graded blended acidifier in drinking water, birds receiving 0.10, 0.15, and 0.20% acidifier decreased the internal pH of gastrointestinal tract and muscle, and exhibited increased duodenal weight, length, villus high, and the ratio of villus high to crypt depth. Drinking water with 0.2% blended acidifier increased the abundance of probiotics (Bacteroidaceae, Ruminococcaceae, and Lachnospiraceae) and decreased the account of pathogenic bacteria such as Desulfovibrionaceae. Alternations in gut microflora were closely related to the metabolism of carbohydrate, amino acid, and vitamins. These findings, therefore, suggest that drinking water with 0.10 to 0.13% the combination HMTBa with acidifier might benefit to intestinal development and gut microbiota, and the subsequent produce a positive effect on the performance of broilers.

Optimal treatment for advanced cervical cancer after first line chemotherapy remains undefined. Immune checkpoint inhibition with pembrolizumab, a programmed cell death protein 1(PD-1) inhibitor, is under investigation. We analyzed the micro-environmental and molecular genetic profile of tumors from 4 patients with metastatic cervical cancer treated with off-label second-line pembrolizumab in an effort to identify predictive biomarkers. All patients received 2 mg/kg of pembrolizumab, 3-weekly until disease progression. Immunohistochemistry(IHC) for PD-1, PD-L1, CD3 and CD8, as well as next generation sequencing (NGS) for 50 cancer-related genes were performed on tumor samples. All patients tolerated treatment well with no discontinuation of treatment due to toxicity. One patient experienced dramatic and prolonged partial response, and remains stable on pembrolizumab with a progression free survival (PFS) of 21 months at the time of reporting of this series. Three patients experienced disease progression as best response. In the exceptional responder, there was no tumoral expression of PD-L1, however, combined positive score (CPS) for PD-L1 was 1 and we identified somatic mutations in ERBB4(R612W), PIK3CA(E542K) and RB1(E365K). In 2 patients, despite progressive disease defined by RECIST v1.1, symptom stabilization on pembrolizumab was observed. The tumors of both patients had PD-1 expression in ≥1% of stromal lymphocytes. All patients with response or clinical benefit had CPS for PD-L1 ≥ 1. NGS revealed PIK3CA mutations in 3 tumors. Pembrolizumab is a promising therapeutic option in advanced cervical cancer. Further evaluation of biomarkers may guide optimal patient selection. Keywords: Cervical cancer, Pembrolizumab, Immune checkpoint inhibition, Biomakers

The aim of this study was to evaluate the effects of geese’s maternal diet supplemented with flaxseed on the fatty acid profiles of egg yolks and the antioxidant status of their offspring. A total of 288 female Huoyan geese (42 weeks old) were randomly allotted to four experimental groups in this 56-day experiment and fed on diets containing flaxseed at 0% (control), 5%, 10% and 15%, respectively. There were nine replicate pens per treatment, with eight geese per replicate pen. The concentration of α-linolenic acid (linear, P

Lpin1 was a gene with important effects on controlling lipid/energy metabolism in humans and mice. However, little was known about chicken Lpin1 gene. In the present study, two transcript isoforms of chicken Lpin1 were identified. Lpin1-α was predicted encoding one 902 amino acid protein, whereas Lpin1-δ was predicted encoding one 918 amino acid protein with an insertion of 48-bp fragment from intron 12 of chicken Lpin1-α, and a conservative element was found to be located in intron 12 of chicken Lpin1-α genomic sequence. Ten variants were identified from chicken Lpin1-α coding sequence, and two missense mutations were predicted to affect the protein function of Lpin1. Reverse transcription PCR (RT-PCR) analysis revealed that chicken total Lpin1, Lpin1-α and Lpin1-δ were expressed in all analyzed tissues, and presented clear tissue expression differences. Real-time quantitative RT-PCR revealed that 30% energy restriction significantly elevated the total Lpin1 mRNA expression level in hepatic (P < 0.01) and adipose (P < 0.01) tissues of birds. Chicken total Lpin1 gene mRNA expression level presented a significantly inverse correlation with some traits including abdominal fat rate (P < 0.01), serum high-density lipoprotein (P < 0.05) and total cholesterol (P < 0.05), which would make a foundation for the further study on chicken Lpin1 gene function.

In recent years, the field of learning analytics has gained significant attention as educators and researchers seek to understand and optimize the learning process in online learning systems. This paper presents a novel methodology for predicting learning performance in online learning systems by leveraging natural language processing (NLP) and embedding techniques. The study focuses on two online learning systems, namely BookRoll and Viscode, and aims to analyze the learning behaviors of students using system logs extracted from the databases. The logs are converted into semester and daily learning description documents to capture the daily activities and progress of the learners. To transform the natural language data into numerical representations, the transformer-based BERT model, Google Gemini, and OpenAI large text embedding methodology are employed to generate embeddings for the learning descriptions. Subsequently, k-means clustering is applied to identify distinct learning behaviors exhibited by students. These clusters are labeled with numbers, and the daily learning descriptions are combined into a sequence, referred to as the DNA of learning behaviors. By utilizing this DNA representation, the learning status of students is effectively captured, and a machine learning model is trained to predict learning performance. The experimental results demonstrate the efficacy of the proposed methodology in achieving highly convincing predictions. The contributions of this research lie in the adoption of a unique approach, integrating NLP methodologies and embeddings techniques, to enable accurate learning performance prediction in online learning systems.