Essential oils are widely used in the pharmaceutical, food and cosmetic industries, and many plant essential oils have shown that they have positive effects on broilers nutrition. This experiment was conducted to study the effects of orally administered different dosages of carvacrol essential oils on intestinal barrier function in broiler chickens. A total of eighty 28-day-old (1.28 ± 0.15 kg) ROSS 308 broilers were randomly allocated to four groups of 20 replicates each, with one chicken per replicate per cage, and all were fed with the same diet. Four experimental groups were orally administered 0, 200, 300 or 400 μl carvacrol essential oils at 18:00 hr every day during the 2-week experimental period. As a result of which, the gene expression of the occludin, claudin-1, claudin-5, ZO-1 and ZO-2 in intestinal mucosa of small intestine (p < 0.05) and the goblet cell content in small intestine epithelium (p < 0.05) were significantly increased; test subjects with 300 or 400 μl carvacrol essential oils reduced the microbial counts of Salmonella spp. and Escherichia coli in the intestines (p < 0.05); Essential oils administration also significantly increased activity of the sucrase (p < 0.05) and lactase (p < 0.05) in intestinal mucosa. In conclusion, the carvacrol essential oils have positive effects on growth performance and intestinal barriers function of broilers; those effects may be related to the dosage, as administration of 300 or 400 μl was more effective than that of 200 μl.

The aim of this study was to investigate the effects of stimbiotic (STB), a xylanase and xylo-oligosaccharide complex. A total of 36 male weaned pigs with initial body weights of 8.49 ± 0.10 kg were used in a 3-week experiment. The experiment was conducted in a 2 × 3 factorial arrangement (six replicates/treatment) of treatments consisting of two levels of challenge (challenge and non-challenge) and three levels of STB (0, 0.5, and 1 g/kg diet). Supplementations STB 0.5 g/kg (STB5) and STB 1 g/kg (STB10) improved the G:F (p = 0.04) in piglets challenged with STEC. STB supplementation, which also decreased (p < 0.05) the white blood cells, neutrophils, lymphocytes, and expression levels of tumor necrosis factor-alpha and interleukin-6. Supplementations STB5 and STB10 improved (p < 0.01) the lymphocytes and neutrophils in piglets challenged with STEC on 14 dpi. Additionally, supplementations STB5 and STB10 improved (p < 0.01) the tumor necrosis factor-alpha in piglets challenged with STEC on 3 dpi. Supplementations STB5 and STB10 also improved the villus height-to-crypt depth ratio (p < 0.01) in piglets challenged with STEC. Supplementation with STB reduced (p < 0.05) the expression levels of calprotectin. In conclusion, STB could alleviate a decrease of the performance, immune response, and inflammatory response induced by the STEC challenge.

Since its development, deep learning has been quickly incorporated into the field of medicine and has had a profound impact. Since 2017, many studies applying deep learning-based diagnostics in the field of orthopedics have demonstrated outstanding performance. However, most published papers have focused on disease detection or classification, leaving some unsatisfactory reports in areas such as segmentation and prediction. This review introduces research published in the field of orthopedics classified according to disease from the perspective of orthopedic surgeons, and areas of future research are discussed. This paper provides orthopedic surgeons with an overall understanding of artificial intelligence-based image analysis and the information that medical data should be treated with low prejudice, providing developers and researchers with insight into the real-world context in which clinicians are embracing medical artificial intelligence.

PurposeThis study aimed to compare the clinical results of revision Bankart repair versus the Latarjet procedure for failed Bankart repair. MethodsA literature search was performed in databases, such as Pubmed, Embase, and Scopus Library. The studies were appraised using the Methodological Index for Non‐randomized Studies tool. Studies for failed Bankart repair with revision Bankart repair or Latarjet procedure were included. The pain VAS, ROWE score, rate of return to sports and preinjury level of sports, recurrent instability, range of motion, and complications were compared. Additionally, the pain VAS, ROWE score, forward flexion, and external rotation at side were subjected to a meta‐analysis. ResultsTwenty‐four articles were included in the systematic review. The functional outcomes in terms of the ROWE score, recurrent instability, return to sports, and the preinjury level of sports was better in the Latarjet procedure group than those in the revision Bankart repair group (ROWE score, 91 vs. 86.7; recurrent instability rate, 3.5% vs. 14.4%; return to sports rate, 100% vs. 87.9%; return to preinjury level of sports rate, 89.9% vs. 74.9%; all P < 0.001). However, the results of postoperative pain and the postoperative limitation of external rotation at side were worse in the Latarjet procedure group than those in the revision Bankart repair group (pain VAS, 1.4 vs. 0.8; postoperative external rotation at side, 38° vs. 60°; all P < 0.001). In addition, the majority of the complications occurred in the Latarjet procedure group. In the meta‐analysis, the postoperative ROWE score was significantly higher in the Latarjet procedure group than that in the revision Bankart group (revision Bankart repair: 95% CI 88.9–80.9, I2 = 65.70; Latarjet procedure: 95% CI 95.8–88.1, I2 = 93.37; P = 0.014). However, the pain VAS, forward flexion, and external rotation at side did not reach the significant level in the meta‐analysis. ConclusionCompared with revision Bankart repair, the Latarjet procedure for failed Bankart repair showed better ROWE scores, stability, and return to sports or preinjury level of sports; however, the postoperative pain and the limitation of external rotation at side were worse with more complications. IRB NoKUMC 2022–01‐024. Level of evidenceLevel IV.

Introduction Rotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic resonance imaging (MRI) is a commonly used diagnostic modality for RCT, but the interpretation of the results is tedious and has some reliability issues. In this study, we aimed to evaluate the accuracy and efficacy of the 3-dimensional (3D) MRI segmentation for RCT using a deep learning algorithm. Methods A 3D U-Net convolutional neural network (CNN) was developed to detect, segment, and visualize RCT lesions in 3D, using MRI data from 303 patients with RCTs. The RCT lesions were labeled by two shoulder specialists in the entire MR image using in-house developed software. The MRI-based 3D U-Net CNN was trained after the augmentation of a training dataset and tested using randomly selected test data (training: validation: test data ratio was 6:2:2). The segmented RCT lesion was visualized in a three-dimensional reconstructed image, and the performance of the 3D U-Net CNN was evaluated using the Dice coefficient, sensitivity, specificity, precision, F1-score, and Youden index. Results A deep learning algorithm using a 3D U-Net CNN successfully detected, segmented, and visualized the area of RCT in 3D. The model’s performance reached a 94.3% of Dice coefficient score, 97.1% of sensitivity, 95.0% of specificity, 84.9% of precision, 90.5% of F1-score, and Youden index of 91.8%. Conclusion The proposed model for 3D segmentation of RCT lesions using MRI data showed overall high accuracy and successful 3D visualization. Further studies are necessary to determine the feasibility of its clinical application and whether its use could improve care and outcomes.