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关键词： 急性胰腺炎   直方图分析   磁共振成像   大黄素   微循环   大鼠  

摘要： 目的 探究基于多参数磁共振成像(magnetic resonance imaging, MRI)构建急性胰腺炎(acute pancreatitis, AP)大鼠微循环障碍及炎症负荷的程度量化评估体系,验证对比增强比(contrast enhancement ratio, CR)及直方图(histogram)参数在大鼠胰腺损伤评价中的价值,并探索大黄素(emodin)在活体状态下的潜在保护作用。材料与方法共纳入45只Sprague-Dawley(SD)大鼠,分为AP组、大黄素干预(emodin treated, ET)组和对照(control, CN)组,每组15只。利用3.0 T MRI获取增强T1WI图像,并测定图像CR、偏度(Skewness)和峰度(Kurtosis)。同时检测血清淀粉酶、脂肪酶及肌酐水平,进行组织学评分(histological score, HS),测定诱导型一氧化氮合酶(inducible nitric oxide synthase, iNOS)表达。采用Spearman秩相关系数分析影像学参数与病理指标间的相关性,进一步使用多元回归分析构建AP损伤预测模型,通过受试者工作特征(receiver operating characteristic, ROC)曲线评价模型预测效能。结果 AP组影像指标明显异常,CR和Skewness升高(P<0.001),Kurtosis降低(P<0.05),差异均有统计学意义;ET组三项影像指标均较AP组改善(P<0.05),差异具有统计学意义,并趋近CN组水平。相关性分析证明,CR与HS及iNOS阳性表达量呈显著中到高度正相关(ρ=0.64~0.85,P<0.001),Kurtosis与HS呈显著负相关(ρ=-0.84,P<0.001)。多元回归分析证明,CR为HS独立预测因子(β=6.69,P<0.05),而Kurtosis与HS呈显著负相关(β=-2.56,P<0.001),Skewness无独立预测价值(P>0.05)。以HS≥12作为重度AP的界值,CR+Kurtosis联合模型预测准确率达89.6%,曲线下面积(area under the curve, AUC)为0.95。结论 CR、Skewness和Kurtosis能够从灌注状态与结构异质性两方面无创量化AP损伤。其中CR主要反映微循环灌注变化,Kurtosis与组织结构破坏程度相关性更强。多参数MRI能敏感检测大黄素减轻炎症、改善微循环的保护效应,为AP严重程度分级及治疗疗效动态评估提供可靠的无创影像学方法,具有潜在临床应用价值。

关键词： dental abutments   dental prosthesis retention   resin cements   TheraCem  

摘要： Statement of the ProblemRetention is still a primary concern in conservatively managing short clinical crowns (SCC) and minimal restorative space. In modern dentistry, there is a growing expectation for the durability and retention of indirect restorations, along with a high esthetic demand, even in unfavorable underlying *** study aims to establish a reliable approach for the conservative treatment of SCCs using monolithic zirconia crowns (MZC).Materials and MethodsSixty human molars were collected and mounted in resin blocks. The teeth were prepared with two different abutment heights (2 and 4 mm). MZCs with buccal and lingual projections were designed and milled after digital scanning. Half of the restorations were cemented with TheraCem (TC) calcium silicate-based self-adhesive resin cement, while the remaining half were cemented with glass ionomer (GI) cement. The specimens underwent thermocycling and cyclic loading. A traction test was then performed in the universal testing machine to evaluate the debonding forces. Data was analyzed using Pearson correlation and one-way ANOVA *** strong positive correlation was shown in Pearson analysis between the assigned group and the pull-out force (r = 0.95, p-value <= 0.01). In addition, ANOVA found a significant mean difference in the pairwise comparison of groups. Increasing abutment height in groups with either GI or TC cement type resulted in increased measured force. More importantly, TC groups have shown a greater average value than specimens with GI *** demonstrated the significant influence of TC cement on the pull-out force measurement, outperforming the GI cement. The abutment height also showed a smaller contribution to the force measurement. Low-thickness monolithic zirconia restorations cemented with self-adhesive resin cement can be recommended as a reliable and effective treatment option for clinicians managing cases with SCCs and compromised retention.

关键词： animal cancers   CAM   chicken embryos   chorioallantoic membrane   in ovo/ex ovo model  

摘要： In recent years, particular attention has been paid to the possible connections, similarities, and potential uses of animals, especially pets (dogs and cats), in research on the causes, characteristics, and treatment of cancers occurring in pets and humans. One of the most promising experimental research models used to explore these issues is the avian embryo chorioallantoic membrane (CAM). This review aims to highlight the problem of the occurrence of cancers in domestic animals, placing emphasis on types, incidence, and predispositions of dogs and cats. Methodology and applications in cancer studies of this unique model were presented in detail. Moreover, the advantages and disadvantages of this diagnostic tool, as well as potential and future perspectives, were also described. This review confirms that cancer research can be conducted without the use of animals. Furthermore, the CAM can provide a robust and reliable model for this type of research and provide translational potential as an ethical, cost-effective model bridging laboratory and clinical research.

关键词： CAD   polymorphism   CYP17A1 gene   CAD   polymorphism  

摘要： Purpose: This study aimed to investigate the association between CYP17A1 gene polymorphisms and coronary artery disease (CAD) risk in a Chinese population.
Patients and Methods: A total of 2221 subjects (1363 CAD patients and 858 controls) were enrolled. Five single-nucleotide polymorphisms (SNPs) (rs11191548, rs17115100, rs4409766, rs6162, and rs6163) were genotyped. To account for multiple testing across genetic models, the false discovery rate (FDR) correction was applied. A nomogram incorporating CYP17A1 genetic variants and clinical characteristics was developed to predict CAD risk.
Results: In the overall population, preliminary association analyses identified three SNPs (rs11191548, rs17115100, rs4409766) with genotype distributions significantly different between cases and controls under recessive models. These associations remained significant after FDR correction for multiple testing across all 5 SNPs and 3 genetic models tested (all q = 0.035). Subsequent multivariate logistic regression, adjusted for clinical confounders, confirmed independent protective effects: the CC genotype of rs11191548 (OR = 0.507, 95% CI: 0.352- 0.730, P < 0.001), the CC genotype of rs4409766 (OR = 0.557, 95% CI: 0.394- 0.786, P = 0.001), and the TT genotype of rs17115100 (OR = 0.632, 95% CI: 0.473- 0.844, P = 0.002). The integrated nomogram achieved an area under the curve (AUC) of 0.727- 0.728 for CAD risk prediction. Moreover, exploratory sex-stratified analyses indicated potential sex-specific associations, with some variants linked to CAD risk in either males or females at a nominal significance level.
Conclusion: The rs11191548, rs17115100, and rs4409766 variants of the CYP17A1 gene were found to be associated with CAD in a Chinese population.

摘要： 随着服装产业数字化转型升级的加速推进,传统服装计算机辅助设计(computer-aided design, CAD)教学面临新的挑战与机遇。人工智能(artificial intelligence, AI)技术融入中职服装CAD教学,是教学改革、产教融合和技能型人才培养的必然方向。本文探讨AI技术与中职服装CAD教学的融合价值,分析其在课程内容重构、教学方法创新、教学策略优化方面的具体应用路径,以期为职业教育数字化转型提供参考,助力培养适应产业升级的高素质服装技术技能人才。

关键词： Ca2+ signals   NtBAG5   NtCaM   senescence   tobacco   yellowing  

摘要： Leaf yellowing critically impacts tobacco quality and economic value. The Bcl-2-associated athanogene (BAG) gene family regulates plant development and senescence, yet the role of NtBAG5 in tobacco remains poorly understood. Here, we demonstrate that NtBAG5 acts as a key promoter of leaf senescence. CRISPR/Cas9-generated NtBAG5 mutants exhibited delayed senescence, enhanced activities of antioxidant enzymes, and reduced malondialdehyde (MDA) content, whereas NtBAG5-overexpressing plants showed the opposite effects. Promoter-GUS analysis revealed high NtBAG5 expression in roots and stems. Hormone treatments indicated that NtBAG5 expression is upregulated by ABA, ETH, IAA, and GA (at late stage) but downregulated by MeJA. Mechanistically, NtBAG5 interacts with calmodulin (CaM) via its BAG domain and IQ motif, as confirmed by yeast two-hybrid and BiFC assays. Ca2 + was found to modulate CaM conformation and strengthen the NtBAG5-CaM interaction. Silencing NtCaM via VIGS induced severe leaf yellowing and growth defects. Our results reveal that the NtBAG5-CaM complex, regulated by Ca2 + and hormones, modulates leaf senescence through the antioxidant system, providing new insights for improving tobacco quality.

关键词： CAEVMD   multiscale convolutional neural networks   CAM   SAM   sparse penalty  

摘要： Rolling bearings inevitably generate noise during operation, which reduces diagnostic accuracy. In this paper, we propose a center-frequency-learning Variational Modal Decomposition (VMD) combined with a Convolutional Autoencoder (CAE) (CAEVMD) to process noisy signals and extract fault features, using a multiscale Convolutional Neural Network (CNN) for bearing fault diagnosis. First, the noisy signal is fed into the VMD for decomposition. The decomposed modal signal is sparsely penalized to suppress the modal noise. The sparsely penalized modal component is encoded, compressed, decoded, and reconstructed. The reconstructed output signal shows reduced noise. Secondly, the fault features are extracted using a multiscale dilated Convolutional Neural Network, combined with the Spatial Attention Mechanism (SAM) and the Channel Attention Mechanism (CAM), for fault diagnosis. Validated on the Western Reserve University bearing dataset and the simulated bearing experimental dataset, the experimental results show that the proposed network model achieves high diagnostic accuracy across different noise conditions, outperforms the comparative methods, and demonstrates high accuracy, robustness, and good generalization.

关键词： Inflammatory bowel disease   polyphenols   polysaccharides   short-chain fatty acids   probiotics   microbiota   antioxidants   anti-inflammatory  

摘要： Inflammatory bowel disease (IBD) is a chronic autoimmune condition whose pathogenesis has not been fully elucidated, and current treatments are not definitive and often carry several side effects. The Complementary and Alternative Medicine (CAM) offers a new approach to conventional medicine. However, their clinical application and mechanisms remain ***: The aim of this review is to evaluate the anti-inflammatory, impact on microbiota and antioxidant efficacy of currently available CAM for ***: The literature collection was obtained from Google Scholar, MEDLINE, PubMed and Web of Science (WOS). Studies in both human and animal models, published in English language between 2018 and 2024, were selected. Sixty-seven studies were included in the current review after inclusion and exclusion screening ***: Mostly, studies showed significant anti-inflammatory, gut microbiota restoring, antioxidant effects of polyphenols, polysaccharides, emodin, short-chain fatty acids (SCFA;including butyrate, propionate and acetate), and probiotics although some contrasting results were noted. Current evidence shows that polyphenols exhibit the most consistent result in alleviating IBD pathophysiology, primarily due to their significant SCFA-elevating ***: Future studies may focus on human studies, narrowing down on individual factors which may change natural product's metabolism. Further research studies are also essential to obtain therapeutic recommendations.

关键词： deep learning   pneumothorax   CAD   chest x-rays   pneumonia   chest radiographs  

摘要： Lung diseases remain a major global health concern, necessitating the development of advanced diagnostic methods. A chest x-ray is the most common diagnostic tool for lung diseases in medical practice. This research explores the application of deep learning in computer-aided diagnosis (CAD) for lung disease screening. The proposed computational model is evaluated against existing methodologies to assess its efficacy in detecting lung diseases using chest x-ray datasets. This study presents the development and evaluation of a DL-based classification model designed to automatically detect and differentiate pneumothorax and pneumonia from normal images of chest radiographs. The model is trained and validated using publicly available benchmark datasets to ensure its robustness and generalizability and then tested with images obtained from Maharishi Markandeshwar Institute of Medical Science and Research, Mullana, Ambala. The pre-processed images trained and tested with several pre-trained models based on CNN Vgg-16, EfficientNet, Inception, MobileNet, MobileNetV2, MobileNetV3small. MobileNetV3small achieved the highest accuracy of 97% in classifying lung diseases. This model also evaluates the match percentage of detected disease which helps medical experts identifying disease which otherwise are sometimes difficult to identify and helpful for new radiologists. The proposed model achieved high accuracy in diagnosing chest diseases using chest x-rays. Evaluation on the testing dataset demonstrated that the model significantly outperforms existing methods in terms of classification performance.