Growth hormone suppresses the expression of IGFBP-5, and promotes the IGF-I-induced phosphorylation of Akt in bovine mammary epithelial cells

Growth hormone (GH) plays a specific role to inhibit apoptosis in the bovine mammary gland through the insulin-like growth factor (IGF)-I system, however, the mechanism of GH action is poorly understood. In this study, we show that GH dramatically inhibits the expression of IGFBP-5, and GH along with IGF-I enhanced the phosphorylation of Akt through the reduction of IGF binding protein (IGFBP)-5. To determine how GH affects Akt through IGF-I in bovine mammary epithelial cells (BMECs), we examined the phosphorylation of Akt in GH treated BMECs and found that IGF-I induced phosphorylation of Akt was significantly enhanced by the treatment with GH. We demonstrated that GH reduces mRNA and protein expression of IGFBP-5 in BMECs, but it does not affect the expression of IGFBP-3. To determine that the enhanced effect of the Akt phosphorylation by the treatment of GH is due to the inhibition of the expression of IGFBP-5, we examined the effect of IGFBP-3 and -5 on the phosphorylation of Akt through IGF-I in the GH-treated BMECs. The phosphorylation of Akt was inhibited in a dose-dependent manner when IGFBP-5 was added at varying concentrations and was also inhibited in the presence of IGFBP-3. The results of this study suggest that GH plays an important role on mammary gland involution in bovine mammary epithelial cells.     

抗氰烯菌酯假禾谷镰孢突变体的诱导及其生物学特性

为评估引起小麦茎基腐病的病原菌假禾谷镰孢Fusarium pseudograminearum对氰烯菌酯的抗性风险,对5株敏感菌株进行了室内药剂驯化,获得33株抗性突变体,突变频率为16.5%,其对氰烯菌酯的抗性水平范围为7.39～1 665.76倍,3株表现低抗,4株表现中抗,26株表现高抗;发现在myosin-5基因上存在11种抗性突变类型,其中217位的丝氨酸突变为亮氨酸(S217L)、420位的谷氨酸突变为赖氨酸(E420K)和135位的丙氨酸突变为苏氨酸(A135T)为主要突变类型,其比例分别为45.5%、15.2%和9.1%。S217L型抗性突变体的产孢量显著下降,菌丝生长速率和致病力与亲本菌株无显著差异。E420K型抗性突变体的菌丝生长速率和致病力显著下降,产孢量与亲本菌株无显著差异。A135T型抗性突变体的菌丝生长速率和产孢量与亲本菌株无显著差异。研究结果表明假禾谷镰孢在药剂选择压力下易形成氰烯菌酯的抗性群体,对氰烯菌酯存在中到高等的潜在抗性风险,其myosin-5的点突变与其对氰烯菌酯的抗性相关。     

MicroRNA-9-5p mediates sympathetic overactivity by targeting KCNN3 in paraventricular nucleus of rats with T2D

AIM To investigate whether microRNA-9-5p （miR-9-5p） mediates sympathetic overactivity by targeting KCNN3 （potassium intermediate/small conductance calcium-activated channel, subfamily N, member 3） gene,which encoded small-conductance calcium-activated potassium channel 3 （SK3） protein, in paraventricular nucleus （PVN） of rats with type 2 diabetes mellitus （T2D）. METHODS A rat model of T2D was established by high-fat diet combined with intraperitoneal injection of 30 mg/kg streptozotocin. The levels of miR-9-5p and KCNN3 mRNA in PVN were detected by real-time PCR. The relationship between KCNN3 and miR-9-5p was predicted by TargetScan. Recombinant adeno-associated virus （rAAV）-miR-9-5p or KCNN3 were bilaterally microinjected into the PVN to observe the changes in plasma glucose levels and sympathetic drive indicators. The number of FosB and SK3 positive cells was measured by immunofluorescence staining. The protein expression of SK3 was determined by Western blot. The relationship between KCNN3 and miR-9-5p were confirmed by cell transfection and dual-luciferase reporter assay. RESULTS Compared with the rats in diabetes control （DC） group, the blood glucose, sympathetic drive indexes and the level of miR-9-5p in PVN were significantly increased, while the SK3 expression in PVN was obviously reduced in the diabetes mellitus （DM） rats. After microinjecion of rAAV-miR-9-5p in PVN, the sympathetic drive indexes, blood glucose, and the number of FosB-positive cells were increased significantly, but the SK3 protein expression was significantly reduced （P<0.05）. However, up-regulation of KCNN3 in PVN had the opposite effect. These responses were obviously enhanced in DM rats compared with DC rats. The results of cell transfection and dual-luciferase reporter assay demonstrated that miR-9-5p bound to the 3’-UTR of KCNN3 and inhibit its expression. CONCLUSION miR-9-5p was up-regulated in PVN of the rats with T2D, and it may mediate sympathoexcitation by targeting KCNN3.     

绵羊WNT5A基因克隆及其组织表达分析

WNT5A(Wnt family member 5A)参与了多种细胞的增殖、凋亡和分化等生物学过程,在乳腺形态发生、毛囊发育等方面发挥了重要作用.该试验利用RT-PCR获得绵羊WNT5A基因的CDS区,分析WNT5A蛋白的结构特征并利用RT-qPCR检测WNT5A基因在9个组织中的表达情况.绵羊WNT5A基因的CDS区...     

基于改进YOLOv8n的茶叶嫩稍检测方法

针对名优茶智能采摘中茶叶嫩梢识别精度不足的问题,该研究对YOLOv8n模型进行优化。首先,在主干网络中引入动态蛇形卷积（dynamic snake convolution,DSConv）,增强模型对茶叶嫩梢形状信息的捕捉能力;其次,将颈部的路径聚合网络（path aggregation network,PANet）替换为加权双向特征金字塔网络（bi-directional feature pyramid network,BiFPN）,强化模型的特征融合效能;最后,在颈部网络的每个C2F模块后增设了无参注意力模块（simple attention module,SimAM）,提升模型对茶叶嫩梢的识别关注度。试验结果表明,改进后的模型比原始模型的精确率（precision,P）、召回率（recall,R）、平均精确率均值（mean average precision,mAP）、F1得分（F1 score,F1）分别提升了4.2、2.9、3.7和3.3个百分点,推理速度为42 帧/s,模型大小为6.7 MB,满足低算力移动设备的部署条件。与Faster-RCNN、YOLOv5n、YOLOv7n和YOLOv8n目标检测算法相比,该研究提出的改进模型精确率分别高出57.4、4.4、4.7和4.2个百分点,召回率分别高出53.0、3.6、2.8和2.9个百分点,平均精确率均值分别高出58.9、5.0、4.6和3.7个百分点,F1得分分别高出了56.8、3.9、3.7和3.3个百分点,在茶叶嫩梢检测任务中展现出了更高的精确度和更低的漏检率,能够为名优茶的智能采摘提供算法参考。     

基于YOLOv5s-ESTC的肉苁蓉检测

为了解决因梭梭和红柳等宿主遮挡、样本分布密集、样本大小不均衡等造成人工种植肉苁蓉检测精度低以及模型参数量过大难以向嵌入式设备移植等问题,该研究提出一种基于改进YOLOv5s的人工种植肉苁蓉轻量化检测方法。首先,将YOLOv5s的主干网络替换为EfficientNetv2网络,以减少模型参数量和计算复杂度进而实现模型轻量化,便于后期将模型向嵌入式设备部署;其次,为了增强模型对小目标肉苁蓉特征信息的提取能力,将C3模块与Swin Transformer Block进行整合,得到C3STR模块,将其引入主干网络,并将其输出的特征图与Neck网络中的特征图进行融合;最后,在检测头前端与颈项加强网络之间添加CA注意力机制,以弱化背景信息、聚焦目标特征,提高网络检测性能。试验结果表明,该模型对于肉苁蓉的检测精度和准确率分别为89.8%和92.3%,模型的参数量和计算量分别为5.69×10⁶ MB和6.8 GB,权重文件大小为11.9 MB,单幅图像推理时间为8.9 ms,能够实现实时性检测。同其他主流模型相比,改进后的模型的检测精度分别比SSD、Faster R-CNN、YO...     

基于改进YOLOv7的杨梅树单木检测

为了快速检测和统计杨梅树的数量,该研究提出了一种基于改进YOLOv7的杨梅树单木检测模型：YOLOv7-ACGDmix。首先,对YOLOv7的可扩展高效长程注意力网络（extended-efficient long-range attention networks, E-ELAN）进行改进,通过融合兼具卷积和注意力机制优势的ACmix（a mixed model that enjoys the benefit of both self-attention and convolution）结构得到AC-E-ELAN模块,提升模型的学习和推理能力,引入可变形卷积（deformable convolutional networks version 2, DCNv2）结构得到DCNv2-E-ELAN模块,增强模型对不同尺寸目标的提取能力;其次,采用内容感知特征重组（content-aware reassembly of features, CARAFE）上采样模块,提高模型对重要特征的提取能力;然后,在主干和头部网络部分添加全局注意力机制（global-attention mechanism, GAM）,强化特征中的语义信息和位置信息,提高模型特征融合能力;最后,采用WIoU（wise intersection over union）损失函数减少因正负样本数据不平衡造成的干扰,增强模型的泛化性。在公开数据集上的试验结果表明,YOLOv7-ACGDmix模型的精确率达到89.1%,召回率达到89.0%,平均精度均值（mean average precision, mAP）达到95.1%,F₁-score达到89.0%,相比于原YOLOv7模型分别提高1.8、4.0、2.3和3.0个百分点。与Faster R-CNN、SSD、YOLOv8模型相比,改进模型的平均精度均值（mAP_0.5）分别提高了9.8、2.2、0.7个百分点。实地采集杨梅树样本数据的检测精确率87.3%、召回率85.7%。试验表明,改进模型为基于无人机影像的杨梅树单木检测提供了一种有效的解决方案,对果园精准管理的发展具有重要意义。     

水下底栖生物轻量化目标检测算法YOLOv7-RFPCW

针对水下底栖生物检测模型参数量过多,计算量过大,同时水下环境复杂容易造成错检和漏检,影响模型在水下底栖生物检测任务中的准确性的问题。提出了一种水下底栖生物轻量化检测算法YOLOv7-RFPCW。对YOLOv7网络重新设计轻量级网络结构,降低了特征提取网络的参数量和计算量,减少模型体积。设计了P-ELAN和P-ELAN-W模块,进一步轻量化特征提取网络;针对水下图像颜色失真,目标的空间位置不准确的问题,采用CBAM注意力模块加强特征融合,减少信息丢失,以更好地适应特殊的水下环境;针对水下目标容易出现形状变形的问题,使用WIOU-V3损失函数替换默认的CIOU损失函数,提高水下底栖生物检测的鲁棒性。试验结果显示,改进后的模型YOLOv7-RFPCW的参数量和计算量分别减少了75.9%和30.7%,模型体积减小了75.3%,精度提升了1.9个百分点。这一综合性的提升兼顾了轻量化和精度,为在水下环境中部署提供了可行的解决方案,验证了所提出的改进算法能胜任水下底栖生物检测任务。