成骨细胞在骨骼发育和矿化中扮演重要角色。然而，对肉仔鸡胫骨成骨细胞原代培养模型的建立和评价研究很少。因此，在目前研究中通试验1采用组织块法从1日龄AA肉公鸡胫骨中分离成骨细胞，通过细胞形态、碱性磷酸酶(ALP)染色和茜素红染色进行鉴定；试验2分别在成骨细胞持续培养第4、8、12、16、20、24、28和32天对原代培养的肉仔鸡胫骨成骨细胞的活力和矿化进行评价。

试验1结果表明，肉仔鸡胫骨原代成骨细胞呈梭形、三角形或多边形。ALP染色后95%以上细胞呈蓝黑色，连续培养4天后形成矿化结节；试验2结果表明，在整个培养过程中，虽然培养时间对乳酸脱氢酶(LDH)活性有影响(P=0.0012)，但LDH活性保持在相对稳定的水平。另外，培养时间显著影响(P≤0.0001)矿化结节的数量和面积比例，且随着培养时间的增加，其矿化结节数量呈线性和二次曲线增长(P<0.04)，并在24-32天内保持稳定。根据矿化结节数量和面积比例的最佳拟合断线模型或二次曲线模型(P<0.0001)评价最佳培养时间分别为17和26天。

结果表明，采用组织块法成功构建了肉仔鸡胫骨成骨细胞原代培养模型，其具有典型的成骨细胞形态、ALP活性和矿化特征，在持续培养4-32天内能保持相对稳定的活力，胫骨原代成骨细胞的最佳培养时间为17-26天。因此，该方法建立的肉鸡胫骨成骨细胞原代培养模型可用于进一步研究肉鸡骨骼发育和矿化的潜在机理。

本研究成功构建了稳定、可靠的肉鸡胫骨成骨细胞原代培养模型。

本研究旨在确定II b型钠磷协同转运载体（NaP-IIb）和无机磷转运载体2（PiT2）是否直接参与原代培养肉鸡鸡胚十二指肠上皮细胞磷吸收。针对NaP-IIb和PiT2基因设计小干扰RNA（siRNA）序列，合成并转染至原代培养肉鸡鸡胚十二指肠细胞，通过抑制效率分析筛选出对NaP-IIb和PiT2基因干扰有效的siRNAs，用于后续磷吸收试验。转染有效抑制NaP-IIb或PiT2的siRNA至原代培养肉鸡鸡胚十二指肠上皮细胞，待Transwell培养板上的细胞汇合成单层后，将磷转运载体基因（NaP-IIb或PiT2）沉默细胞或未转染细胞在含有0或0.25 mM磷（以KH₂PO₄形式引入）的吸收培养基中孵育，以检测十二指肠上皮细胞对磷的吸收。结果表明，si-1372和si-890分别为抑制NaP-IIb和PiT2基因表达的有效siRNA。与无磷组相比，添加磷可显著提高（P=0.065）原代培养肉鸡鸡胚十二指肠上皮细胞PiT2蛋白丰度，并增强（P<0.0001）其磷吸收。另外，NaP-IIb沉默显著降低（P=0.07）原代培养肉鸡鸡胚十二指肠上皮细胞磷吸收，但PiT2沉默对其并无影响（P=0.345）。综上所述，NaP-IIb可能直接参与肉鸡十二指肠上皮细胞磷吸收，而PiT2并未直接参与。

骨形态蛋白（bone morphogenetic protein，BMP）和促分裂原活化蛋白激酶（mitogen-activated protein kinase，MAPK）信号通路在调控骨骼形成和发育中扮演着重要角色。然而，目前关于肉鸡饲粮不同非植酸磷水平（non-phytate phosphorus，NPP）对这些信号通路及其与骨磷沉积和骨骼发育相关性的影响尚不清楚。因此，本试验旨在研究饲粮添加磷对肉鸡BMP和MAPK信号通路及其与骨磷沉积和骨骼发育相关性的影响。将800只1日龄AA肉公鸡按体重随机分成5个处理组，每个处理组8个重复。5个处理组饲粮的NPP水平分别为：1-21日龄：0.15、0.25、0.35、0.45和0.55%，22-42日龄：0.15、0.22、0.29、0.36和0.43%。试验结果表明，随着饲粮NPP水平的增加，14和28日龄肉鸡胫骨细胞外信号调节激酶1（Extracellular Signal-Regulated Kinase 1，ERK1）的mRNA表达、14日龄肉鸡胫骨磷酸化ERK1及28和42日龄肉鸡胫骨BMP2的蛋白表达线性降低（P<0.04），而42日龄肉鸡胫骨c-Jun氨基末端激酶1（c-Jun N-terminal kinase 1，JNK1）的mRNA表达线性增加（P<0.02）。在14日龄，肉鸡胫骨灰分总磷沉积量、骨矿物质含量、骨密度、骨强度及胫骨灰分与ERK1和JNK1 mRNA表达及磷酸化ERK1呈显著负相关（r=-0.726~-0.359，P<0.05），而胫骨碱性磷酸酶活性和骨钙素含量与ERK1 mRNA表达及磷酸化ERK1呈显著正相关（r=0.405~0.665，P<0.01）。在28日龄，肉鸡的胫骨灰分总磷沉积量、骨矿物质含量、骨密度、骨强度及胫骨灰分与ERK1 mRNA表达和BMP2蛋白表达呈显著负相关（r=-0.518~-0.370，P<0.05），而与胫骨碱性磷酸酶呈显著正相关（r=0.382~0.648，P<0.05）。结果表明，ERK1和JNK1 mRNA表达、BMP2蛋白表达及磷酸化ERK1与胫骨灰分总磷沉积量、骨矿物质含量、骨密度、骨强度及胫骨灰分呈显著负相关，但是与胫骨碱性磷酸酶活性和骨钙素呈显著正相关，表明肉鸡骨磷沉积和骨骼发育受BMP和MAPK信号通路的调节。本研究揭示了肉鸡骨磷沉积和骨骼发育受BMP和MAPK信号通路调节的机制。

Cuticular wax plays an important role in protecting land plant against biotic and abiotic stresses.  Cuticular wax production on plant surface is often visualized by a characteristic glaucous appearance.  This study identified quantitative trait loci (QTLs) for wheat (Triticum aestivum L.) flag leaf glaucousness (FLG) using a high-density genetic linkage map developed from a recombinant inbred line (RIL) population derived from the cross Heyne×Lakin by single-seed descent.  The map consisted of 2 068 single nucleotide polymorphism (SNP) markers and 157 simple sequence repeat (SSR) markers on all 21 wheat chromosomes and covered a genetic distance of 2 381.19 cM, with an average marker interval of 1.07 cM. Two additive QTLs for FLG were identified on chromosomes 3AL and 2DS with the increasing FLG allele contributed from Lakin.  The major QTL on 3AL, QFlg.hwwgr-3AL, explained 17.5–37.8% of the phenotypic variation in different environments.  QFlg.hwwgr-3AL was located in a 4.4-cM interval on chromosome 3AL that was flanked by two markers IWA1831 and IWA8374.  Another QTL for FLG on 2DS, designated as QFlg.hwwgr-2DS which was identified only in Yangling in 2014 (YL14), was flanked by IWA1939 and Xgwm261 and accounted for 11.3% of the phenotypic variation for FLG.  QFlg.hwwgr-3AL and QFlg.hwwgr-2DS showed Additive×Environment (AE) interactions, explaining 3.5 and 4.4% of the phenotypic variance, respectively.  Our results indicated that different genes/QTLs may contribute different scores of FLG in a cultivar and that the environment may play a role in FLG.

Avian influenza (AI), caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral contamination of poultry products in the food supply chain. Distinctions in AI outbreak between strains H5N1 and H7N9 indicate that early detection of the AI virus in poultry is crucial for the effective warning and control of AI to ensure food safety. Therefore, the establishment of a poultry surveillance system for food safety by early detection is urgent and critical. In this article, methods to detect AI virus, including current methods recommended by the World Health Organization (WHO) and the World Organisation for Animal Health (Office International des Epizooties, OIE) and novel techniques not commonly used or commercialized are reviewed and evaluated for feasibility of use in the poultry surveillance system. Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. Systematic approaches or integrated methods ought to be employed according to the application scenarios at every stage of the poultry supply chain to prevent AI outbreaks.