Embryonic development is a critical period for phenotype formation.Environmental variation during embryonic development can induce changes in postnatal phenotypes of animals.The thyroxine secretion and aerobic metabol...Embryonic development is a critical period for phenotype formation.Environmental variation during embryonic development can induce changes in postnatal phenotypes of animals.The thyroxine secretion and aerobic metabolic activity of small birds are important phenotypes closely related to their winter survival.In the context of climate change,it is necessary to determine whether temperature variation during incubation in birds leads to developmental plasticity of these cold responsive phenotypes.We incubated Japanese Quail(Coturnix japonica)eggs at 36.8℃,37.8℃,and 38.8℃,and raised the chicks to 35-day old at 22℃with same raising conditions,then all the quails were exposed to gradually temperature dropping environment(from 15℃to 0℃).After cold treatment,serum T3 level,resting metabolic rate,skeletal muscle and liver metabolomes of the birds were measured.The serum T3 levels were significantly lower in the 38.8℃group and significantly higher in the 36.8℃group compared to the 37.8℃group.The metabolic rate in the 38.8℃group was significantly lower compared to the 37.8℃group.Compared with the 37.8℃group,metabolites involved in the tricarboxylic acid cycle in the liver were significantly lower in the 38.8℃group,and metabolites related to lipid oxidation metabolism and fatty acid biosynthesis were significantly lower in the skeletal muscles in the 38.8℃group but significantly higher in the 36.8℃group.These results indicate that incubation temperature variation can lead to developmental plasticity in cold responsive physiological phenotypes.Higher incubation temperature may impair the capacity of birds coping with cold challenge.展开更多
Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conserv...Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conservation.Reeves’ s Pheasant(Syrmaticus reevesii) is a threatened species endemic to China,which is characterized by female-only incubation.However,there is a lack of information regarding the impact of weather conditions on clutch size and incubation behavior in this species.Using satellite tracking,we tracked 27 wild female Reeves’ s Pheasants from 2020 to 2023 in Hubei Province,China.We explored their clutch size and incubation behavior,as well as their responses to ambient temperature and precipitation.Clutch size averaged 7.75 ±1.36,had an association with average ambient temperature and average daily precipitation during the egglaying period,and was potentially linked to female breeding attempts.Throughout the incubation period,females took an average of 0.73 ±0.46 recesses every 24 h,with an average recess duration of 100.80 ±73.37 min and an average nest attendance of 92.98 ±5.27%.They showed a unimodal recess pattern in which nest departures peaked primarily between 13:00 and 16:00.Furthermore,females rarely left nests when daily precipitation was high.Recess duration and nest attendance were influenced by the interaction between daily mean ambient temperature and daily precipitation,as well as day of incubation.Additionally,there was a positive correlation between clutch size and recess duration.These results contribute valuable insights into the lifehistory features of this endangered species.展开更多
Convolution Neural Networks(CNN)can quickly diagnose COVID-19 patients by analyzing computed tomography(CT)images of the lung,thereby effectively preventing the spread of COVID-19.However,the existing CNN-based COVID-...Convolution Neural Networks(CNN)can quickly diagnose COVID-19 patients by analyzing computed tomography(CT)images of the lung,thereby effectively preventing the spread of COVID-19.However,the existing CNN-based COVID-19 diagnosis models do consider the problem that the lung images of COVID-19 patients in the early stage and incubation period are extremely similar to those of the non-COVID-19 population.Which reduces the model’s classification sensitivity,resulting in a higher probability of the model misdiagnosing COVID-19 patients as non-COVID-19 people.To solve the problem,this paper first attempts to apply triplet loss and center loss to the field of COVID-19 image classification,combining softmax loss to design a jointly supervised metric loss function COVID Triplet-Center Loss(COVID-TCL).Triplet loss can increase inter-class discreteness,and center loss can improve intra-class compactness.Therefore,COVID-TCL can help the CNN-based model to extract more discriminative features and strengthen the diagnostic capacity of COVID-19 patients in the early stage and incubation period.Meanwhile,we use the extreme gradient boosting(XGBoost)as a classifier to design a COVID-19 images classification model of CNN-XGBoost architecture,to further improve the CNN-based model’s classification effect and operation efficiency.The experiment shows that the classification accuracy of the model proposed in this paper is 97.41%,and the sensitivity is 97.61%,which is higher than the other 7 reference models.The COVID-TCL can effectively improve the classification sensitivity of the CNN-based model,the CNN-XGBoost architecture can further improve the CNN-based model’s classification effect.展开更多
Growth indicators including weight, body length, wings length, tail length, tarsus, gape, the third toe and head width of 21 nestlings of Great Bustard (Otis tarda) were measured and investigated in Harbin Zoo, Harbin...Growth indicators including weight, body length, wings length, tail length, tarsus, gape, the third toe and head width of 21 nestlings of Great Bustard (Otis tarda) were measured and investigated in Harbin Zoo, Harbin, China during 1999-2002, and methods on successfully fostering nestlings of the bird were also summarized in this article. The results showed: the Great Bustard is a kind of premature bird and its birth weight was 86.31?.56g (N=21); environmental temperature for the neonatal nestlings should be controlled at 36C; the feeding principle having many meals but little food at each for the nestlings should be followed; since six weeks after birth, nestlings of both gender began to show significant difference in body weight, the weight of male was 1.8 times of that of the female after fourteenth week, and by weight and body figure sexual identity could be easily discerned when 3 or 4 months old; There is no significant difference in growth and development of all organs between male and female nestlings and organ growth curves were fit into Logistic equation.展开更多
基金funded by the National Natural Science Foundation of China(32071515 to S.Z.)Graduate Research and Practice Projects of Minzu University of China(SZKY2024035 to R.Z.)。
文摘Embryonic development is a critical period for phenotype formation.Environmental variation during embryonic development can induce changes in postnatal phenotypes of animals.The thyroxine secretion and aerobic metabolic activity of small birds are important phenotypes closely related to their winter survival.In the context of climate change,it is necessary to determine whether temperature variation during incubation in birds leads to developmental plasticity of these cold responsive phenotypes.We incubated Japanese Quail(Coturnix japonica)eggs at 36.8℃,37.8℃,and 38.8℃,and raised the chicks to 35-day old at 22℃with same raising conditions,then all the quails were exposed to gradually temperature dropping environment(from 15℃to 0℃).After cold treatment,serum T3 level,resting metabolic rate,skeletal muscle and liver metabolomes of the birds were measured.The serum T3 levels were significantly lower in the 38.8℃group and significantly higher in the 36.8℃group compared to the 37.8℃group.The metabolic rate in the 38.8℃group was significantly lower compared to the 37.8℃group.Compared with the 37.8℃group,metabolites involved in the tricarboxylic acid cycle in the liver were significantly lower in the 38.8℃group,and metabolites related to lipid oxidation metabolism and fatty acid biosynthesis were significantly lower in the skeletal muscles in the 38.8℃group but significantly higher in the 36.8℃group.These results indicate that incubation temperature variation can lead to developmental plasticity in cold responsive physiological phenotypes.Higher incubation temperature may impair the capacity of birds coping with cold challenge.
基金supported by the National Natural Science Foundation of China (grant number 31872240)。
文摘Weather conditions play a pivotal role in embryo development and parental incubation costs,potentially impacting the clutch size and incubation behavior of birds.Understanding these effects is crucial for bird conservation.Reeves’ s Pheasant(Syrmaticus reevesii) is a threatened species endemic to China,which is characterized by female-only incubation.However,there is a lack of information regarding the impact of weather conditions on clutch size and incubation behavior in this species.Using satellite tracking,we tracked 27 wild female Reeves’ s Pheasants from 2020 to 2023 in Hubei Province,China.We explored their clutch size and incubation behavior,as well as their responses to ambient temperature and precipitation.Clutch size averaged 7.75 ±1.36,had an association with average ambient temperature and average daily precipitation during the egglaying period,and was potentially linked to female breeding attempts.Throughout the incubation period,females took an average of 0.73 ±0.46 recesses every 24 h,with an average recess duration of 100.80 ±73.37 min and an average nest attendance of 92.98 ±5.27%.They showed a unimodal recess pattern in which nest departures peaked primarily between 13:00 and 16:00.Furthermore,females rarely left nests when daily precipitation was high.Recess duration and nest attendance were influenced by the interaction between daily mean ambient temperature and daily precipitation,as well as day of incubation.Additionally,there was a positive correlation between clutch size and recess duration.These results contribute valuable insights into the lifehistory features of this endangered species.
基金This work was supported,in part,by the Natural Science Foundation of Jiangsu Province under Grant Numbers BK20201136,BK20191401in part,by the National Nature Science Foundation of China under Grant Numbers 62272236,61502096,61304205,61773219,61502240in part,by the Public Welfare Fund Project of Zhejiang Province Grant Numbers LGG20E050001.
文摘Convolution Neural Networks(CNN)can quickly diagnose COVID-19 patients by analyzing computed tomography(CT)images of the lung,thereby effectively preventing the spread of COVID-19.However,the existing CNN-based COVID-19 diagnosis models do consider the problem that the lung images of COVID-19 patients in the early stage and incubation period are extremely similar to those of the non-COVID-19 population.Which reduces the model’s classification sensitivity,resulting in a higher probability of the model misdiagnosing COVID-19 patients as non-COVID-19 people.To solve the problem,this paper first attempts to apply triplet loss and center loss to the field of COVID-19 image classification,combining softmax loss to design a jointly supervised metric loss function COVID Triplet-Center Loss(COVID-TCL).Triplet loss can increase inter-class discreteness,and center loss can improve intra-class compactness.Therefore,COVID-TCL can help the CNN-based model to extract more discriminative features and strengthen the diagnostic capacity of COVID-19 patients in the early stage and incubation period.Meanwhile,we use the extreme gradient boosting(XGBoost)as a classifier to design a COVID-19 images classification model of CNN-XGBoost architecture,to further improve the CNN-based model’s classification effect and operation efficiency.The experiment shows that the classification accuracy of the model proposed in this paper is 97.41%,and the sensitivity is 97.61%,which is higher than the other 7 reference models.The COVID-TCL can effectively improve the classification sensitivity of the CNN-based model,the CNN-XGBoost architecture can further improve the CNN-based model’s classification effect.
文摘Growth indicators including weight, body length, wings length, tail length, tarsus, gape, the third toe and head width of 21 nestlings of Great Bustard (Otis tarda) were measured and investigated in Harbin Zoo, Harbin, China during 1999-2002, and methods on successfully fostering nestlings of the bird were also summarized in this article. The results showed: the Great Bustard is a kind of premature bird and its birth weight was 86.31?.56g (N=21); environmental temperature for the neonatal nestlings should be controlled at 36C; the feeding principle having many meals but little food at each for the nestlings should be followed; since six weeks after birth, nestlings of both gender began to show significant difference in body weight, the weight of male was 1.8 times of that of the female after fourteenth week, and by weight and body figure sexual identity could be easily discerned when 3 or 4 months old; There is no significant difference in growth and development of all organs between male and female nestlings and organ growth curves were fit into Logistic equation.
