Enzymolytic soybean meal improves growth performance, economic efficiency and organ development associated with cecal fermentation and microbiota in broilers offered low crude protein diets.

The objective of this experiment was to determine the effect of low crude protein (CP) diets containing increasing amounts of enzymolytic soybean meal (ESBM) on growth performance, economic benefit and organ development and the role of cecal fermentation and microbiota in broilers. A total of 360 one-day-old Arbor Acres chicks were randomly allocated into 6 groups with 6 replicates and 10 chicks each. The six dietary treatments consisted of a standard high-CP diet (PC), a low-CP diet (NC), and an NC diet with 0.5, 1.0, 1.5%, or 2.0% ESBM. The experiment lasted for 42 days. Compared to PC, NC showed decreased (p < 0.05) average daily gain (ADG) in broilers from 22 to 42 days and from 1 to 42 days, while increasing levels of ESBM quadratically increased (p < 0.05) ADG from 1 to 42 days. Feed cost and total revenue in the NC were lower (p < 0.05) than that in the PC, while supplementation with ESBM in the NC linearly increased (p < 0.05) net profit and economic efficiency in broilers. There were significant differences (p < 0.05) in the liver, proventriculus and gizzard indices between the PC and NC groups, and supplementation with ESBM linearly increased (p < 0.05) the relative weights of liver, pancreas, proventriculus and gizzard in broilers at 42 days of age. The PC group had a higher cecal acetic acid concentration at 21 days and propionic acid concentration at both 21 and 42 days than the NC group (p < 0.05). Cecal acetic acid and propionic acid concentrations linearly increased (p < 0.05) with increasing levels of ESBM in broilers at 42 days of age. No significant differences in ACE, Chao1, Shannon and Simpson indices were observed among groups (p > 0.05), while the cecal abundances of Bacteroides, Faecalibacterium and Clostridium IV increased (p < 0.05) with the increasing level of ESBM in the low-CP diets. In conclusion, feeding ESBM improved economic efficiency, digestive organ development, cecal fermentation and microbial community composition, and up to 2.0% ESBM addition had no negative effect on the growth performance in broilers fed low CP diets.

Understanding the impact of heatwave on urban heat in greater Sydney: Temporal surface energy budget change with land types.

The impact of heatwaves (HWs) on urban heat island (UHI) is a contentious topic with contradictory research findings. A comprehensive understanding of the response of urban and rural areas to HWs, considering the underlying cause of surface energy budget changes, remains elusive. This study attempts to address this gap by investigating a 2020 HW event in the Greater Sydney Area using the Advanced Weather Research and Forecasting (WRF) model with 250-m high resolution. Findings indicate that the HW intensifies the nighttime surface UHI by approximately 4 °C. An analysis of surface energy budgets reveals that urban areas store more heat during the HW due to receiving more solar radiation and less evapotranspiration compared to rural areas. The maximum heat storage flux in urban during the HW can be around 200 W/m2 higher than that during post-HW. The stored heat is released at nightime, raising the air temperature in the urban areas. Forests and savannas have relatively lower storage heat fluxes due to high transpiration and albedo, and the maximum heat storage flux is only around 50 W/m2 higher than that during post-HW. In contrast, a negative synergistic effect is detected between the 2-m UHI and HW. This may be because other meteorological conditions including wind have substantial impacts on the air temperature pattern. The strong hot and dry winds coming from the west resulted in a higher air temperature in the western urban district, and intra-city disparities are higher. Meanwhile, the western forest area also experiences higher temperatures due to the westward winds. In addition, changes in wind direction alter the temperature distribution in the northern rural region. The findings of the present study may provide some insights into urban heat mitigation during HW.

An optimization for postpartum depression risk assessment and preventive intervention strategy based machine learning approaches.

BACKGROUND: Postpartum depression (PPD) is one of the most common psychiatric disorders for women after delivery. The establishment of an effective PPD prediction model helps to distinguish high-risk groups, and verifying whether such high-risk groups can benefit from drug intervention is very important for clinical guidance. METHODS: We collected data of parturients that underwent a cesarean delivery. The Control group was divided into a training cohort and a testing cohort. Six different ML models were constructed and we compared their prediction performance in the testing cohort. For model interpretation, we introduced SHapley Additive exPlanations (SHAP). Then, training cohort, ketamine group and dexmedetomidine (DEX) group were classified as high or low risk for PPD by the model. A 1:1 propensity score matching (PSM) was performed to compare the incidence of PPD between two groups in different risk cohorts. RESULTS: Extreme gradient enhancement (XGB) had the best recognition effect, with an area under the receiver operating characteristic curve (AUROC) of 0.789 (95 % CI 0.742-0.836) in the training cohort and 0.744 (95 % CI 0.655-0.823) in the testing cohort, respectively. A threshold of 21.5 % PPD risk probability was determined. After PSM, the results showed that the incidence of PPD in the two intervention groups was significantly different from the control group in the high-risk cohort (P < 0.001) but not in the low-risk cohort (P > 0.001). CONCLUSION: Our study demonstrated that the XGB algorithm provided a more accurate in prediction of PPD risk, and it was beneficial to receive early intervention for the high-risk groups distinguished by the model.

The Impact of the "Belt and Road" Initiative on Accounting Conservatism of Energy-Intensive Enterprises under the Low-Carbon Background.

In recent years, the "Belt and Road" Initiative (BRI) has paid more and more attention to practicing the concept of green development. The concept of green development in the BRI will help promote the active response to climate change in the regions along the route and maintain global ecological security and is of great significance to the green transformation and development of energy-intensive enterprises. Using company-level data from China over the 2011-2020 period, we provide a comprehensive analysis of the impact of the BRI on energy-intensive enterprise accounting conservatism. We find that BRI has decreased the energy-intensive enterprise accounting conservatism, and this result continues to hold after a series of robustness tests. We also examine the effect of the RBI on accounting conservatism across company types and ages and find that the BRI is beneficial to energy-intensive state-owned enterprises (SOEs) and young companies. Furthermore, analysis reveals that BRI changes the accounting conservatism of energy-intensive enterprises mainly through debt financing, tax burden, and legal environment channels.

Establishment of Economic Forecasting Model of High-tech Industry Based on Genetic Optimization Neural Network.

Scientific and accurate prediction of high-tech industries is of great practical significance for government departments to grasp the future economic operation and formulate development strategies. In this paper, aiming at some shortcomings of neural network (NN) applied in economic forecasting, GANN was introduced to construct the economic forecasting model of high-tech industry. Genetic algorithm (GA) has simple calculation and strong robustness and can generally ensure convergence to the global optimum, which effectively overcomes the shortcomings of NN using gradient descent method. In order to verify the feasibility of the economic forecasting model in this paper, the comparative experiments of different models are carried out in this paper. Experimental results show that the proposed algorithm has faster convergence speed and greater generalization ability, and the average error rate is reduced to about 1%. The prediction accuracy of this model reached 95.14%, which was about 11.93% higher than the previous model. Applying the economic forecasting model in this paper to the economic forecasting of high-tech industries can provide the means and reference value for the government to formulate regional future economic development plans, forecast, and control the economic growth and development direction.

The development and application of a prediction model for postpartum depression: optimizing risk assessment and prevention in the clinic.

BACKGROUND: Preventive intervention can significantly reduce the human and economic costs of postpartum depression (PPD) compared with treatment post-diagnosis. However, identifying women with a high PPD risk and making a judgement as to the benefits of preventive intervention is a major challenge. METHODS: This is a retrospective study of parturients that underwent a cesarean delivery. Control group was used as development cohort and validation cohort to construct the risk prediction model of PPD and determine a risk threshold. Ketamine group and development cohort were used to verify the risk classification of parturients by evaluating whether the incidence of PPD decreased significantly after ketamine treatment in high-risk for PPD population. RESULTS: The AUC for the development cohort and validation cohort of the PPD prediction model were 0.751 (95%CI:0.700-0.802) and 0.748 (95%CI:0.680-0.816), respectively. A threshold of 19% PPD risk probability was determined, with a specificity and sensitivity in the validation cohort are 0.766 and 0.604, respectively. After matching the high-risk group and the low-risk group by propensity score, the results demonstrated that PPD incidence significantly reduced in the high-risk group following ketamine, versus non-ketamine, intervention (p < 0.01). In contrast, intervention in the low-risk group showed no significant difference in PPD outcomes (p > 0.01). LIMITATION: Randomized trials are needed to further verify the feasibility of the model and the thresholds proposed. CONCLUSION: This prediction model developed in this study shows utility in predicting PPD risk. Ketamine intervention significantly lowers PPD incidence in parturients with a risk classification threshold greater than 19%.

A fuzzy DRBFNN-based information security risk assessment method in improving the efficiency of urban development.

The rapid development of urban informatization is an important way for cities to achieve a higher pattern, but the accompanying information security problem become a major challenge restricting the efficiency of urban development. Therefore, effective identification and assessment of information security risks has become a key factor to improve the efficiency of urban development. In this paper, an information security risk assessment method based on fuzzy theory and neural network technology is proposed to help identify and solve the information security problem in the development of urban informatization. Combined with the theory of information ecology, this method establishes an improved fuzzy neural network model from four aspects by using fuzzy theory, neural network model and DEMATEL method, and then constructs the information security risk assessment system of smart city. According to this method, this paper analyzed 25 smart cities in China, and provided suggestions and guidance for information security control in the process of urban informatization construction.

Automatic Assessment of Biometric Parameters in Optic Nerve Head Area by "Zhongshan ONH Calculator (ZOC)".

PURPOSE: To test the repeatability and reproducibility of the Zhongshan ONH Calculator (ZOC) software in terms of selected optic nerve head (ONH) parameters commonly used in clinical research of glaucoma. MATERIALS AND METHODS: Forty-two horizontal single-line scans were selected to test the repeatability and reproducibility of the ZOC software. Clinically relevant 2D parameters of the ONH area were selected to test repeatability of ZOC, including length of BMO, minimum rim thickness on both sides (RIML and RIMR), optic cup depth (OCD), and depth of the anterior surface of the LC (ALCD). RESULTS: Intraobserver test showed higher the intra-class correlation coefficient (ICC) of BMO ((0.991 vs. 0.777), RIML (0.988 vs. 0.890), RIMR (0.972 vs. 0.846), OCD (0.997 vs. 0.992), and ALCD (0.993 vs. 0.949) by single researcher using ZOC software than manual measurement. BA analysis showed acceptable agreement between automatic and manual measurements. SDs and limits of agreement (95% CI) of BMO, RIML, RIMR, OCD, and ALCD were 0.05 (-0.13, 0.07), 0.03 (-0.05, 0.05), 0.03 (-0.06, 0.07), 0.015 (-0.035, 0.024), and 0.04 (-0.07, 0.08), respectively. CONCLUSION: This study presented the design and development of software for the automatic measurement of OCT images of ONH area with good reproducibility. In the future, with advances of OCTs and improvements to the resolution of the LC, ZOC will become a powerful tool in glaucoma research.

A simple and cost-effective assay for measuring anti-drug antibody in human patients treated with Adalimumab.

It has been reported that 90% of the anti-drug antibody (ADA) to Adalimumab in human patients bound to the TNF-binding area, resulted in the annual loss of responses to Adalimumab up to 24%. It is of urgency to develop a cost-effective and easy-to-use ADA diagnostic kit for diagnosis of potential drug-resistance in patients treated with Adalimumab in clinic hospitals to avoid the tremendous economic and human costs to patients and health-care providers. In this study, we reported the generations of mouse monoclonal and monkey polyclonal antibodies against Adalimumab as assay standards and positive quality controls respectively. A Bridging ELISA assay was successfully developed with a limit of detection (LOD) between 22-80ng/ml. The preliminary validation of assay was carried out first with 50 normal human sera, further validated by screening the ADA in 192 serum samples from monkeys treated with or without Adalimumab. Our data showed that the Bridging ELISA kit is very sensitive, highly specific and ready for study in human clinic trials.

The role of the quality assessment in the determination of overall biosimilarity: a simulated case study exercise.

A determination of biosimilarity is based on a thorough characterization and comparison of the quality profiles of a similar biotherapeutic product and its reference biotherapeutic product. Although the general principles on the role of the quality assessment in a biosimilar evaluation are widely understood and agreed, detailed discussions have not been published yet. We try to bridge this gap by presenting a case study exercise based on fictional but realistic data to highlight key principles of an evaluation to determine the degree of similarity at the quality level. The case study comprises three examples for biosimilar monoclonal antibody candidates. The first describes a highly similar quality profile whereas the second and third show greater differences to the reference biotherapeutic product. The aim is to discuss whether the presented examples can be qualified as similar and which additional studies may be helpful in enabling a final assessment. The case study exercise was performed at the WHO implementation workshop for the WHO guidelines on quality assessment of similar biotherapeutic products held in Xiamen, China, in May 2012. The goal was to illustrate the interpretation of the comparative results at the quality level, the role of the quality assessment in the entire biosimilarity exercise and its influence on the clinical evaluation. This paper reflects the outcome of the exercise and discussion from Xiamen.

The biopharmaceutical industry in China: history and future perspectives.

Biopharmaceuticals reflect the rapid progress achieved in modern biomedical research. This area has also become one of the main criteria for assessing the development level of biotechnology for a particular country. Although it has been only three decades since the first biopharmaceutical, recombinant human insulin, was licensed by the US Food and Drug Administration, the biopharmaceutical industry has become the fastest growing, most dynamic and technology-intensive sector in the biomedical field. Since the licensing of recombinant human interferon α1b in 1989, the biopharmaceutical industry in China has gone through initial developments and gradually entered a period of rapid growth. This paper provides an overview of the status and development trends of biopharmaceuticals in China, and compares them with those observed in developed countries.