Pricing strategy research in the dual-channel pharmaceutical supply chain considering service.

In the context of developing a new era, the pharmaceutical supply chain market has gradually transformed from a seller's market to a buyer's market. The closer the consumers are, the greater the market pricing power, so the pharmaceutical market power of manufacturers and retailers has also changed. This study considers the effect of service on the pricing strategy of the pharmaceutical platform supply chain. The study aimed to coordinate optimization, and the coordination strategy of the pharmaceutical platform supply chain of complementary products is discussed mainly by researching the price and service factors. Various situations are studied by hypothesis and model solving. This study uses Stackelberg game decision-making. Manufacturers are at the forefront of platform supply chain decisions. The research found that the price was lower under centralized decision-making than under decentralized decision-making. Coordination between price and service levels needs attention in the pharmaceutical platform supply chain of complementary products, and the service level should be controlled within a certain range. Only by improving the service level can enterprises maximize profits, providing a theoretical basis for pharmaceutical supply chain pricing strategy research. Supply chain members must strive to improve service levels to improve medical supply consumers' (patients) psychological satisfaction level. Service levels do not fully mitigate channel conflict. Therefore, pharmaceutical complements have become a way to alleviate the conflicts in the pharmaceutical platform supply chain.

Progress in the Clinical Assessment and Treatment of Myocardial Depression in Critically Ill Patient with Sepsis.

Myocardial inhibition is the main cause of death in patients with sepsis.In recent years, methodological differences in the diagnosis, assessment, and treatment of septic myocardial depression have been observed, and how to objectively and accurately evaluate the degree of myocardial depression and the timing of treatment strategies have generally been the focus of this area of research. Based on the relevant research at home and abroad, the current review summarizes the clinical characteristics, methodological diagnosis, and symptomatic treatment of septic myocardial depression. The aim of doing so is to provide a reference for the early identification and treatment of patients with sepsis and myocardial depression.

The influence of machine learning-based knowledge management model on enterprise organizational capability innovation and industrial development.

The aims are to explore the construction of the knowledge management model for engineering cost consulting enterprises, and to expand the application of data mining techniques and machine learning methods in constructing knowledge management model. Through a questionnaire survey, the construction of the knowledge management model of construction-related enterprises and engineering cost consulting enterprises is discussed. First, through the analysis and discussion of ontology-based data mining (OBDM) algorithm and association analysis (Apriori) algorithm, a data mining algorithm (ML-AR algorithm) on account of ontology-based multilayer association and machine learning is proposed. The performance of the various algorithms is compared and analyzed. Second, based on the knowledge management level, analysis and statistics are conducted on the levels of knowledge acquisition, sharing, storage, and innovation. Finally, according to the foregoing, the knowledge management model based on engineering cost consulting enterprises is built and analyzed. The results show that the reliability coefficient of this questionnaire is above 0.8, and the average extracted value is above 0.7, verifying excellent reliability and validity. The efficiency of the ML-AR algorithm at both the number of transactions and the support level is better than the other two algorithms, which is expected to be applied to the enterprise knowledge management model. There is a positive correlation between each level of knowledge management; among them, the positive correlation between knowledge acquisition and knowledge sharing is the strongest. The enterprise knowledge management model has a positive impact on promoting organizational innovation capability and industrial development. The research work provides a direction for the development of enterprise knowledge management and the improvement of innovation ability.

Assessment of regional greenhouse gas emission from beef cattle production: A case study of Saskatchewan in Canada.

The beef cattle production has been considered as one of the largest sources of greenhouse gases (GHGs) emission. A large amount of GHGs including N2O and CH4 from enteric fermentation and manure are discharged to atmosphere during beef-production process. In addition, a substantial amount of GHGs is also emitted from many other related processes such as feed production, transportation, and energy consumption. In this study, an emission assessment model was developed to quantify the amount of regional GHGs produced from the beef cattle production process. A case study was conducted based on the beef production in Saskatchewan, Canada. The results demonstrated that the GHG emissions from the annual marketed beef cattle in Saskatchewan in 2014 were 8.52 × 109 kg CO2-eq in total and the cattle-source GHGs (enteric CH4, manure CH4, and manure N2O emission) accounted for more than 90% of the total emission. Sensitivity analysis showed that the most critical factors influencing the GHG emission included feedlot manure handling system, cattle diet, feed additives, maximum methane producing capacity (Bo), and climate (temperature, precipitation, and potential evapotranspiration). The potential impacts of climate change on GHG emission from beef cattle production in Saskatchewan were also investigated. An overall decrease in the GHG emission can be observed due to the climate change, which are 3.67%, 4.96%, and 6.63% for 2020-2039, 2040-2059, and 2060-2099, respectively.

A progressive compression model of thoracic spinal cord injury in mice: function assessment and pathological changes in spinal cord.

Non-traumatic injury accounts for approximately half of clinical spinal cord injury, including chronic spinal cord compression. However, previous rodent spinal cord compression models are mainly designed for rats, few are available for mice. Our aim is to develop a thoracic progressive compression mice model of spinal cord injury. In this study, adult wild-type C57BL/6 mice were divided into two groups: in the surgery group, a screw was inserted at T9 lamina to compress the spinal cord, and the compression was increased by turning it further into the canal (0.2 mm) post-surgery every 2 weeks up to 8 weeks. In the control group, a hole was drilled into the lamina without inserting a screw. The results showed that Basso Mouse Scale scores were lower and gait worsened. In addition, the degree of hindlimb dysfunction in mice was consistent with the degree of spinal cord compression. The number of motor neurons in the anterior horn of the spinal cord was reduced in all groups of mice, whereas astrocytes and microglia were gradually activated and proliferated. In conclusion, this progressive compression of thoracic spinal cord injury in mice is a preferable model for chronic progressive spinal cord compression injury.

The Growth-Promoting Effect of Dietary Nucleotides in Fish Is Associated with an Intestinal Microbiota-Mediated Reduction in Energy Expenditure.

Background: Nucleotides have been used as functional nutrients to improve the growth and health of animals, including fish. The mechanism involved in the growth-promotion effect of nucleotides is still unclear.Objective: We investigated the bioenergetic mechanism underlying the growth-promotion effect of nucleotides in zebrafish and the associated roles played by the intestinal microbiota.Methods: Larval zebrafish were fed a control or a 0.1% mixed nucleotides-supplemented diet for 2 wk. Standard metabolic rate, the minimal rate of energy expenditure by animals at rest, was evaluated by oxygen consumption with the use of a respirometer. The expressions of fasting-induced adipose factor (Fiaf), inflammatory cytokines, and genes involved in fatty acid (FA) oxidation were tested by quantitative reverse transcriptase-polymerase chain reaction. The intestinal microbiota from the nucleotide-fed fish (NT fish) or control fish was transferred to 3-d postfertilization germ-free zebrafish in which oxygen consumption and expression of cytokines and fiaf were evaluated.Results: Compared with controls, nucleotide supplementation at 0.1% increased the weight and energy gains of zebrafish by 10% and 25%, respectively (P < 0.01). Standard metabolic rate was 28% lower in NT fish than in controls (P < 0.001). Nucleotide supplementation downregulated the inflammatory tone in the head kidney of the fish. Moreover, NT fish had a 51% lower intestinal expression of fiaf than did controls (P < 0.05), which was consistent with decreased expression of key genes involved in FA oxidation [carnitine:palmitoyl transferase 1a (cpt1a) and medium-chain acyl coenzyme A dehydrogenase (mcad)] in liver and muscle. Germ-free zebrafish colonized with microbiota from NT fish had a 25% lower standard metabolic rate than did those colonized by control microbiota (P < 0.01), whereas direct nucleotide feeding of germ-free zebrafish did not affect standard metabolic rate relative to germ-free controls that were not fed nucleotides. Furthermore, germ-free zebrafish colonized with nucleotide microbiota exhibited downregulated inflammatory tone and 33% lower fiaf expression compared with their control microbiota-colonized counterparts.Conclusions: The growth-promoting effect of dietary nucleotides in zebrafish involves 2 intestinal microbiota-mediated mechanisms that result in reduced standard metabolic rate: 1) lower inflammatory tone and 2) reduced FA oxidation associated with increased microbial suppression of intestinal fiaf.

Structure-based virtual screening for drug discovery: a problem-centric review.

Structure-based virtual screening (SBVS) has been widely applied in early-stage drug discovery. From a problem-centric perspective, we reviewed the recent advances and applications in SBVS with a special focus on docking-based virtual screening. We emphasized the researchers' practical efforts in real projects by understanding the ligand-target binding interactions as a premise. We also highlighted the recent progress in developing target-biased scoring functions by optimizing current generic scoring functions toward certain target classes, as well as in developing novel ones by means of machine learning techniques.

Confidence interval of the difference between two proportions with overdispersion.

In confidence interval estimation of the difference between two proportions with overdispersion due to positive correlations, the usual asymptotic normality-based method generally has lower coverage rates than desired, especially when sample size is moderate. Applying the concept of effective sample size to existing methods for independent data, we propose three new asymptotic normality-based methods. It is demonstrated through an extensive Monte Carlo study that the proposed methods generally perform better than the usual method. The proposed methods are illustrated in the application to a motivating data example.