Search

Drug testing has many test elements. It aims to prevent unqualified drugs from entering the market and ensure drug safety. The existing artificial intelligence (AI) online monitoring system identifies active ingredients in the process of use. Owing to their openness, data are easy to be lost, failing to meet user needs and inducing a specific impact on the use of the monitoring system. With the continuous development of computer and measurement technologies, various biochemical data are increasing at an unprecedented speed, and numerous databases are emerging. Extracting patterns from considerable known data and experimental facts is an essential task for a wide range of biological and chemical workers. Pattern recognition is one of the essential technologies for data mining. It is widely used in industry, agriculture, national defense, biomedicine, meteorology, astronomy, and other fields. To improve the effect of the online drug ingredient recognition system, this study used AI to design an online drug ingredient recognition-embedded monitoring system and applied AI to the teaching field to improve teaching efficiency. First, this study constructed the framework of the AI online drug ingredient recognition-embedded monitoring system and introduced the process of online drug ingredient recognition. Then, it introduced the pattern recognition method, constructed the pattern recognition system, and presented the pattern recognition algorithm and the algorithm evaluation index. Afterward, it used pattern recognition to conduct a qualitative analysis of the infrared spectrum of drug components and introduced the overall process of the qualitative analysis. In addition, this study employed AI to implement changes to the embedded system instruction in colleges and universities, summarizing the current issues. The impact of drug component recognition and the educational impact of embedded systems were investigated in the experimental portion. The experimental findings demonstrated the excellent accuracy, sensitivity, specificity, and Matthew correlation coefficient of the online drug component recognition-integrated monitoring system in this work. Compared with that of other systems, its average drug component recognition accuracy was above 0.85. Students in five majors reported high levels of satisfaction with the embedded system teaching, which is better for delivering college instruction.

With the continuous development of the pharmaceutical industry, people have always paid attention to the safety and effectiveness of drugs, including innovative drugs and generic drugs. For pharmaceutical companies as manufacturers, drug development is a very lengthy process that requires high costs, millions of man-hours, thousands of trials, and the mobilization of hundreds of researchers. Therefore, efforts need to be made to develop drugs with high safety and effectiveness. Drug research and development plays an important role today. Based on this, this article applied computer molecular simulation embedded technology and artificial intelligence technology to drug research and development. First, the problems faced in the research and development of anti-inflammatory disease-dependent tumor drugs were introduced, and then the applications of computer molecular simulation embedded technology and artificial intelligence technology in drug research and development were analyzed. Subsequently, the application of artificial intelligence in drug research and development teaching was analyzed, and a teaching system based on computer molecular simulation embedded technology and artificial intelligence was designed. Finally, the application effects of computer molecular simulation embedded technology and artificial intelligence technology were analyzed, and a feasible conclusion was drawn. The use of computer molecular simulation embedded technology and artificial intelligence technology can greatly improve the efficiency of drug research and development, and the research and development safety of imatinib mesylate has been improved by 7%. On the other hand, it can improve students’ learning interest and stimulate their learning interest, and students’ drug research and development capabilities have been improved. Drug research and development for inflammatory-dependent tumors has good application prospects.

Essential tremor (ET) and Parkinson's disease (PD) are two common movement disorders. A large number of clinical evidence found that a part of patients with early diagnosis of ET could evolve into PD. These patients are diagnosed with essential tremor⁃Parkinson's disease (ET⁃PD). However, there is a lack of diagnostic criteria for ET⁃PD, and the overlap of clinical symptoms of ET and PD makes the identification of ET⁃PD challenging. Here, with an aim to improve the levels of clinical diagnosis and treatment, we summarize the research progress of ET⁃PD in epidemiology, clinical characteristics, pathology and pathophysiology, electrophysiological characteristics, neuroimaging characteristics, genetics and treatment in order to improve the level of clinical diagnosis and treatment.

Objective To investigate maternal and neonatal outcomes after different intrapartum interventions for vaginal birth after cesarean section (VBAC) in mainland China. Methods A retrospective study was performed on 143 VBAC cases from Beijing Obstetrics and Gynecology Hospital between January 2015 and November 2016. These cases were divided into two groups on the basis of different intrapartum interventions. Maternal and neonatal outcomes were compared. Results The durations of the first stage and total labor after oxytocin were significantly longer than those before oxytocin use. The proportion of operative vaginal delivery with oxytocin was significantly higher than that without oxytocin (43.9% vs. 11.8%). The times of the first stage, second stage, and total labor with analgesia were significantly longer than those without analgesia (548.4±198.1 vs. 341.8±233.0 minutes, 52.0±38.9 vs. 36.0± 29.1 minutes, and 606.3±212.1 vs. 387.3±233.0 minutes, respectively). Postpartum hemorrhage and operative vaginal delivery occurred significantly more frequently in women with epidural analgesia than in those without epidural analgesia (29.7% vs. 12.3 and 35.1% vs. 16.0%, respectively). Conclusions Induction can increase the rate of operative vaginal delivery in VBAC. Oxytocin and epidural analgesia may increase the risk of operative vaginal delivery, and may be associated with a prolonged duration of labor.

Background: In the mainland of China, the trial of labor after cesarean section is still a relatively new technique. In this study, we aimed to investigate the effects of labor onset, oxytocin use, and epidural anesthesia on maternal and neonatal outcomes for vaginal birth after cesarean section (VBAC) in a tertiary hospital in China. Methods: This was a retrospective study carried out on 212 VBAC cases between January 2015 and June 2017 in Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Relevant data were acquired on a form, including maternal age, gravidity and parity, body mass index before pregnancy, weight gain during pregnancy, type of labor onset, gestational age, the use of oxytocin and epidural anesthesia, birth mode, the duration of labor, and neonatal weight. The factors affecting maternal and neonatal outcomes for cases involving VBAC, especially with regards to postpartum hemorrhage (PPH) and fetal distress, were evaluated by univariate analysis and multivariable logistic regression. Results: Data showed that 36 women (17.0%) had postpartum hemorrhage (PPH) and 51 cases (24.1%) featured fetal distress. Normal delivery took place for 163 infants (76.9%) while 49 infants (23.1%) underwent operative vaginal deliveries with forceps. There were 178 cases (84.0%) of spontaneous labor and 34 cases (16.0%) required induction. Oxytocin was used in 54 cases (25.5%) to strengthen uterine contraction, and 65 cases (30.7%) received epidural anesthesia. The rate of normal delivery in cases involving PPH was significantly lower than those without PPH (61.1% vs. 80.1%; χ2 = 6.07, P = 0.01). Multivariate logistic analysis showed that the intrapartum administration of oxytocin (odds ratio [OR] = 2.47; 95% confidence interval [CI] = 1.07–5.74; P = 0.04) and birth mode (OR = 0.40; 95% CI = 0.18–0.87; P = 0.02) was significantly associated with PPH in VBAC cases. Operative vaginal delivery occurred more frequently in the group with fetal distress than the group without (49.0% vs. 14.9%, χ2 = 25.36, P = 0.00). Multivariate logistic analysis also revealed that the duration of total labor (OR = 1.01; 95% CI = 1.00–1.03; P = 0.04) and the gestational week of delivery (OR = 1.08; 95% CI = 1.05–1.11; P = 0.00) were significantly associated with fetal distress in VBAC. Conclusions: The administration of oxytocin during labor and birth was identified as a protective factor for PPH in VBAC while birth mode was identified as a risk factor. Finally, the duration of total labor and the gestational week of delivery were identified as risk factors for fetal distress in cases of VBAC. This information might help obstetricians provide appropriate interventions during labor and birth for VBAC.

The high- and low-pressure switching of the axial piston pump is realized by the structure of the valve plate, and the buffer-groove structure on the valve plate is very important to reduce the pressure shock and flow fluctuation. In order to optimize the structural parameters of the buffer tank of the piston pump, the influence of the triangular-groove structure on the outlet pressure–flow characteristics was analyzed, and the low-pulsation buffer-groove structure was designed. First, the relationship between the structure of the triangular buffer tank and the output pressure and flow characteristics of the pump was analyzed theoretically. The Computational Fluid Dynamics (CFD) method was used to calculate the pressure and flow characteristics of the whole pump flow field of the triangular-groove structure, and the influence of the buffer-groove structure parameters on the outlet flow pulsation characteristics was studied. The multi-objective optimization algorithm was used to optimize the structure parameters of the buffer tank, and the optimized structure significantly reduced the outlet pressure–flow pulsation of the piston pump. The results show that, after optimization, the width angle of the front and rear triangular groove is 82.3°, the depth angle is 12.7°, the optimized pressure pulsation rate is 0.3%, and the optimized flow pulsation rate is 13.7%. [ABSTRACT FROM AUTHOR]

There's a paucity of robust normal fractional limb and organ volume standards from a large and diverse ethnic population. The Fetal 3D Study was designed to develop research and clinical applications for fetal soft tissue and organ volume assessment. The NICHD Fetal Growth Studies (2009–2013) collected 2D and 3D fetal volumes. In the Fetal 3D Study (2015–2019), sonographers performed longitudinal 2D and 3D measurements for specific fetal anatomical structures in research ultrasounds of singletons and dichorionic twins. The primary aim was to establish standards for fetal body composition and organ volumes, overall and by maternal race/ethnicity, and determine whether these standards vary for twins versus singletons. We describe the study design, methods, and details about reviewer training. Basic characteristics of this cohort, with their corresponding distributions of fetal 3D measurements by anatomical structure, are summarized. This investigation is responsive to critical data gaps in understanding serial changes in fetal subcutaneous fat, lean body mass, and organ volume in association with pregnancy complications. In the future, this cohort can answer critical questions regarding the potential influence of maternal characteristics, lifestyle factors, nutrition, and biomarker and chemical data on longitudinal measures of fetal subcutaneous fat, lean body mass, and organ volumes. [ABSTRACT FROM AUTHOR]