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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]

This analysis systematically reviewed the efficacy of evidence‐based care on diabetic foot ulcers. A computerised literature search was conducted for randomised controlled studies (RCTs) of evidence‐based care interventions for the treatment of diabetic foot ulcers using the PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), China Biomedical Literature Database (CBM) and Wanfang databases from the date of inception of each database to June 2023. The articles were independently screened, data were extracted by two researchers, and the quality of each study was assessed using the Cochrane bias assessment tool. Meta‐analysis of the data was performed using RevMan 5.4 software. Twenty‐five RCTs with a total of 2272 patients were included. Meta‐analysis showed that, compared with other care methods, evidence‐based care significantly improved the treatment efficacy of diabetic foot ulcers (odds ratio: 3.91, 95% confidence interval [CI]: 2.76 to 5.53, p < 0.001) and significantly reduced their fasting plasma glucose (mean difference [MD]: −1.10, 95% CI: −1.24 to −0.96, p < 0.001), 2‐h postprandial glucose (2hPG) (MD: −1.69, 95% CI: −2.07 to −1.31, p < 0.001) and glycated haemoglobin (HbA1c) (MD: −0.71, 95% CI: −0.94 to −0.48, p < 0.001). Evidence‐based care intervention is effective at reducing FPG, 2hPG and HbA1c levels and improving treatment efficacy in patients with diabetic foot ulcers. [ABSTRACT FROM AUTHOR]

Creutzfeldt-Jakob disease (CJD) is a group of clinically rare neurodegenerative diseases caused by misfolding of prion proteins, and is the most common type of human prion diseases. Since the prion characteristics were recognized in the 1970s, the diagnostic detection technology has made great progress, especially the real-time quaking-induced conversion (RT-QuIC). This paper describes the pathogenesis of CJD, the mechanism of action of RT-QuIC and its application in the diagnosis of CJD in order to promote the application and development of RT-QuIC technology in the field of CJD. [ABSTRACT FROM AUTHOR]

Objective To report clinical phenotype and gene mutation characteristics of one case of early-onset Alzheimer's disease (EOAD) associated with PSEN2 V214L mutation and conduct a pedigree analysis. Methods and Results A 63-year-old male proband with no family history of dementia, onset at 58 years old, had memory loss as the first manifestation and progressive aggravation of symptoms. Neuropsychological tests showed a score of 1 on Mini-Mental State Examination (MMSE), 0 on Montreal Cognitive Assessment (MoCA), 71 on Activities of Daily Living Scale (ADL), and 3 on Hachinski Ischemic Score (HIS). Head MRI revealed extensive cortical atrophy, with prominent atrophy of bilateral hippocampal, multiple hyperintensity in deep white matter (Fazekas grade 2). Exons of high-throughput sequencing of dementia-related genes showed that both the proband and his sister had heterozygous missense mutations in exon 8 of PSEN2 gene c.640G > T (p.V214L) and heterozygous splicing mutations in exon 28 of SORL1 gene c.3815-4A > C. The proband was finally diagnosed with EOAD associated with PSEN2 V214L mutation, and the proband's sister was considered as an absolute risk group for Alzheimer's disease (AD). Conclusions The PSEN2 V214L mutation probably causes EOAD. Further investigations should be conducted to evaluate the effects on the production of amyloid β-protein 40 and 42 (Aβ40 and Aβ42), then verify its pathogenicity. [ABSTRACT FROM AUTHOR]