RESUMEN
Uyghur medicine is one of the four major ethnic medicines in China and is a component of traditional Chinese medicine. The intrinsic quality of Uyghur medicinal materials will directly affect the clinical efficacy of Uyghur medicinal preparations. However, in recent years, problems such as adulteration of Uyghur medicinal materials and foreign bodies with the same name still exist, so it is necessary to strengthen the quality control of Uyghur medicines to guarantee Uyghur medicinal efficacy. Identifying the components of Uyghur medicines can clarify the types of medicinal materials used, is a crucial step to realizing the quality control of Uyghur medicines, and is also an important step in screening the effective components of Uyghur medicines. Currently, the method of identifying the components of Uyghur medicines relies on manual detection, which has the problems of high toxicity of the unfolding agent, poor stability, high cost, low efficiency, etc. Therefore, this paper proposes a method based on Raman spectroscopy and multi-label deep learning model to construct a model Mix2Com for accurate identification of Uyghur medicine components. The experiments use computer-simulated mixtures as the dataset, introduce the Long Short-Term Memory Model (LSTM) and Attention mechanism to encode the Raman spectral data, use multiple parallel networks for decoding, and ultimately realize the macro parallel prediction of medicine components. The results show that the model is trained to achieve 90.76% accuracy, 99.41% precision, 95.42% recall value and 97.37% F1 score. Compared to the traditional XGBoost model, the method proposed in the experiment improves the accuracy by 49% and the recall value by 18%; compared with the DeepRaman model, the accuracy is improved by 9% and the recall value is improved by 14%. The method proposed in this paper provides a new solution for the accurate identification of Uyghur medicinal components. It helps to improve the quality standard of Uyghur medicinal materials, advance the research on screening of effective chemical components of Uyghur medicines and their action mechanisms, and then promote the modernization and development of Uyghur medicine.
Asunto(s)
Medicina Tradicional de Asia Oriental , Espectrometría Raman , Espectrometría Raman/métodosRESUMEN
OBJECTIVE: To evaluate the validity of psychological care combined with enhanced recovery after surgery (PC+ERAS) management in perioperative nursing care of andrological patients. METHODS: A total of 300 male patients undergoing andrological surgery were included in this study, 150 given PC+ERAS and the other 150 receiving routine nursing care as controls. We evaluated anxiety and depression of all the patients on admission and discharge using Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS), and compared post-operative hospital days, off-bed time, first passage of flatus, Visual Analog Scale (VAS) score and satisfaction with nursing care between the two groups of patients. RESULTS: On discharge, significant improvement was observed in SAS and SDS scores in the PC+ERAS group compared with the baseline, even more significant than in the control group (P < 0.01), but no obvious improvement was seen in the controls (P > 0.05). The patients in the PC+ERAS group also achieved a significantly shorter post-operative hospital stay, earlier post-operative off-bed time and passage of flatus, lower VAS score, and higher satisfaction with nursing care than those in the control group (P < 0.05). CONCLUSIONS: Psychological care combined with ERAS management deserves wide application in the perioperative nursing care of andrological patients, which can significantly improve the patients' anxiety and depression, shorten post-operative hospital stay, reduce VAS score, and increase their satisfaction with nursing care.
Asunto(s)
Recuperación Mejorada Después de la Cirugía , Enfermería Perioperatoria , Procedimientos Quirúrgicos Urológicos Masculinos/enfermería , Procedimientos Quirúrgicos Urológicos Masculinos/psicología , Humanos , Tiempo de Internación , Masculino , Complicaciones Posoperatorias , Periodo PosoperatorioRESUMEN
The potential of low-cost bioenergy recovery from peanut shell was limited for its complex cellulose structure. In order to enhance the total reducing sugar (TRS) yield for bio-H2 production, peanut shell with heat (HT, 50-100 °C) or freezing pretreatment (FT, -80 to 0 °C) under different duration (0.5-12 h) was investigated. For uncovering the enhancement mechanisms, morphological feature and crystalline structure were analyzed by scanning electron microscope (SEM) and X-ray powder diffraction (XRD). The optimal pretreatment of 50 °C for 12 h was obtained with TRS yield increased 73.6%, while the H2 yield of 1.25 ml/mg-TRS was peaked with pretreatment at -80 °C. The SEM and XRD further demonstrated that mechanisms of HT and FT were realized through different ways, which were cracking and collapsing in HT, and delamination and peeling in FT, respectively.