Zhouherndon6867

One on one surgery with cytoreductive surgical procedure and also hyperthermic intraperitoneal chemo with regard to people using intestines peritoneal metastases.

To control the risks of powder caking and capsule shell embrittlement of Guizhi Fuling Capsules, a predictive model for hygroscopicity of contents in Guizhi Fuling Capsules was built. A total of 90 batches of samples, including raw materials, intermediate powders and capsules, were collected during the manufacturing of Guizhi Fuling Capsules. According to the production sequence, 47 batches were used as the calibration set, and the properties of raw materials and the four intermediate powders were comprehensively characterized by the physical fingerprint. Then, the partial least squares(PLS) model was developed with the content hygroscopicity as the response variable. The variable importance in projection(VIP), variance inflation factor(VIF) and regression coefficients were used to screen out potential critical material attributes(pCMAs). As a result, five pCMAs from 54 physical parameters were screened out. Furthermore, different models were built by different combinations of pCMAs, and their predictive robustness of 43 batches was evaluated on the basis of the validation set. Finally, the tap density(D_c) of wet granules obtained from wet granulation and the angle of repose(α) of raw materials were identified as the critical material attributes(CMAs) affecting the hygroscopicity of the contents of Guizhi Fuling Capsules. The prediction model established with the two CMAs as independent variables had an average relative prediction error of 2.68% for samples in the validation set, indicating a good accuracy of prediction. selleck kinase inhibitor This paper proved the feasibility of predictive modeling toward the control of critical quality attributes of Chinese medicine oral solid dosage(OSD). The combination of the continuous quality improvement, the industrial big data and the process modeling technique paved the way for the intelligent manufacturing of Chinese medicine oral solid preparations.Lonicerae Japonicae Flos and Artemisiae Annuae Herba(LA or Jinqing) alcohol precipitation has various process parameters and complex process mechanism, and is one of the key units for manufacturing Reduning Injection. In order to identify the critical process parameters(CPPs) affecting the weight of the extract produced from the alcohol precipitation process, 259 batches of historical production data from 2017 to 2018 were collected, with a total of 829 318 data points. These data showed characteristics of large data, such as a large data volume, a low value density, and diverse sources. The data cleaning and feature extraction were first performed, and 48 feature variables were selected. The original data points were reduced to 9 936. Then, a combination of Pearson correlation analysis and grey correlation analysis were used to screen out 15 potential critical process parameters(pCPPs). After that, the partial least squares(PLS) was used in prediction of the weight of the extract, proving that the performance of predictive model based on 15 pCMAs is equivalent to that of predictive model based on 48 feature variables. The variable importance in projection(VIP) index was used to identify 9 CPPs, including 2 alcohol precipitation supernatant volume parameters, 4 initial extract weight parameters and 3 added alcohol volume parameters. As a result, the number of data points was 1 863, accounting for 0.28% of the original data. The big data analysis approach from a holistic point of view can effectively increase the value density of the original data. The critical process parameters obtained can help to accurately describe the quality transfer mechanism of the Jinqing alcohol precipitation process.Along with the striding of the Chinese medicine(CM) manufacturing toward the Industry 4.0, some digital factories have accumulated lightweight industrial big data, which become part of the enterprise assets. These digital assets possess the possibility of solving the problems within the CM production system, like the Sigma gap and the poverty of manufacturing knowledge. From the holistic perspective, a three-tiered architecture of CM industrial big data is put forward, and it consists of the data integration layer, the data analysis layer and the application scenarios layer. In data integration layer, sensing of CM critical quality attributes is the key technology for big data collection. In data analysis and mining layer, the self-developed iTCM algorithm library and model library are introduced to facilitate the implementation of the model lifecycle methodologies, including process model development, model validation, model configuration and model maintenance. The CM quality transfer structure is closely related with the connection mode of multiple production units. The system modeling technologies, such as the partition-integration modeling method, the expanding modeling method and path modeling method, are key to mapping the structure of real manufacturing system. It is pointed out that advance modeling approaches that combine the first-principles driven and data driven technologies are promising in the future. At last, real-world applications of CM industrial big data in manufacturing of injections, oral solid dosages, and formula particles are presented. It is shown that the industrial big data can help process diagnosis, quality forming mechanism interpretations, real time release testing method development and intelligent product formulation design. As renewable resources, the CM industrial big data enable the manufacturing knowledge accumulation and product quality improvement, laying the foundation of intelligent manufacturing.OBJECTIVE To present a striking case of new-onset psychosis in a middle-aged woman subsequently diagnosed with behavioral variant frontotemporal dementia (bvFTD). To review the data regarding key red-flag features that may suggest a diagnosis of a neurodegenerative process, and specifically bvFTD, rather than a primary psychotic disorder. To examine the role of genetics, especially mutations of the microtubule-associated protein tau (MAPT) gene, in familial cases of frontotemporal dementia (FTD). selleck kinase inhibitor DATA SOURCES The pertinent literature was searched online (PubMed, Google Scholar) using the following search terms frontotemporal dementia (FTD), Pick's disease, behavioral variant FTD (bvFTD), psychosis, delusions, MAPT, and genetics. No date or language limit was applied. STUDY SELECTION The case report was generated through detailed assessment of clinical notes, imaging studies, and laboratory results. The brain autopsy was carried out and summarized by our neuropathology team. Previously published literature was selected for inclusion in the review section based on relevance to the topic.