OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

Objective To explore the value of pulmonary perfusion SPECT/CT imaging for diagnosing pulmonary embolism(PE)and combining with clinical and laboratory indicators for predicting prognosis.Methods Totally 260 patients with suspected PE were retrospectively collected,and PE was clinically confirmed in 237 cases.The diagnostic efficacy of pulmonary perfusion SPECT/CT imaging and CT pulmonary angiography(CTPA)were compared.Among 237 patients with clinically confirmed PE,160 cases were initially diagnosed who underwent standard anticoagulant therapy and were regularly followed up to 3 months after discharge,and their prognosis were analyzed.Logistic regression was used to analyze clinical data,laboratory indicators and pulmonary perfusion defect scores based on pulmonary perfusion SPECT/CT imaging to screen the independent predictors of poor prognosis of PE of the above patients,and a prediction model was then constructed.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate the predictive efficacy of this model for predicting prognosis of PE.Results The positive rate of PE diagnosed with pulmonary perfusion SPECT/CT was higher than that with CTPA(66.54％[173/260]vs.59.62％[155/260],x2=4.765,P=0.038).Among 160 cases of clinically confirmed PE,poor prognosis was observed in 51 cases,while good prognosis was noticed in 109 cases.Patients' age,blood urea nitrogen,serum creatinine,uric acid,D-dimer level and pulmonary perfusion defect score were all independent predictors for poor prognosis of PE(all P＜0.05),and AUC of the established combined model was 0.731.Conclusion Pulmonary perfusion SPECT/CT imaging could be used for diagnosing PE,and combining with clinical and laboratory indicators could effectively predict prognosis of PE.

Objective To observe changes of dynamic functional connectivity(dFC)of brain networks in different stages of Parkinson disease(PD).Methods Totally 52 early-stage PD patients(early PD group),36 late-stage PD patients(late PD group)and 38 healthy controls(HC group)were prospectively enrolled,and resting-state functional MRI were performed.The sliding window,independent component analysis and k-means clustering were used to extract dFC intensity and temporal properties,including fractional windows,dwell time and transition frequency.Results Network connectivity patterns within and between visual network(VIS),sensorimotor network(SMN),default mode network(DMN),cerebellar network(CB)and cognitive executive network(CEN)were altered in PD patients.Four dFC states were identified,in which connections between components in states Ⅰ and Ⅱ were compact,while in states Ⅲ and Ⅳ were sparse.The fractional window and dwell time of late PD group,early PD group and HC group successively increased under state Ⅱ,but successively decreased under state Ⅲ(all P＜0.05).Under state Ⅰ and Ⅳ,no significant difference of fractional window nor dwell time was found between early PD group and late PD group(both P＞0.05),and the above indexes under state Ⅰ were both lower than those in HC group(all P＜0.05),the fraction window under state Ⅳ was higher than that in HC group(both P＜0.05).Conclusion The temporal properties of dFC in PD patients were altered,characterized by increased tendency toward segregated states.Furthermore,fractional windows and dwell time were associated with PD disease stages,suggesting that dFC parameters might serve as novel biomarkers for assessing clinical progression of PD.

Objective To study the death status of pancreatic cancer among residents in Xuhui district, Shanghai, from 1992 to 2021, and analyze its trends of change, so as to provide evidence for the prevention and treatment of pancreatic cancer. Methods Based on the database of Shanghai death registration system from 1992 to 2021, the crude mortality rate, standardized mortality rate, age-specific mortality rate and other indicators of pancreatic cancer among registered residents in Xuhui district were calculated. The Joinpoint software was used to analyze the trends of average annual percent change (AAPC) of pancreatic cancer mortality rate, and the age-period-cohort model was used to analyze the age effect, period effect and birth cohort effect pairs significant changes in pancreatic cancer mortality. Results In 2021, the mortality rate of pancreatic cancer in Xuhui district, Shanghai, ranked fourth among malignant tumors, and the winning rate and world standard rate of the whole population, males and females were 8.34/100 000 (8.81/100 000, 7.98/100 000) and 7.28/100 000 (7.69/100 000, 6.96/100 000), respectively, with males higher than females. AAPC of crude mortality rate and the standardized (6) mortality rate were higher in males than that in females. The age-specific mortality rate increased with the increase of age, and the highest mortality rate was found in 60-84 years old group. The age-period-cohort model showed that from 1992 to 2021, the annual net shift of pancreatic cancer mortality among the whole population, male and female residents in Xuhui district, Shanghai, was 1.22%, 1.58%, 1.15% (P=0.20, 0.19, 0.45) respectively, and the time trend was not significant. From the perspective of age effect, the risk of death from pancreatic cancer in the whole population and with age deviation in males had an obvious trend with increasing age (P<0.05), while the age effect in females had no obvious trend. From the perspective of period effect, no period deviation was significant in the whole population, males and females (P>0.05). In terms of cohort effects, there were significant differences in the whole population and the male cohort deviations(P<0.05). No significant cohort effect was observed in the female population. Conclusions The mortality rate of pancreatic cancer among registered residents in Xuhui district, Shanghai from 1992 to 2021, was on the rise, especially in the 60-84 years old group and male. The prevention and control of pancreatic cancer needs to develop effective epidemic prevention measures for corresponding populations.

Objective To explore how digital and intelligent technologies can optimize the storage allocation and picking paths for Traditional Chinese medicine decoction pieces.Methods Based on prescription information and medicine data from the hospital information system(HIS),this study employs MATLAB programming to use an integer linear programming(ILP)algorithm for optimizing the storage allocation of Traditional Chinese medicine decoction pieces.Additionally,a greedy algorithm is applied to optimize the picking paths to reduce the picking distance for pharmacists.Finally,an independent samples paired t-test is used to analyze the experimental data to verify the significance of the optimizations.Results A total of 7 734 prescriptions were collected from the HIS.The results of storage optimization showed that the total distance before optimization was(87.58±0.29)m,which was reduced to(85.35±0.28)m after optimization(P﹤0.000 1).The picking path optimization results showed that the picking path was(85.35±0.28)m before optimization and(40.06±0.11)m after optimization(P﹤0.000 1).The results of the independent samples paired t-test indicate that the path was significantly reduced after both storage and picking path optimizations,with statistical significance.Conclusion By using digital and intelligent methods,informatics pharmacists can effectively shorten the picking paths for Traditional Chinese medicine decoction pieces,improve dispensing efficiency,and reduce patient waiting times.

Objective To observe changes of dynamic functional connectivity(dFC)of brain networks in different stages of Parkinson disease(PD).Methods Totally 52 early-stage PD patients(early PD group),36 late-stage PD patients(late PD group)and 38 healthy controls(HC group)were prospectively enrolled,and resting-state functional MRI were performed.The sliding window,independent component analysis and k-means clustering were used to extract dFC intensity and temporal properties,including fractional windows,dwell time and transition frequency.Results Network connectivity patterns within and between visual network(VIS),sensorimotor network(SMN),default mode network(DMN),cerebellar network(CB)and cognitive executive network(CEN)were altered in PD patients.Four dFC states were identified,in which connections between components in states Ⅰ and Ⅱ were compact,while in states Ⅲ and Ⅳ were sparse.The fractional window and dwell time of late PD group,early PD group and HC group successively increased under state Ⅱ,but successively decreased under state Ⅲ(all P＜0.05).Under state Ⅰ and Ⅳ,no significant difference of fractional window nor dwell time was found between early PD group and late PD group(both P＞0.05),and the above indexes under state Ⅰ were both lower than those in HC group(all P＜0.05),the fraction window under state Ⅳ was higher than that in HC group(both P＜0.05).Conclusion The temporal properties of dFC in PD patients were altered,characterized by increased tendency toward segregated states.Furthermore,fractional windows and dwell time were associated with PD disease stages,suggesting that dFC parameters might serve as novel biomarkers for assessing clinical progression of PD.

Objective To explore how digital and intelligent technologies can optimize the storage allocation and picking paths for Traditional Chinese medicine decoction pieces.Methods Based on prescription information and medicine data from the hospital information system(HIS),this study employs MATLAB programming to use an integer linear programming(ILP)algorithm for optimizing the storage allocation of Traditional Chinese medicine decoction pieces.Additionally,a greedy algorithm is applied to optimize the picking paths to reduce the picking distance for pharmacists.Finally,an independent samples paired t-test is used to analyze the experimental data to verify the significance of the optimizations.Results A total of 7 734 prescriptions were collected from the HIS.The results of storage optimization showed that the total distance before optimization was(87.58±0.29)m,which was reduced to(85.35±0.28)m after optimization(P﹤0.000 1).The picking path optimization results showed that the picking path was(85.35±0.28)m before optimization and(40.06±0.11)m after optimization(P﹤0.000 1).The results of the independent samples paired t-test indicate that the path was significantly reduced after both storage and picking path optimizations,with statistical significance.Conclusion By using digital and intelligent methods,informatics pharmacists can effectively shorten the picking paths for Traditional Chinese medicine decoction pieces,improve dispensing efficiency,and reduce patient waiting times.

Objective To explore the value of pulmonary perfusion SPECT/CT imaging for diagnosing pulmonary embolism(PE)and combining with clinical and laboratory indicators for predicting prognosis.Methods Totally 260 patients with suspected PE were retrospectively collected,and PE was clinically confirmed in 237 cases.The diagnostic efficacy of pulmonary perfusion SPECT/CT imaging and CT pulmonary angiography(CTPA)were compared.Among 237 patients with clinically confirmed PE,160 cases were initially diagnosed who underwent standard anticoagulant therapy and were regularly followed up to 3 months after discharge,and their prognosis were analyzed.Logistic regression was used to analyze clinical data,laboratory indicators and pulmonary perfusion defect scores based on pulmonary perfusion SPECT/CT imaging to screen the independent predictors of poor prognosis of PE of the above patients,and a prediction model was then constructed.Receiver operating characteristic(ROC)curve was plotted,and the area under the curve(AUC)was calculated to evaluate the predictive efficacy of this model for predicting prognosis of PE.Results The positive rate of PE diagnosed with pulmonary perfusion SPECT/CT was higher than that with CTPA(66.54％[173/260]vs.59.62％[155/260],x2=4.765,P=0.038).Among 160 cases of clinically confirmed PE,poor prognosis was observed in 51 cases,while good prognosis was noticed in 109 cases.Patients' age,blood urea nitrogen,serum creatinine,uric acid,D-dimer level and pulmonary perfusion defect score were all independent predictors for poor prognosis of PE(all P＜0.05),and AUC of the established combined model was 0.731.Conclusion Pulmonary perfusion SPECT/CT imaging could be used for diagnosing PE,and combining with clinical and laboratory indicators could effectively predict prognosis of PE.

Alcoholic steatohepatitis (ASH) is a liver disease characterized by steatosis, inflammation, and necrosis of the liver tissue as a result of excessive alcohol consumption. Pregnane X receptor (PXR) is a xenobiotic nuclear receptor best known for its function in the transcriptional regulation of drug metabolism and disposition. Clinical reports suggested that the antibiotic rifampicin, a potent human PXR activator, is a contraindication in alcoholics, but the mechanism was unclear. In this study, we showed that the hepatic expression of fatty acid binding protein 4 (FABP4) was uniquely elevated in ASH patients and a mouse model of ASH. Pharmacological inhibiting FABP4 attenuated ASH in mice. Furthermore, treatment of mice with the mouse PXR agonist pregnenolon-16α-carbonitrile (PCN) induced the hepatic and circulating levels of FABP4 and exacerbated ASH in a PXR-dependent manner. Our mechanism study established FABP4 as a transcriptional target of PXR. Treatment with andrographolide, a natural compound and dual inhibitor of PXR and FABP4, alleviated mice from ASH. In summary, our results showed that the PXR-FABP4 gene regulatory axis plays an important role in the progression of ASH, which may have accounted for the contraindication of rifampicin in patients of alcoholic liver disease. Pharmacological inhibition of PXR and/or FABP4 may have its promise in the clinical management of ASH.