ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Objective To build a healthcare data quality testing system to solve the problems due to low-quality data.Methods The system was developed based on 11 evaluation indicators in four categories including completeness,accuracy,data scope and timeliness,which was realized with MySQL 5.7 database,Browser/Server(B/S)architecture,Python,Java,Vue language and vscode neovim development tool.There were four functional modules involved in the system for system setup,data management,quality management and quality analysis.Results The system developed managed data quality testing rules flexibly and normatively,which could be used for periodical analysis of data quality and viewing of data testing results conveniently and enhanced the efficiency for testing data quality and solving data quality problems.Conclusion The system developed enhances data quality and provides data support for hospitals.[Chinese Medical Equipment Journal,2024,45(4):7-12]

Objective To construct a big data sharing platform for clinical scientific research to solve the problems of clinical research in decentralized application systems and data sharing safety.Methods A clinical research information data usage management system was developed through the formulation of management methods in line with the actual situation of the institution,normalized standard data usage processes and a data usage service team.Then a clinical scientific research big data sharing platform including the components for sharing environment construction,research application integration,data desensitization and encryption and file management was established based on the existing hospital systems,the requirements of clinical research data usage management and the habits of clinical researchers.Results The platform realized the balance between open sharing of clinical research data and data security control,which improved the efficiency of clinical researchers while reducing data security risks during data transmission and data analysis.Conclusion The clinical scientific research big data sharing platform meets the needs of clinical scientific research application and data security management,and provides references for the co-construction-sharing of medical big data resources.[Chinese Medical Equipment Journal,2024,45(4):27-31]

OBJECTIVE: To explore the genotyping characteristics of human fecal Escherichia coli( E. coli) and the relationships between antibiotic resistance genes (ARGs) and multidrug resistance (MDR) of E. coli in Miyun District, Beijing, an area with high incidence of infectious diarrheal cases but no related data. METHODS: Over a period of 3 years, 94 E. coli strains were isolated from fecal samples collected from Miyun District Hospital, a surveillance hospital of the National Pathogen Identification Network. The antibiotic susceptibility of the isolates was determined by the broth microdilution method. ARGs, multilocus sequence typing (MLST), and polymorphism trees were analyzed using whole-genome sequencing data (WGS). RESULTS: This study revealed that 68.09% of the isolates had MDR, prevalent and distributed in different clades, with a relatively high rate and low pathogenicity. There was no difference in MDR between the diarrheal (49/70) and healthy groups (15/24). CONCLUSION We developed a random forest (RF) prediction model of TEM.1 + baeR + mphA + mphB + QnrS1 + AAC.3-IId to identify MDR status, highlighting its potential for early resistance identification. The causes of MDR are likely mobile units transmitting the ARGs. In the future, we will continue to strengthen the monitoring of ARGs and MDR, and increase the number of strains to further verify the accuracy of the MDR markers.
Humans ; Escherichia coli/genetics* ; Escherichia coli Infections/epidemiology* ; Multilocus Sequence Typing ; Genotype ; Beijing ; Drug Resistance, Multiple, Bacterial/genetics* ; Anti-Bacterial Agents/pharmacology* ; Diarrhea ; Microbial Sensitivity Tests

OBJECTIVE: To screen the prognostic biomarkers of metabolic genes in patients with multiple myeloma (MM), and construct a prognostic model of metabolic genes. METHODS: The histological database related to MM patients was searched. Data from MM patients and healthy controls with complete clinical information were selected for analysis.The second generation sequencing data and clinical information of bone marrow tissue of MM patients and healthy controls were collected from human protein atlas (HPA) and multiple myeloma research foundation (MMRF) databases. The gene set of metabolism-related pathways was extracted from Molecular Signatures Database (MSigDB) by Perl language. The biomarkers related to MM metabolism were screened by difference analysis, univariate Cox risk regression analysis and LASSO regression analysis, and the risk prognostic model and Nomogram were constructed. Risk curve and survival curve were used to verify the grouping effect of the model. Gene set enrichment analysis (GSEA) was used to study the difference of biological pathway enrichment between high risk group and low risk group. Multivariate Cox risk regression analysis was used to verify the independent prognostic ability of risk score. RESULTS: A total of 8 mRNAs which were significantly related to the survival and prognosis of MM patients were obtained (P<0.01). As molecular markers, MM patients could be divided into high-risk group and low-risk group. Survival curve and risk curve showed that the overall survival time of patients in the low-risk group was significantly better than that in the high risk group (P<0.001). GSEA results showed that signal pathways related to basic metabolism, cell differentiation and cell cycle were significantly enriched in the high-risk group, while ribosome and N polysaccharide biosynthesis signaling pathway were more enriched in the low-risk group. Multivariate Cox regression analysis showed that the risk score composed of the eight metabolism-related genes could be used as an independent risk factor for the prognosis of MM patients, and receiver operating characteristic curve (ROC) showed that the molecular signatures of metabolism-related genes had the best predictive effect. CONCLUSION Metabolism-related pathways play an important role in the pathogenesis and prognosis of patients with MM. The clinical significance of the risk assessment model for patients with MM constructed based on eight metabolism-related core genes needs to be confirmed by further clinical studies.
Humans ; Cell Cycle ; Multiple Myeloma/genetics* ; Prognosis ; Risk Factors

OBJECTIVE: To predict the trends for fine-scale spread of Oncomelania hupensis based on supervised machine learning models in Shanghai Municipality, so as to provide insights into precision O. hupensis snail control. METHODS: Based on 2016 O. hupensis snail survey data in Shanghai Municipality and climatic, geographical, vegetation and socioeconomic data relating to O. hupensis snail distribution, seven supervised machine learning models were created to predict the risk of snail spread in Shanghai, including decision tree, random forest, generalized boosted model, support vector machine, naive Bayes, k-nearest neighbor and C5.0. The performance of seven models for predicting snail spread was evaluated with the area under the receiver operating characteristic curve (AUC), F1-score and accuracy, and optimal models were selected to identify the environmental variables affecting snail spread and predict the areas at risk of snail spread in Shanghai Municipality. RESULTS: Seven supervised machine learning models were successfully created to predict the risk of snail spread in Shanghai Municipality, and random forest (AUC = 0.901, F1-score = 0.840, ACC = 0.797) and generalized boosted model (AUC= 0.889, F1-score = 0.869, ACC = 0.835) showed higher predictive performance than other models. Random forest analysis showed that the three most important climatic variables contributing to snail spread in Shanghai included aridity (11.87%), ≥ 0 °C annual accumulated temperature (10.19%), moisture index (10.18%) and average annual precipitation (9.86%), the two most important vegetation variables included the vegetation index of the first quarter (8.30%) and vegetation index of the second quarter (7.69%). Snails were more likely to spread at aridity of < 0.87, ≥ 0 °C annual accumulated temperature of 5 550 to 5 675 °C, moisture index of > 39% and average annual precipitation of > 1 180 mm, and with the vegetation index of the first quarter of > 0.4 and the vegetation index of the first quarter of > 0.6. According to the water resource developments and township administrative maps, the areas at risk of snail spread were mainly predicted in 10 townships/subdistricts, covering the Xipian, Dongpian and Tainan sections of southern Shanghai. CONCLUSIONS Supervised machine learning models are effective to predict the risk of fine-scale O. hupensis snail spread and identify the environmental determinants relating to snail spread. The areas at risk of O. hupensis snail spread are mainly located in southwestern Songjiang District, northwestern Jinshan District and southeastern Qingpu District of Shanghai Municipality.
Animals ; Bayes Theorem ; China/epidemiology* ; Ecosystem ; Gastropoda ; Supervised Machine Learning

Intestinal obstruction is one of the most common diseases in abdominal surgery, and its prevention and treatment is a clinical difficulty. Although surgical operation can solve the symptoms of obstruction, there are many postoperative complications, and it is easy to develop re-obstruction due to postoperative abdominal adhesion. The internal fixation of small intestine with obstruction catheter provides a new idea for the prevention of postoperative adhesive bowel obstruction. The use of transanal ileus catheter provides the possibility of direct intestinal anastomosis after resection of malignant obstruction in the left hemicolon and can reduce the incidence of postoperative complications. However, sufficient attention should be paid to the related complications, and prevention and treatment should be planned. It is important to note that the use of obstruction catheter is only one of the conservative treatments for bowel obstruction, and it is not a complete replacement of surgery. Surgical treatment should still be considered, if the catheter fails to significantly move, if the obstructive symptoms do not significantly improve 5 days after catheterization.
Catheters ; Digestive System Surgical Procedures ; Humans ; Intestinal Obstruction/surgery* ; Intestine, Small ; Tissue Adhesions

Objective:Recently, increasing number of lung cancer patients benefit from immune-checkpoint inhibitors (ICIs). However, the data of Chinese small cell lung cancer (SCLC) patients is limited. This study aims to analyze the response and survival data of ICIs treatment in SCLC and to explore the predictive biomarkers.Methods:Forty-seven SCLC patients who received ICIs treatment from Peking University Cancer Hospital from May 2017 to September 2019 was recruited. Clinical characteristics including sex, age, smoking status, ICIs strategy, PD-L1 expression and therapeutic efficacy were collected to explore the clinical predictive biomarkers for SCLC ICIs treatment.Results:Among the 47 patients, 18 (38.3%) cases were partial repose (PR), 11 (23.4%) were stable disease (SD), 18 (38.3%) were progressive disease (PD), and the objective response rate (ORR) was 38.3%, disease control rate (DCR) was 61.7%, the median progression-free survival (PFS) was 5.3 months. ICIs monotherapy accounts for 27.7%, the ORR was 15.4%, DCR was 53.8%, median PFS was 2.7 months. Combined therapy accounts for 72.3%, the ORR was 47.1%, DCR was 64.7%, median PFS was 5.4 months. Fourteen (29.8%) patients received ICIs as the first line treatment, their ORR was 85.7%, DCR was 100%, median PFS was 9.1 month. The ORR was not related to the age, sex, body mass index (BMI), smoking status and programmed death-ligand 1 (PD-L1) expression ( P>0.05). The ORRs were higher in patients underwent PD-L1 monotherapy ( P=0.001), combined therapy ( P=0.002) and received ICIs as the first line treatment ( P<0.001). Log-rank analysis indicated that the PFS of female patients were 12.0 months, significantly longer than 4.4 months of male patients in ICIs treatment ( P=0.038). Patients who received PD-L1 monotherapy, combined treatment, or ICIs as the first line treatment had longer PFS than their counterparts, though no statistical significant was observed ( P>0.05). Cox multivariate analysis showed that, the gender was not an independent predictor for PFS in ICIs treatment ( HR=3.777, 95% CI=0.974~30.891, P=0.054). Conclusions:Immunotherapy is an effective treatment strategy for SCLC. Patients who receive combined ICIs treatment, first line ICIs treatment and PD-L1 treatment may get greater benefits. PD-L1 expression cannot predict the response and PFS in SCLC ICIs treatment.