This article reports a diagnostically and therapeutically challenging case of small intestinal marginal zone lymphoma. The patient presented with recurrent abdominal pain as the chief complaint, and imaging revealed multifocal small bowel wall thickening with high uptake, multisegmental luminal stenosis, and proximal dilation. Initial diagnostic workup, including gastroscopy, colonoscopy, and enteroscopy with biopsy, failed to establish a definitive diagnosis. Empirical anti-tuberculosis therapy was ineffective. A repeat enteroscopic biopsy performed over eight months after symptom onset eventually confirmed the diagnosis of mucosa-associated lymphoid tissue (MALT) extranodal marginal zone lymphoma. Despite three different chemotherapy regimens, the patient's intestinal obstruction symptoms persisted, with imaging still showing multifocal bowel wall thickening and hypermetabolic activity. A critical diagnostic dilemma arose regarding whether the PET/CT-positive lesions represented residual lymphoma or fibrotic scarring, whether further chemotherapy adjustments were warranted, and whether surgical resection was necessary. Multidisciplinary discussion concluded that imaging had limited discriminatory value in this scenario and that surgical intervention should be pursued if feasible. The patient successfully underwent partial small bowel resection, with postoperative pathology confirming no residual lymphoma but significant fibrotic changes. The patient has since resumed a normal diet, with body weight nearly restored to pre-illness levels. This case highlights that fibrotic transformation is a common sequela of treated marginal zone lymphoma and that PET/CT may misleadingly suggest residual disease, potentially leading to unnecessary chemotherapy. Timely surgical intervention is crucial in such scenarios.

The assessment of adverse drug events is an important basis for clinical safety evaluation and post-marketing risk control of drugs,and its causality assessment is gaining increasing attention.The existing methods for assessing the causal relationship between drugs and the occurrence of adverse reactions can be broadly classified into three categories:global introspective methods,standardized methods,and probabilistic methods.At present,there is no systematic introduction of the operational details of the various methods in the domestic literature.This paper compares representative causality assessment methods in terms of definition and concept,methodological steps,industry evaluation and advantages and disadvantages,clarifies the basic process of determining the causality of adverse drug reactions,and discusses how to further improve the adverse drug reaction monitoring and evaluation system,with a view to providing a reference for drug development and pharmacovigilance work in China.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Pulmonary disease is one of the major threats to human health. However, the current clinical treatment drugs for lung diseases generally have problems such as low lung delivery efficiency, fast clearance rate and obvious toxic side effects. Recently, membrane biomimetic nanocarriers have attracted more and more attention. Due to their advantages of high targeting, long cycle time, good biocompatibility and strong immune escape ability, membrane biomimetic nanocarriers have become a major research hotspot in targeted therapy of lung diseases. In this review, we discuss the main preparation methods of membrane biomimetic nanoparticles, the characteristics of membrane biomimetic nanocarriers from different cell sources and their application in the targeted therapy of lung diseases. At the same time, according to the characteristics of different membranes, the shortcomings, current technical limitations and future prospects are discussed. This review is expected to provide references for the design of membrane biomimetic nanocarriers and their potential applications in the treatment of lung diseases.

A new method was developed for simultaneous detection of total 19 kinds of organophosphate esters(OPEs)and their diester metabolites(di-OPEs)in human serum(1.0 mL)and urine(1.5 mL)with low volume of samples.The target compounds were determined using ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)after acetonitrile liquid-liquid extraction combined with purification using an ENVI-18 solid-phase extraction(SPE)column.OPEs and di-OPEs were separated using a Shim-pack GIST C18 column(100 mm×2.1 mm,2 μm)with a Shim-pack GIST-HP(G)C18 guard column.An electrospray ionization source(ESI)was employed in mass spectrometry analysis,with positive/negative ion mode using the multiple reaction monitoring(MRM).All target compounds were separated within 15 min,and exhibited good linear relationships in the concentration range of 2-100 ng/mL,with correlation coefficients(R2)above 0.994.The method detection limits(MDL)in serum ranged from 0.001 to 0.178 ng/mL and the MDL in urine ranged from 0.001 to 0.119 ng/mL.The recoveries of the analytes spiked in serum and urine matrices at two concentration levels were 30.5%-126.8%,with the relative standard deviations(RSDs)ranged from 1%to 23%.In addition,paired serum and urine samples from 11 patients were analyzed.For all samples tested,the internal standards of OPEs exhibited recoveries between 61%and 114%,whereas the internal standards for di-OPEs had recoveries ranging from 43%to 103%.OPEs and di-OPEs exhibited high detection frequencies in 22 serum and urine samples.Triethyl phosphate(TEP),tributyl phosphate(TBP),tris(2-ethylhexyl)phosphate(TEHP),tris(2-butoxyethyl)phosphate(TBEP),tris(1-chloro-2-propyl)phosphate(TCIPP),triphenyl phosphate(TPHP),tri-m-tolyl-phosphate(TMTP)and 2-ethylhexyl diphenyl phosphate(EHDPP)were universally detected in all serum samples.TCIPP was identified at the highest concentrations(median 0.548 ng/mL)in serum samples.In urine samples,the detection frequency for 12 kinds of target compounds reached 100%.Notably,TBP emerged as the predominant OPE in urine,demonstrating a median concentration of 0.506 ng/mL.Regarding di-OPEs,bis(2-chloroethyl)phosphate(BCEP)and bis(2-butoxyethyl)hydrogen phosphate(BBOEP)were the most abundant in urine,with median concentrations of 6.404 and 2.136 ng/mL,respectively.The total concentrations of OPEs and di-OPEs in serum and urine were 1.580-3.843 ng/mL and 5.149-17.537 ng/mL,respectively.These results not only confirmed the effectiveness of the method in detection of OPEs and di-OPEs in biological matrices,but also revealed the widespread presence of OPE compounds in human body and pointed to potential exposure risks.

Objective:To analyze the role of learning engagement and learning burnout in the relationship between supervisors' guidance and the personal ability of postgraduates in the Professional Master's Program in Clinical Medicine.Methods:A total of 4 016 postgraduates in the Professional Master's Program in Clinical Medicine from 61 colleges were surveyed in 2020. Common method bias was assessed using the Harman's single factor test and total score was determined by the entropy weight method. Causality and mediation effect were analyzed by linear regression, and mediation effect was tested by Bootstrapping.Results:The average scores of supervisors' guidance, learning burnout, learning engagement and personal ability were (4.13±0.87), (2.49±1.11), (3.88±0.83), and (3.71±0.78), respectively. Supervisors' guidance significantly and positively impacted learning engagement ( β=0.689, P<0.001) and personal ability ( β=0.504, P<0.001). Learning engagement played a partial mediating role (89.30% of mediation effect) between supervisors' guidance and personal ability. Learning burnout (interaction term β=0.078, P<0.001) positively regulated the relationship between supervisors' guidance and learning engagement. Conclusions:Learning engagement can mediate the effect of supervisors' guidance on the personal ability of postgraduates in the Professional Master's Program in Clinical Medicine, and learning burnout positively regulates the effect of supervisors' guidance on learning engagement. Strengthened supervisors' guidance, increased attention to students' learning burnout, and enhanced learning engagement can further improve the personal abilities of postgraduates in the Professional Master's Program in Clinical Medicine.

Objective:To investigate the current status of and relationship between practice efficacy, professional identity, and anxiety among public health master's graduates.Methods:From a national survey on the satisfaction with education of fresh medical master's graduates conducted from June to July, 2022, we selected 461 master's graduates of public health with internship experience from 49 institutions. With the use of SPSS 21.0, we compared the scores of practice efficacy, professional identity, and self-rated anxiety by personal characteristics through t-tests and analysis of variance; and explored the mediating role of anxiety in the relationship between practice efficacy and professional identity through stratified regression analysis. Results:The public health master's graduates scored (3.47±1.23) points for anxiety, (3.92±0.88) points for practice efficacy, and (4.33±0.77) points for professional identity. The score of anxiety differed significantly by sex, the degree of being affected by public health emergencies/major outbreaks, and internship initiative (all P<0.05). The score of practice efficacy was significantly different by sex, the type of institution, the degree of being affected by public health emergencies/major outbreaks, and internship initiative (all P<0.05). The score of professional identity differed significantly by sex, the type of institution, major transfer, the degree of being affected by public health emergencies/major outbreaks, internship initiative, and internship duration (all P<0.05). Professional identity was positively correlated with practice efficacy ( r=0.652, P<0.01) and negatively correlated with anxiety ( r=-0.213, P<0.05). The stratified regression results showed that practice efficacy positively influenced professional identity ( β=0.782, P<0.001), and anxiety partially mediated the relationship between the two ( β=-0.104, P<0.05). Conclusions:Anxiety plays a mediating role in the relationship between practice efficacy and professional identity, suggesting that reducing anxiety can help enhance practice efficacy to promote the professional identity of public health master's graduates.

Objective To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography(CBCT)images,and to compare and analyze the estimation re-sults.Methods A total of 498 Shanghai Han adolescents and children CBCT images of the oral and maxillofacial regions were collected.The pulp and tooth volumes of the left maxillary central incisor and cuspid were measured and calculated.Three machine learning algorithms(K-nearest neighbor,ridge regression,and decision tree)and stepwise regression were used to establish four age estimation models.The coefficient of determination,mean error,root mean square error,mean square error and mean ab-solute error were computed and compared.A correlation heatmap was drawn to visualize and the monotonic relationship between parameters was visually analyzed.Results The K-nearest neighbor model(R2=0.779)and the ridge regression model(R2=0.729)outperformed stepwise regression(R2=0.617),while the decision tree model(R2=0.494)showed poor fitting.The correlation heatmap demon-strated a monotonically negative correlation between age and the parameters including pulp volume,the ratio of pulp volume to hard tissue volume,and the ratio of pulp volume to tooth volume.Con-clusion Pulp volume and pulp volume proportion are closely related to age.The application of CBCT-based machine learning methods can provide more accurate age estimation results,which lays a founda-tion for further CBCT-based deep learning dental age estimation research.

Objective To explore the medication rules of Professor HUANG Li for the treatment of recurrent angina pectoris after percutaneous coronary intervention(PCI)for coronary heart disease by data mining method.Methods The prescriptions for effective cases of recurrent angina pectoris after PCI for coronary heart disease treated by Professor HUANG Li in the outpatient department of China-Japan Friendship Hospital were collected.SPSS Statistics 26.0 software and SPSS Modeler 18.0 software were used for frequency statistics,analysis of the therapeutic actions,properties,flavors and meridian tropism of the prescribed herbs as well as association rule analysis,cluster analysis and factor analysis of the herbs.Results A total of 344 Chinese medicine prescriptions were obtained,involving 209 herbs,with a cumulative frequency of 5 874 times.The top 30 Chinese medicinals were named as the high-frequency Chinese medicines,and the herbs with the frequency over 100 times in descending order were Astragali Radix,Chuanxiong Rhizoma,Puerariae Lobatae Radix,Rhodiolae Crenulatae Radix et Rhizoma,Notoginseng Radix et Rhizoma,Poria,Dalbergiae Odoriferae Lignum,Atractylodis Macrocephalae Rhizoma,Curcumae Rhizoma,Sparganii Rhizoma,Dioscoreae Rhizoma,Citri Reticulatae Pericarpium,Pinelliae Rhizoma Praeparatum,Codonopsis Radix,and Glycyrrhizae Radix et Rhizoma.The high-frequency Chinese medicinals were mostly classified as blood-activating and stasis-resolving drugs and qi-replenishing drugs.The medicinal properties of the drugs were characterized by being warm,mild,or cold,the flavors were predominated by being sweet,pungent or bitter,and the medicinals usually had the meridian tropism of the spleen,lung and liver meridians.A total of 30 association rules were mined out,cluster analysis yielded 5 herbal groups,and factor analysis yielded 11 groups of common factors.Conclusion For the treatment of cardiovascular diseases,Professor HUANG Li follows the theory of qi,blood and water,and especially pays more attention to the ascending and descending of qi movement.For qi deficiency and blood stasis contribute to the basic pathogenesis of recurrent angina pectoris after PCI,the therapy of benefiting qi,activating blood and removing stasis is recommended.Moreover,the simultaneous regulation of five zang-organs and simultaneous use of the cold and warm herbs are performed,and the herbs of benefiting qi and invigorating spleen,resolving phlegm and inducing diuresis,tranquilizing mind,promoting qi and dissipating masses,and activating blood to eliminate stasis are used for adjuvant therapy.

Objective To investigate the diagnostic value of CT radiomics features in pulmonary alveolar proteinosis(PAP).Methods The general data and clinical characteristics of 24 patients with PAP in the Chinese PLA General Hospital from November 2008 to August 2022 were retrospectively collected and analyzed.Another 53 patients with other diffuse lung diseases except for PAP during the same period served as control group.The differences in the 10 conventional CT signs(semantic features)and 107 radiomics features between the two groups were compared.All patients were randomly divided into the training group(n=53)and the validation group(n=24)at a ratio of 7:3.CT semantic feature model,radiomics model and combined model to diagnose PAP were constructed in training group,and the diagnostic efficacy of models was compared using the receiver operating characteristic(ROC)curve in validation group.Decision curve analysis(DCA)was used to assess the value of models for practical clinical application.Radscore was calculated for the model with the highest diagnostic efficacy.Results A total of 24 patients with pathologically confirmed PAP were enrolled,with a male to female ratio of 3:1 and an average age of(44.6±15.2)years.The main clinical symptoms of patients with PAP included shortness of breath,cough,sputum and chest tightness.Compared with control group,the incidence of pleural effusion in PAP group was significantly lower(P＜0.05),while no significant differences were observed in other CT features(P＞0.05).The areas under the curve(AUC)of the semantic feature model for diagnosing PAP in training and validation group were 0.590 and 0.594,respectively,and in validation group,the accuracy,sensitivity,and specificity for diagnosis of PAP were 0.188,1.000,and 0.188,respectively.The AUCs of the radiomics model in training group and validation group were 0.845 and 0.867,respectively,and in validation group,the accuracy,sensitivity,and specificity were 0.641,0.938,and 0.703,respectively.The AUCs of the combined model in training group and validation group were 0.850 and 0.883,respectively,and in validation group,the accuracy,sensitivity,and specificity were 0.688,0.750,and 0.938,respectively.The AUCs of the radiomics model and the combined model were significantly greater than that of the semantic feature model,but there was no significant difference in the AUCs between the first two models.The decision curve analysis showed that both the radiomics model and the combined model had high application value for predicting PAP.Conclusion CT radiomics shows higher clinical value in the diagnosis of PAP compared with conventional CT features.