Histopathological examination is currently the gold standard for the diagnosis of metabolic associated fatty liver disease （MAFLD）； however， due to its invasiveness， high risks， and low feasibility， application of noninvasive indicators in the staging and classification of MAFLD has become a research hotspot. This article systematically reviews the efficacy of dynamic changes in various noninvasive markers in reflecting histological changes and clinical outcome events in MAFLD patients， in order to provide theoretical support for dynamic monitoring and individualized management of the disease.

Objective To construct a glioma microfluidic chip model to simulate tumor microenvironment for evaluating the medicinal efficacy of anti-glioma traditional Chinese medicines. Methods Glioblastoma cells U251 were seeded into microfluidic chips with different culture modes, and the cell viability and tumour microenvironment within the constructed model were characterized. Fluorescence staining was used to evaluate the effects of the positive drugs temozolomide （TMZ） and docetaxel （DOC） on the cell activity and apoptosis within the model, which was applied to evaluate the medicinal efficacy of the extracts of the herb Scutellaria barbata on gliomas. Results The cells in the constructed U251 microfluidic chip model displayed high viability and were able to mimic the hypoxic microenvironment of tumor to a certain extent. The viability of the U251 cells in the microfluidic chips decreased with the increasing of the concentration of the positive drug, and the viability of the 3D cultured U251 cells was higher than that in the 2D condition （P<0.05）. The intracellular mitochondrial membrane potential decreased with the increasing of the concentration of the positive drug. And the 2 mg/ml Scutellaria barbata extract killed U251 cells to a certain extent and reduced the mitochondrial membrane potential of the cells in the model. Conclusion This study successfully constructed a microfluidic chip model of glioma that could effectively simulate the tumor microenvironment and rapidly evaluate the anti-tumor medicinal efficacy, which provided a new strategy for the medicinal efficacy evaluation and active components screening of anti-glioma traditional Chinese medicines.

Objective To evaluate the efficacy of Puerariae lobatae radix （PLR） and Anemarrhenae Rhizoma （AR） in preventing and treating Alzheimer’s disease （AD） and explore its potential mechanism of action by LC-MS serum metabolomics strategy. Methods The AD rat model was established by administering aluminum chloride （AlCl₃） and D-galactose （D-gal） for 20 weeks. The traditional Chinese medicine intervention group was given the PLR, AR, and PLR-AR extracts for 8 weeks by gavage. The model effect and efficacy were evaluated by Morris water maze test and biochemical indicators including SOD, NO, and MDA; Metabolomics research based on the UHPLC-Q/TOF-MS method was conducted, and relevant metabolic pathways were analyzed through the MetaboAnalyst online website. Results The learning and memory abilities of AD model rats were significantly decreased compared with the control group, and the levels of oxidative stress and lipid peroxides were significantly increased （P<0.05）, while the SOD content was decreased considerably （P<0.01）. The learning and memory abilities of AD model rats were improved, oxidative stress and lipid peroxidation levels were reversed, and serum SOD content was increased significantly after the intervention of PLR-AR, with better effects than single drugs. Through metabolomics, 70 differential metabolites were identified between the AD model group and the control group, mainly involving 10 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and unsaturated fatty acid biosynthesis, et.al. The intervention of PLR-AR could adjust 47 metabolites, with 20 metabolites showing significant differences （P<0.05）. The significantly adjusted metabolites involve 6 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, et al. Conclusion The combination of PLR and AR could significantly improve the learning and memory abilities of AD rat models. The mechanism may be related to the improvement of oxidative stress and lipid peroxidation levels, the increase of serum SOD content, and the regulation of phenylalanine, tyrosine, and tryptophan biosynthesis pathways.

Autism spectrum disorder involves challenges in social communication and restricted, repetitive behaviors. Historically, males have received autism diagnoses at comparatively high rates, prompting an underrepresentation of females in research and an incomplete understanding of sex-specific symptom presentations and comorbidities. This review examines sex differences in the prevalence of common comorbidities of autism to inform tailored clinical practices. These conditions include attention deficit hyperactivity disorder, anxiety disorders, conduct disorder, depression, epilepsy, intellectual disability, and tic disorders. Attention deficit hyperactivity disorder is prevalent in both sexes; however, females may more frequently exhibit the inattentive subtype. Anxiety disorders display inconsistent sex differences, while conduct disorder more frequently impacts males. Depression becomes more common with age; some studies indicate more pronounced symptoms in adolescent girls, while others suggest greater severity in males. Epilepsy is more prevalent in females, especially those with intellectual disabilities. Despite displaying a male predominance, intellectual disability may exacerbate the severity of autism to a greater degree in females. No clear sex differences have been found regarding tic disorders. Overall, contributors to sex-based differences include biases stemming from male-centric diagnostic tools, compensatory behaviors like camouflaging in females, genetic and neurobiological differences, and the developmental trajectories of comorbidities. Recognizing these factors is crucial for developing sensitive diagnostics and sex-specific interventions. Inconsistencies in the literature highlight the need for longitudinal studies with large, diverse samples to investigate autism comorbidities across the lifespan. Understanding sex differences could facilitate earlier identification, improved care, and personalized interventions, thus enhancing quality of life for individuals with autism.

Background/Aims: Cholecystectomy for gallbladder (GB) polyps is performed primarily based on preoperative images. This study examined the accuracy of surgical indications commonly used in clinical practice for detecting neoplastic polyps and investigated further clues for predicting neoplastic polyps. Methods: This retrospective study included 385 patients who underwent a cholecystectomy for GB polyps. The predictive performances of seven surgical indications were compared by fitting the receiver operating characteristic curves. Logistic regression analysis was used to identify the candidate variables associated with predicting neoplastic polyps. Results: Neoplastic polyps were identified in 18.9% (n=62) of the 385 patients assessed. The neoplastic group contained more females than males, larger polyps, more frequent solitary lesions, and lower platelet counts than the non-neoplastic group. Current surgical indications revealed an unsatisfactory prediction for neoplastic polyps. The optimal cutoff polyp size for neoplastic polyps by ultrasound (US) was larger than by computed tomography (CT) (12 mm vs. 10 mm). The proportion of pathologic neoplastic polyps was higher when both US and CT images were used than that predicted using a single test. Logistic regression analysis revealed larger polyps, increasing age, female sex, and lower platelet count to be associated with neoplastic polyps. Conclusions The current indications for cholecystectomy in GB polyps have a low predictive value for neoplastic lesions that can lead to overtreatment. Combining the polyp size from US and CT images may reduce unnecessary surgery. In addition, knowledge of the patient's age, sex, and platelet count could help make more selective surgical decisions for neoplastic polyps.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Objective: To prepare platelet membrane biomimetic liposomes loaded with vincristine sulfate (VCR) for targeted delivery to tumor. Methods: Vincristine sulfate liposomes (LIPO) were prepared using the pH-gradient method, followed by the fusion of platelet membranes and subsequent drug loading to obtain platelet membrane biomimetic liposomes (PLM-LIPO). The particle size, polydispersity index (PDI), Zeta potential, and drug encapsulation efficiency (EE%) of both liposomes were characterized. The tumor-targeting capability was evaluated through in vitro cellular experiments and in vivo biodistribution studies. Results: The optimal preparation conditions for LIPO were determined as follows: DPPC-to-cholesterol molar ratio of 1∶1, internal aqueous phase of 0.3 M pH 4.0 citrate buffer, external aqueous phase of 1 M Na HPO solution, drug-to-lipid ratio of 1∶10, drug loading temperature of 60℃, and loading time of 10 minutes. The LIPO exhibited a mean particle size of (147.3±2.24) nm, PDI of 0.078±0.014, Zeta potential of (-3.54±0.75) mV, and EE% of 91.37±0.47. For PLM-LIPO, prepared via membrane fusion followed by drug loading, the mean particle size was (185.3±3.61) nm, PDI was 0.075±0.022, Zeta potential was (-18.91±1.54) mV, and EE% was 63.36±2.45. In the CD62P validation experiment, the fluorescence intensity of PLM-LIPO was five times higher than that of LIPO. In vitro cellular uptake experiments revealed that PLM-LIPO showed 1.3-fold and 1.2-fold higher uptake rates compared to LIPO at 6 h and 12 h, respectively. In vivo experiments demonstrated that 1h after administration, the accumulation of PLM-LIPO at tumor sites was 4-fold higher than that of LIPO and 6-7 times higher than that in healthy mice. Conclusion: The platelet membrane biomimetic liposomes loaded with vincristine sulfate were successfully developed. Both cellular uptake and tissue distribution studies confirmed the PLM-LIPO enhanced tumor-targeting capability.

OBJECTIVE To establish a pharmaceutical management model for infusion safety in hospitalized inpatients and ensure the safety of drug use. METHODS Our hospital established the standardized management process for infusion scheme， formulated rules for compatibility contraindications in drug combinations. In the form of embedded hospital official account, the infusion scheme and medication guidance WeChat developed by pharmacists are pushed to the mobile phone of inpatients, providing electronic medication guidance services for patients, and forming a pharmaceutical management model for infusion safety of inpatients. RESULTS Our hospital provided a total of 45 291 inpatients with pharmaceutical services including the formulation of individualized infusion scheme and WeChat push infusion scheme and medication guidance as of December 2023. After the implementation of the management model， the intervention rate of pharmacists on the compatibility contraindications in drug combination of long-term medical orders for inpatients increased from 18.25% before implementation to 90.58% （P＜0.01）， and the satisfaction rate of inpatients increased from 87.50% to 94.50% （P＜0.05）. CONCLUSIONS The pharmaceutical management model for infusion safety of hospitalized patients integrates pharmaceutical services throughout the entire process of intravenous medication treatment. Pharmacists can participate in the management of infusion usage while providing qualified finished infusion products, achieving closed-loop management of pharmaceutical services, improving the hospital’s pharmaceutical service capabilities and patient satisfaction, and providing guarantees for the safety and effectiveness of patient medication.

Purpose: Cystic duct cancers (CDCs) have been classified as extrahepatic bile duct cancers or gallbladder cancers (GBCs); however, it is unclear whether their clinical behavior is similar to that of distal extrahepatic bile duct cancers (DBDCs) or GBCs. Materials and Methods: T category of the CDCs was classified using current T category scheme of the GBCs and DBDCs, and clinicopathological factors were compared among 38 CDCs, 345 GBCs, and 349 DBDCs. We modified Nakata’s classifications (type 1, confined within cystic duct [CD]; combined types 2-4, extension beyond CD) and compared them. Results: No significant overall survival (OS) difference was observed between the patients with CDC, GBC, and DBDC. The T category of GBC staging was more accurate at distinguishing OS in patients with CDC than the DBDC staging. Patients with T3 CDC and GBC showed a significant OS difference when using the T category for GBC staging, while those with T1-T2 CDC and GBC showed no significant difference. In contrast, the T category of DBDC staging did not show any significant OS difference between patients with T1-T2 CDC and DBDC or T3 CDC and DBDC. Patients with type 1 CDC had significantly better OS than those with combined types. Conclusion Unlike GBCs and DBDCs, CDCs exhibit distinct clinicopathological characteristics. The OS is better when the CDC confines within the CD, compared to when it extends beyond it. Therefore, we propose a new T category scheme (T1, confined to CD; T2, invaded beyond CD) for better classifying CDCs.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.