ObjectiveTo investigate the effect of honokiol on proliferation， apoptosis， migration， and invasion of gastric cancer cells and its underlying mechanistic. MethodsHuman gastric cancer cell lines HGC-27 and AGS were treated with Honokiol at concentrations of 0， 15， and 25 μmol/L. CCK-8 assays were conducted to determine the half maximal inhibitory concentration （IC₅₀） for both cell lines. Cell viability， proliferation， migration， and invasion capabilities were assessed using CCK-8， colony formation， wound healing， Transwell migration and Transwell invasion assays. Apoptosis rates were measured via flow cytometry. Western blot analysis examined proteins related to proliferation， apoptosis， migration， invasion， and the endoplasmic reticulum stress pathway ATF4-CHOP-TRIB3. ResultsCompared with the control group， treatment with 15 and 25 μmol/L Honokiol significantly reduced the proliferation， colony formation， migration， and invasion capabilities of the two gastric cancer cell lines， while significantly increasing the apoptosis rate （P<0.05）. Additionally， compared to the control group， the protein expression levels of neural cadherin（N-cadherin）， Vimentin， proliferating cell nuclear antigen（PCNA）， and B-cell lymphoma/leukemia-2 protein（Bcl-2）decreased in the two gastric cancer cell lines after treatment with 15 and 25 μmol/L Honokiol， while the protein expression levels of epithelial cadherin（E-cadherin）， Bcl-2-associated X protein（Bax）， activating transcription factor 4（ATF4）， endoplasmic reticulum stress-related protein（CHOP）， and tribbles homolog 3（TRIB3）increased（P<0.05）. ConclusionHonokiol promotes apoptosis and inhibits proliferation， migration， and invasion of gastric cancer HGC-27 and AGS cells by regulating the ERS signaling pathway ATF4/CHOP/TRIB3.

Pancreatic portal hypertension （PPH） is a type of regional portal hypertension secondary to pancreatic diseases and their complications. Unlike portal hypertension caused by liver cirrhosis， PPH is confined to the splenic venous system， and most patients tend to have normal liver function. Splenic vein obstruction and impaired blood return are the core mechanisms underlying the development of PPH， and isolated gastric fundal varices represent a characteristic manifestation of PPH. For patients with pancreatic diseases， it is necessary to establish early warning and risk stratification strategies， and high-quality studies are needed to further confirm the safety and efficacy of anticoagulation， surgical approaches， and interventional therapies in patients with PPH. This article systematically reviews the pathogenesis， etiological classification， clinical features， and key diagnostic points of PPH and discusses the current status of PPH treatment and existing challenges.

[Objective] To assess the data characteristics of quality monitoring indicators for red blood cell (RBC) preparations, so as to provide reference for continuous improvement of blood quality. [Methods] The quality inspection data of 6 types of RBC preparations from Chongqing blood center from 2019 to 2023 were summarized. For the same indicators, the numerical range of quality indicators was monitored by comparing different types of preparations with the national standard GB18469. The loss and/or damage to RBCs caused by different preparation process were compared, and the impact of different preparation processes on the quality of RBCs was discussed. [Results] The appearance and sterility test compliance rates of the six types of RBC preparations were both 100%, while the compliance rates of other items were all ≥75%. The compliance rate of hematocrit for suspended RBCs was the lowest at 75%, with a median of 0.52, which was close to the lower limit of GB18469, while the medians of hematocrit for the other types were all at the midline level of GB18469. The Hb content for different types of RBCs was significantly higher than the corresponding requirements of GB18469 (P<0.05). The hemolysis rate at the end of storage for different types of RBCs was significantly lower than the requirements of GB18469 (P<0.05). The 1 U leukoreduction process resulted in a hemoglobin content loss of about 5% and had a significant impact on the hemolysis rate at the end of storage (P<0.05). The washing process resulted in a hemoglobin content loss of <3% and had no significant impact on the hemolysis rate at the end of storage (P>0.05). The concentration process resulted in a hemoglobin content loss of <3% and had a significant impact on the hemolysis rate at the end of storage (P<0.05). [Conclusion] The impact of different processes on RBC preparations is within a controllable range and meets the requirements of GB18469. The quality monitoring data can provide a reference for clinical blood selection, effectiveness evaluation and revision of related standards.

Background: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment, its standalone efficacy is debated. This study examined the effectiveness of the MMSE alone versus in combination with other cognitive assessments in predicting dementia diagnosis, with the aim of refining the diagnostic accuracy for dementia. Methods: A total of 2,863 participants with subjective cognitive complaints who underwent comprehensive neuropsychological assessments were included. We developed two random forest models: one using only the MMSE and another incorporating additional cognitive tests.These models were evaluated based on their accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) on a 70:30 training-to-testing split. Results: The MMSE-alone model predicted dementia with an accuracy of 86% and AUC of 0.872. The expanded model demonstrated increased accuracy (88%) and an AUC of 0.934.Notably, 17.46% of the cases were reclassified from dementia to non-dementia category upon including additional tests. Higher educational level and younger age were associated with these shifts. Conclusion The findings suggest that although the MMSE is a valuable screening tool, it should not be used in isolation to determine dementia severity. The addition of diverse cognitive assessments can significantly enhance diagnostic precision, particularly in younger and more educated populations. Future diagnostic protocols should integrate multifaceted cognitive evaluations to reflect the complexity of dementia accurately.

Background: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment, its standalone efficacy is debated. This study examined the effectiveness of the MMSE alone versus in combination with other cognitive assessments in predicting dementia diagnosis, with the aim of refining the diagnostic accuracy for dementia. Methods: A total of 2,863 participants with subjective cognitive complaints who underwent comprehensive neuropsychological assessments were included. We developed two random forest models: one using only the MMSE and another incorporating additional cognitive tests.These models were evaluated based on their accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) on a 70:30 training-to-testing split. Results: The MMSE-alone model predicted dementia with an accuracy of 86% and AUC of 0.872. The expanded model demonstrated increased accuracy (88%) and an AUC of 0.934.Notably, 17.46% of the cases were reclassified from dementia to non-dementia category upon including additional tests. Higher educational level and younger age were associated with these shifts. Conclusion The findings suggest that although the MMSE is a valuable screening tool, it should not be used in isolation to determine dementia severity. The addition of diverse cognitive assessments can significantly enhance diagnostic precision, particularly in younger and more educated populations. Future diagnostic protocols should integrate multifaceted cognitive evaluations to reflect the complexity of dementia accurately.

Background: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment, its standalone efficacy is debated. This study examined the effectiveness of the MMSE alone versus in combination with other cognitive assessments in predicting dementia diagnosis, with the aim of refining the diagnostic accuracy for dementia. Methods: A total of 2,863 participants with subjective cognitive complaints who underwent comprehensive neuropsychological assessments were included. We developed two random forest models: one using only the MMSE and another incorporating additional cognitive tests.These models were evaluated based on their accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) on a 70:30 training-to-testing split. Results: The MMSE-alone model predicted dementia with an accuracy of 86% and AUC of 0.872. The expanded model demonstrated increased accuracy (88%) and an AUC of 0.934.Notably, 17.46% of the cases were reclassified from dementia to non-dementia category upon including additional tests. Higher educational level and younger age were associated with these shifts. Conclusion The findings suggest that although the MMSE is a valuable screening tool, it should not be used in isolation to determine dementia severity. The addition of diverse cognitive assessments can significantly enhance diagnostic precision, particularly in younger and more educated populations. Future diagnostic protocols should integrate multifaceted cognitive evaluations to reflect the complexity of dementia accurately.

Objective: To investigate the clinical characteristics, the types of unexpected antibodies, and their impacts on immunological risks among patients with different frequencies of cross-matching incompatibility, so as to propose corresponding solutions. Methods: Data of cross-matching incompatibility samples from 92 medical institutions during 2022 to 2024 were collected and divided into three groups based on the frequency of cross-matching. Statistical analysis was performed on disease types, distribution of hematologic diseases, alloantibody detection rates, and proportions of alloantibody types. Results: The 858 patients were divided into three groups based on the frequency of blood cross-matching incompatibility: ≥5 times (8.28%, 71/858), 2 to 4 times (28.21%, 242/858); 1 time (63.52%, 545/858). There was a clustered distribution of disease types in the ≥5 cross-matchings group, with 71.83% (51/71) of patients having tumors or hematologic and hematopoietic diseases. In contrast, the disease types in the 2 to 4 cross-matchings and 1 cross-matching groups were more diverse. An analysis of 249 patients with hematologic diseases found that multiple myeloma was the most common disease in all three groups, accounting for 31.43% (11/35), 35.37% (29/82), and 37.88% (50/132) respectively. In the ≥5 cross-matchings group, myelodysplastic syndrome (14.29%, 5/35) and thalassemia (14.29%, 5/35) were the second most common diseases. In contrast, in the 2 to 4 cross-matchings group and 1 cross-matching group, autoimmune hemolytic anemia was the second most common disease, with prevalence rates of 20.73% (17/82) and 24.24% (32/132), respectively. Alloantibodies were detected in 54.66% of the patients, with antibodies against Rh blood group being most frequent (>50%) in all three groups. The detection rates of alloantibodies/alloantibodies with coexisting autoantibodies decreased across groups: the ≥5 cross-matchings group (70.42%, 50/71) > the 2 to 4 cross-matchings group (54.96%, 133/242) > the 1 cross-matching group (52.48%, 286/545). Conclusion: The risk of alloantibody production increases in patients with multiple cross-matching incompatibilities, especially in those with tumors or hematologic diseases. For handling of cross-matching incompatibility cases, it is recommended to optimize the cross-matching process, implement individualized transfusion plans, and enhance the technical capabilities of clinical transfusion departments and blood group reference laboratories to ensure the safety and effectiveness of transfusions.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Objective To investigate application value of three-dimensional light sheet microscopy imaging for evaluating intraplaque neovascularization in arterial plaques and the efficacy of intervention,and to assess the effect of melatonin(MLT)on neovascularization by these means.Methods Thirty-six ApoE-/-model mice were randomly divided into three groups(n=12):vehicle group,MLT group,and MLT+GW9662 intervention group(MLT+GW).The mice were treated with vehicle,MLT alone,or MLT combined with peroxisome proliferator activated receptor-γ(PPARγ)inhibitor GW9662,respectively.The carotid arteries of the models were three-dimensionally imaged using a light sheet microscopy,and the length,volume and other indicators of neovascularization were quantitatively analyzed using Imaris software.Subsequently,CD31 immunohistochemical staining was performed for verification.Results The light sheet microscopy preliminarily achieved the three-dimensional visualization of intraplaque neovascularization,and its structure was observed to be three-dimensionally reticular and scattered.The results of Imaris quantitative analysis showed that,compared with vehicle group,the total intraplaque neovas cularization length in the MLT group was shortened[(15.79±12.90)mm vs.(33.42±11.16)mm,P<0.05],the total volume was reduced[(1.34±1.47)×10-3 mm3 vs.(13.44±7.35)×10-3 mm3,P<0.05],and the volume ratio was decreased(0.44%±0.47%vs.3.76%±1.74%,P<0.05).The above indicators in MLT+GW group were significantly increased compared with those in MLT group[total length:(35.31±4.69)mm,total volume:(8.87±3.46)×10-3 mm3,volume ratio:2.89%±0.38%;P<0.05].The CD31 immunohistochemical staining also supported the above findings(P<0.05).Conclusions Based on the light sheet microscopy imaging technology,the three-dimensional visualization and quantitative analysis of intraplaque neovascularization were preliminarily realized.It was found that MLT could reduce the overall burden of intraplaque neovascularization,and PPARγ might be involved in its regulatory process.

Prostate-specific membrane antigen(PSMA)positron emission tomography(PET)is currently a precise diagnostic imaging technology for prostate cancer(PCa).Artificial intelligence(AI)technologies,particularly machine learning and deep learning algorithms,when combined with PSMA PET,showed extensive potential applications in various aspects of PCa management.These include the diagnosis and differential diagnosis of primary tumors,staging,recurrence detection,and treatment planning for PCa.At present,a few AI models have received clinical approval.This paper reviews the application progress of AI combined with PSMA PET in the diagnosis and treatment of PCa,explores the current limitations of AI technologies in clinical practice,and aim to provide references to future diagnosis and treatment studies for PCa.