OBJECTIVE: To investigate the impact of bone mass and volume of low-density zones beneath the tibial plateau on the maximum von Mises stresses experienced by the cartilage and meniscus in the knee joint. METHODS: The study included one healthy adult volunteer, from whom CT scans were obtained, and one patient diagnosed with knee osteoarthrisis (KOA), for whom X-ray films were acquired. A static model of the knee joint featuring a low-density zone was established based on a normal knee model. In the finite element analysis, axial loads of 1 000 N and 1 800 N were applied to the weight-bearing region of the upper surface of the femoral head for model validation and subsequent finite element studies, respectively. The maximum von Mises stresses in the femoral cartilage, as well as the medial and lateral tibial cartilage and menisci, were observed, and the stress percentage of the medial and lateral components were concurrently analyzed. Additionally, HE staining, as well as alkaline magenta staining, were performed on the pathological specimens of patients with KOA in various low-density regions. RESULTS: The results of model validation indicated that the model was consistent with normal anatomical structures and correlated with previous calculations documented in the literature. Static analysis revealed that the maximum von Mises stress in the medial component of the normal knee was the lowest and increased with the advancement of the hypointensity zone. In contrast, the lateral component exhibited an opposing trend, with the maximum von Mises stress in the lateral component being the highest and decreasing as the hypointensity zone progressed. Additionally, the medial component experienced an increasing proportion of stress within the overall knee joint. HE staining demonstrated that the chondrocyte layer progressively deteriorated and may even disappear as the hypointensity zone expanded. Furthermore, alkaline magenta staining indicated that the severity of microfractures in the trabecular bone increased concurrently with the expansion of the hypointensity zone. CONCLUSION The presence of subtalar plateau low-density zone may aggravate joint degeneration. In clinical practice, it is necessary to pay attention to the changes in the subtalar plateau low-density zone and actively take effective measures to strengthen the bone status of the subtalar plateau low-density zone and restore the complete biomechanical function of the knee joint, in order to slow down or reverse the progression of osteoarthritis.
Humans ; Finite Element Analysis ; Knee Joint/physiology* ; Tibia/anatomy & histology* ; Cartilage, Articular/physiology* ; Menisci, Tibial/physiopathology* ; Tomography, X-Ray Computed ; Osteoarthritis, Knee/diagnostic imaging* ; Weight-Bearing ; Bone Density ; Adult ; Stress, Mechanical ; Male ; Middle Aged ; Biomechanical Phenomena ; Female

Non-small cell lung cancer (NSCLC), as the predominant histological subtype of lung cancer, accounts for approximately 85% of all lung cancer cases. In recent years, immune checkpoint inhibitors (ICIs), represented by programmed death 1/programmed death ligand 1 (PD-1/PD-L1) inhibitors, have achieved breakthrough advancements in patients with driver gene-negative NSCLC. They have been established as a key component of first-line treatment regimens and have significantly improved clinical outcomes. However, limited clinical evidence has emerged showing the phenomenon of histological transformation from NSCLC to small cell lung cancer (SCLC) in patients experiencing disease progression after ICIs monotherapy or combination therapy. Systematic research data on the clinical characteristics, molecular biological basis, and subsequent treatment strategies for such transformation events are currently lacking. This article reports a case of SCLC transformation occurring in a patient with KRAS-mutated lung adenocarcinoma after 16 months of ICIs combination therapy and provides a systematic review of 22 similar published cases. The study demonstrates that small cell transformation is a critical mechanism of immunotherapy resistance, and transformed patients exhibit poor prognosis. The research emphasizes the importance of dynamic monitoring of neuron-specific enolase (NSE) and standardized repeat biopsies during treatment, providing a basis for clinical practice. This aids in enhancing the recognition and management capabilities for this rare histological transformation, ultimately improving patient outcomes.
Humans ; Immune Checkpoint Inhibitors/therapeutic use* ; Lung Neoplasms/immunology* ; Carcinoma, Non-Small-Cell Lung/immunology* ; Small Cell Lung Carcinoma/genetics* ; Male ; Middle Aged ; Female

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

The incidence of delayed chemotherapy-induced nausea and vomiting is relatively high among pediatric cancer patients. Nausea and vomiting symptoms can exacerbate physical and psychological burdens, potentially leading to aversion and reduced treatment adherence. This paper analyzes and summarizes delayed chemotherapy-induced nausea and vomiting in pediatric cancer patients, covering overview, influencing factors, assessment tools, and non-pharmacological interventions, aiming to provide insights for clinical prevention and intervention strategies targeting delayed chemotherapy-induced nausea and vomiting in pediatric patients.

Objective:To identify the relevant factors for the first-course remission of acute myeloid leukemia (AML) and to develop a predictive model as well as assess its predictive capability.Methods:Clinical data of 749 patients newly diagnosed with AML admitted to the Department of Hematology, the First Affiliated Hospital, Zhejiang University, School of Medicine from January 1, 2019, to April 30, 2023, were collected and randomly divided into training and validation sets. Multivariate logistic regression analysis was conducted to determine variables associated with complete remission in the first course of induction therapy, and a predictive model was established based on these variables. The receiver operating characteristic (ROC) curve of the predictive model was plotted, and the area under the curve (AUC) was calculated.Results:The indicators predicting the first remission course included peripheral blood white blood cell count during onset, CBF::MYH11 fusion gene, CEBPA bZIP region mutation, myelodysplastic syndrome-related gene mutation, and induction chemotherapy regimen selection as independent factors for the first remission course. The model’s area under the training and validation curves was 0.738 (95% CI: 0.696-0.780) and 0.726 (95% CI: 0.650-0.801), respectively. The Hosmer-Lemeshow test results yielded P-values of 0.993 and 0.335, respectively. Conclusion:In this study, the developed model demonstrates a strong predictive capability for the efficacy of the first course of patients with AML, providing valuable guidance to clinicians in assessing patient prognosis and selecting appropriate treatment strategies.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

Bacterial infection is a major threat to global public health,and can cause serious diseases such as bacterial skin infection and foodborne diseases.It is essential to develop a new method to rapidly di-agnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time.In this work,we developed a 4-mercaptophenylboronic acid gold nanoparticles(4-MPBA-AuNPs)-functionalized hydrogel microneedle(MPBA-H-MN)for bacteria detection in skin inter-stitial fluid.MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min.Surface enhanced Raman spectroscopy(SERS)detection was then performed and combined with ma-chine learning technology to distinguish and identify a variety of bacteria.Overall,the capture efficiency of this method exceeded 50％.In the concentration range of 1 × 10 7 to 1 × 10 10 colony-forming units/mL(CFU/mL),the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration.Using random forest(RF)-based machine learning,bacteria were effectively distinguished with an accuracy of 97.87％.In addition,the harmless disposal of used MNs by photothermal ablation was convenient,environmentally friendly,and inexpensive.This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.

Bacterial infection is a major threat to global public health, and can cause serious diseases such as bacterial skin infection and foodborne diseases. It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time. In this work, we developed a 4-mercaptophenylboronic acid gold nanoparticles (4-MPBA-AuNPs)-functionalized hydrogel microneedle (MPBA-H-MN) for bacteria detection in skin interstitial fluid. MPBA-H-MN could conveniently capture and enrich a variety of bacteria within 5 min. Surface enhanced Raman spectroscopy (SERS) detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria. Overall, the capture efficiency of this method exceeded 50%. In the concentration range of 1 × 10⁷ to 1 × 10¹⁰ colony-forming units/mL (CFU/mL), the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration. Using random forest (RF)-based machine learning, bacteria were effectively distinguished with an accuracy of 97.87%. In addition, the harmless disposal of used MNs by photothermal ablation was convenient, environmentally friendly, and inexpensive. This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.

Objective:To explore the effects of miR-125b on the proliferation, invasion and migration of pancreatic cancer cells by targeting SMYD2 signaling pathway.Methods:The expression of miRNA-125b in Aspc-1 and BxPC-3 lines of pancreatic cancer cells were detected. miRDB, ENCORI and TargetScan databases were used to predict the potential target genes of miRNA-125b. The downstream target genes of miRNA-125b were identified by qPCR assay and double luciferase reporter gene assay. Western blot analysis was performed to detect SMYD2 protein expression after transfection with miRNA-125b inhibitor. EdU staining, Annexin V-FITC/PI assay and Annexin V-FITC/PI assay were used to detect the effects of miRNA-125b inhibitor transfection and simultaneous transfection of miRNA-125b and SMYD2 inhibitor on cell proliferation, clonogenesis and apoptosis.Results:The expression level of miRNA-125b in pancreatic cancer cell lines was higher than that in normal pancreatic duct cells ( P<0.05). The downstream target gene of miRNA-125b was identified as SMYD2 by qPCR assay and double luciferase reporter gene assay. The expression of SMYD2 protein in miR-125b inhibitor group was higher than that in NC group ( P<0.01). EdU cell proliferation assay showed that the number of miRNA-125b positive cells in inhibitor group was lower than that in NC group and Inhibitor NC group ( P<0.05). The number of clones in miR-125b inhibitor+si-SMYD2 group was more than that in miR-125b inhibitor group ( P<0.01). Annexin V-FITC/PI assay showed that the apoptosis number of cell cells in miR-125b inhibitor+si-SMYD2 group was lower than that in miR-125b inhibitor group ( P<0.01) . Conclusion:miRNA-125b is highly expressed in pancreatic cancer cells, and can directly affect the expression of SMYD2 gene, thereby promoting the proliferation and inhibiting the apoptosis of pancreatic cancer cells.

The incidence of delayed chemotherapy-induced nausea and vomiting is relatively high among pediatric cancer patients. Nausea and vomiting symptoms can exacerbate physical and psychological burdens, potentially leading to aversion and reduced treatment adherence. This paper analyzes and summarizes delayed chemotherapy-induced nausea and vomiting in pediatric cancer patients, covering overview, influencing factors, assessment tools, and non-pharmacological interventions, aiming to provide insights for clinical prevention and intervention strategies targeting delayed chemotherapy-induced nausea and vomiting in pediatric patients.