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.

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.

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.

ObjectiveIn order to improve the recognition accuracy of named entities in medical record texts and realize the effective mining and utilization of medical record knowledge， a Bert-Radical-Lexicon（BRL） neural network model is constructed to recognize medical record entities with respect to the characteristics of medical record texts. MethodWe selected 408 medical records related to hypertension from the the Complete Library of Famous Medical Records of Chinese Dynasties and constructed a dataset consisting of 1 672 medical records by manually labeling. Then， we randomly divided the dataset into three subsets， including the training set（1 004 cases）， the testing set （334 cases） and the validation set（334 cases）. Based on this dataset， we built a BRL model that fused various text features of medical records， as well as its variants BRL-B， BRL-L and BRL-R， and a baseline model Base for experiments. During the model training phase， we trained the above models using the training set to reduce the risk of overfitting. We continuously monitored the performance of each model on the validation set during training and saved the model with the best performance. Finally， we evaluated the performance of these models on the testing set. ResultCompared with other models， the BRL model had the best performance in the medical records named entity recognition task， with an overall recognition precision of 90.09%， a recall of 90.61%， and the harmonic mean of the precision and recall（F1） of 90.35% for eight types of entities， including disease， symptom， tongue manifestation， pulse condition， syndrome， method of treatment， prescription and traditional Chinese medicine（TCM）. Compared with the Base model， the BRL model improved the overall F1 value of entity recognition by 5.22%， and the F1 value of pulse condition entity increased by 6.92%， which was the largest increase. ConclusionBy incorporating a variety of medical record text features in the embedding layer， the BRL neural network model has stronger named entity recognition ability， and thus extracts more accurate and reliable TCM clinical information.

ObjectiveTo investigate the trends and significant determinants of delayed HIV diagnosis （DHD） among newly reported HIV/AIDS cases in Xuhui District， Shanghai between 2018 and 2022. MethodsIn the newly reported HIV/AIDS cases， patients died within one year without accident， HIV/AIDS cases with CD₄ cell count <200 cells·μL^-1， and AIDS cases with a CD₄ cell count between 200 to 499 cells·μL^-1 were defined as delayed diagnosis. Univariate and multivariate logistic analysis were employed to explore the influencing factors of DHD. ResultsAmong the 862 newly reported HIV/AIDS cases， The DHD rate was 39.79% without statistically significant difference by year（χ²=4.508， P=0.342）. Patients with CD₄ cell count <200 cells·μL^-1 contributed the largest proportion of DHD. During 2018‒2022， the DHD rate declined among HIV/AIDS patients who were younger than 35 years old or 45‒65 years old， never married， original diagnosis from tertiary specialized hospitals. Patients who were 65 years or older， married or divorced， with heterosexual transmitted HIV/AIDS， and original diagnosis from other types of testing and tertiary metropolitan hospital， had sustainably higher DHD rates. The number of HIV screening and diagnosed from voluntary counseling and testing （VCT） decreased during the COVID-19 epidemic， while the DHD rate increased sharply. Multivariate logistic regression analysis suggested the DHD rates were higher among older age， other types of testing（OR=3.805， 95%CI： 2.260‒6.406）and pre-operative testing（OR=2.411， 95%CI： 1.424‒4.081）. Patients who received CD₄ test in 15 days had a higher DHD rate compared to the cases received CD₄ test exceeding 90 days （OR=0.336， 95%CI： 0.216‒0.522）. ConclusionThere is no significant decrease of delayed HIV diagnosis rate in Xuhui District in recent years， and the number of HIV tests has decreased in 2022. Monitoring of newly reported HIV/AIDS should be conducted continuously. Expansion of HIV antibody screening should be conducted in non-infectious departments and inpatient departments in healthcare institutions， particularly metropolitan hospitals. Assistance should be provided to clinicians and elderly patients for improving their ability to recognize and perceive the risk of HIV/AIDS， in order to enhance early diagnosis and subsequent treatment.

BACKGROUND:Photothermal therapy is a novel tumor treatment strategy that uses photothermal agents to transform light energy into heat energy to accomplish non-invasive tumor ablation.The rise of photothermal therapy and nanotechnology has provided a new perspective on breast cancer treatment.OBJECTIVE:To prepare a new type of near-infrared biomimetic nanoprobe that has been modified by breast cancer cell membrane,to investigate the effect of near-infrared fluorescence/ultrasound imaging in vitro,and to observe its targeting ability and photothermal therapy effect on homologous tumor cells in vitro.METHODS:Organic small molecule ITIC-4CI with A-D-A structure was used as photothermal agents;polylactic acid/glycolic acid copolymer as nanocarrier;4T1 cell membrane of mouse breast cancer cells as a surface modifier of nanoparticles;perfluorohexane(PFH)was loaded.A novel near-infrared biomimetic nanoprobe(4T1m/ITIC-4CI/PFH)was prepared by the double emulsion evaporation method and sonication method.The basic characterization of the nanoprobe and the homologous targeting ability were detected.The photothermal properties and photothermal stability of the probe were investigated,and the near-infrared fluorescence/ultrasound imaging effect of the probe under laser irradiation was observed.The CCK-8 assay and calcein/propidium iodide staining were used to assess the efficacy of photothermal therapy.RESULTS AND CONCLUSION:(1)The prepared 4T1m/ITIC-4CI/PFH nanoprobes had uniform size,high stability,and an average particle size of(92.7±2.3)nm.The probe's protein composition was identical to that of the 4T1 cell membrane.The nanoprobe's ability to target homologous 4T1 cells was validated by an in vitro cell uptake assay.(2)The nanoprobe had a red-shift absorption spectrum and tail emission extending to the near-infrared-Ⅱ,which emitted a bright near-infrared-Ⅱ fluorescence signal under laser irradiation.(3)After laser irradiation,the nanoprobe 4T1m/ITIC-4CI/PFH could be turned into microbubbles and enhanced ultrasound imaging.The results of CCK-8 assay and calcein/propidium iodide staining showed that the nanoprobe 4T1m/ITIC-4CI/PFH had an obvious photothermal killing effect on 4T1 cells.(4)The results show that the nanoprobe 4T1m/ITIC-4CI/PFH has the ability to target homologous tumors and enhance near-infrared-Ⅱ fluorescence imaging/ultrasound imaging and photothermal therapy effects.

L-asparaginase (L-ASN) is widely applied in the treatment of malignant tumor and low-acrylamide food production, however, the low expression level hampers its application. Heterologous expression is an effective strategy to increase the expression level of target enzymes, and Bacillus is generally used as the host for efficient production of enzymes. In this study, the expression level of L-asparaginase in Bacillus was enhanced through optimization of expression element and host. Firstly, five signal peptides (SP_SacC, SP_AmyL, SP_AprE, SP_YwbN and SP_WapA) were screened, among which SP_SacC showed the best performance, reaching an activity of 157.61 U/mL. Subsequently, four strong promoters (P43, P_ykzA-P43, P_Ubay and P_bacA) from Bacillus were screened, and tandem promoter P_ykzA-P43 showed the highest yield of L-asparaginase, which was 52.94% higher than that of control strain. Finally, three Bacillus expression hosts (B. licheniformis Δ0F3 and BL10, B. subtilis WB800) were investigated, and the maximum L-asparaginase activity, 438.3 U/mL, was reached by B. licheniformis BL10, which was an 81.83% increase compared with that of the control. This is also the highest level of L-asparaginase in shake flask reported to date. Taken together, this study constructed a B. licheniformis strain BL10/P_ykzA-P43-SP_SacC-ansZ capable of efficiently producing L-asparaginase, which laid the foundation for industrial production of L-asparaginase.
Bacillus licheniformis/metabolism* ; Asparaginase/genetics* ; Bacillus/genetics* ; Protein Sorting Signals ; Promoter Regions, Genetic/genetics* ; Bacillus subtilis/genetics* ; Bacterial Proteins

Objective:To study the phenotype and genotype distribution of Yersinia pestis ( Y. pestis) in different natural foci of plague in China, so as to provide scientific basis for plague prevention and control. Methods:A total of 2 184 strains of Y. pestis isolated from different time periods, regions, hosts and vectors in 11 plague natural foci of China since 1943 were selected for biochemical type identification, glycolysis test, virulence factor test [capsule antigen (F1), pesticin Ⅰ (Pst Ⅰ), virulence antigen factor (VWa), pigmentation factor (Pgm)], different region (DFR) typing and clustered regularly interspaced short palindromic repeats (CRISPR) typing. Results:There were 16 biochemical types of Y. pestis in the natural foci of plague in China, and each biochemical type showed obvious regional distribution in each foci. Most strains were positive for ass hide glue glycolysis (89.79%, 1 961/2 184), maltose (80.13%, 1 750/2 184), glycerol (94.23%, 2 058/2 184), and denitrification (82.78%, 1 808/2 184), and negative for rhamnose (88.78%, 1 939/2 184) and melibiose (85.62%, 1 870/2 184). Virulence factor test results showed that 99.95% (2 183/2 184) of Y. pestis were F1 positive; 99.73% (2 178/2 184) of Y. pestis can produce Pst Ⅰ; 73.31% (1 601/2 184) of Y. pestis were VWa positive and 26.69% (583/2 184) were VWa negative; Pgm positive strains accounted for 72.62% (1 586/2 184), Pgm negative strains accounted for 21.52% (470/2 184), and Pgm mixed type strains accounted for 5.86% (128/2 184). According to DFR typing results, there were 52 genotypes in 2 184 strains of Y. pestis, of which 19 were major genotypes and 33 were minor genotypes. CRISPR typing revealed 16 major genotypes, of which 7 were newly discovered. Conclusion:The phenotypes and genotypes of Y. pestis in various natural foci of plague in China are diverse and have geographical distribution characteristics.