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

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.

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.

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.

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.

In order to strengthen the supervision of the use of drugs in hospitals，the Sichuan Academy of Medical Sciences· Sichuan Provincial People’s Hospital took the lead in compiling the Principles for the Rational Use of National Key Monitoring Drugs （the Second Batch） with a number of experts from multiple medical units in accordance with the Second Batch of National Key Monitoring Rational Drug Use List （hereinafter referred to as “the List”） issued by the National Health Commission. According to the method of the WHO Guidelines Development Manual， the writing team used the Delphi method to unify expert opinions by reading and summarizing the domestic and foreign literature evidence of related drugs， and applied the evaluation， formulation and evaluation method of recommendation grading （GRADE） to evaluate the quality of evidence formed， focusing on more than 30 drugs in the List about the evaluation of off-label indications of drugs， key points of rational drug use and key points of pharmaceutical monitoring. It aims to promote the scientific standardization and effective management of clinical medication， further improve the quality of medical services， reduce the risk of adverse drug reactions and drug abuse， promote rational drug use， and improve public health.

ObjectiveTo investigate the identification of kidney Yang deficiency syndrome of patients with osteoporosis（OP）， and to form the clinical syndrome identification rules of traditional Chinese medicine（TCM）. MethodBasic information， etiology， clinical symptoms and other characteristics of 982 OP patients were included， and statistical tests were used to screen the variables associated with kidney Yang deficiency syndrome. Taking the decision tree as the base model， bootstrap aggregation algorithm（Bagging algorithm） was utilized to establish the classification model of kidney Yang deficiency syndrome in OP， generating numerous rules and removing redundancy. Combining least absolute shrinkage and selection operator（LASSO） regression to screen key rules and integrate them to construct an identification model， achieving the identification of kidney Yang deficiency syndrome in OP patients. ResultEighteen key identification rules were screened out， and of these， where 11 rules with regression coefficients>0 correlated positively with the kidney Yang deficiency syndrome， the rule with the highest coefficient was chilliness（present）&feverish sensation over the palm and sole（absent）. The other 7 rules with regression coefficients<0 correlated negatively with the syndrome， the rule with the lowest coefficient was reddish tongue（present）&diarrhea（absent）&deficiency of endowment（absent）. According to the regression coefficients of each key rule， variables with importance>0.2 were ranked as chilliness， reddish tongue， feverish sensation over the palm and sole， cold limbs， clear urine， diarrhea， deficiency of endowment， prolonged illness. The results of the partial dependence analysis of the identification model showed that compared to OP patients without chilliness， those with chilliness（present） had a 0.266 8 higher probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identification of the syndrome. Similarly， compared to OP patients without reddish tongue， those with reddish tongue had a 0.141 9 lower probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identifying non-kidney Yang deficiency syndrome. The accuracy， sensitivity， specificity and area under receiver operating characteristic curve（AUC） of the established kidney Yang deficiency syndrome identification model in the test set were 0.865 9， 0.853 7， 0.872 0 and 0.931 5， respectively. ConclusionA precise identification model of OP kidney Yang deficiency syndrome is conducted basing on the rule ensemble method of Bagging combining LASSO regression， and the screened key rules can explain the identification process of kidney Yang deficiency syndrome. In this research， according to the regression coefficients of rules， the importance and partial dependence of variables， combined with the thinking of TCM， the influence of patient characteristics on the identification of syndromes is described， so as to reveal the primary and secondary syndromes of identification and assist the clinical identification of kidney Yang deficiency syndrome.