Diabetes mellitus, characterized by glucose metabolism disorders and marked by insulin deficiency or insulin resistance, has seen a continuous rise in prevalence. In recent years, islet transplantation has matured as a therapeutic approach for diabetes, becoming an important method for glycemic control and the reduction of diabetes-related complications. Donor selection directly influences transplant outcomes, and various research institutions worldwide have proposed multiple scoring systems to optimize donor assessment, such as the University of Alberta scoring system and the North American Islet Donor Score. This article explores the impact of key factors such as donor age, body mass index and ischemia time on islet transplantation. Combining practical experience in pancreatic donor selection from Shanghai Changzheng Hospital, it proposes screening criteria for pancreatic donors suitable for China, aiming to provide new evidence for improving the success rate of islet transplantation.

ObjectiveTo investigate whether Huanglian Jiedutang （HLJD） and its major active constituents （geniposide， baicalin， and berberine） can inhibit the inflammatory response of BV2 cells under lipopolysaccharide （LPS） stimulation via the high-mobility group protein B1 （HMGB1）/Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB） signaling pathway， and to explore differences in therapeutic efficacy among the three monomers， their combined formula， and HLJD under equal content ratios. MethodsBV2 microglial cells were used as the primary experimental model. Cell viability was assessed using the cell counting kit-8 （CCK-8） method to examine the effects of different concentrations of dimethyl sulfoxide （DMSO， 0.8%， 0.4%， 0.2%， 0.1%， and 0.05%） on cell viability. IncuCyte was employed to monitor the growth of cells under different concentrations of HLJD （200， 100， 50， 25， 12.5， 6.25 mg·L^-1）. Nitric oxide （NO） assay was used to screen the optimal HLJD concentration. High-performance liquid chromatography （HPLC） determined the content of geniposide， baicalin， and berberine in HLJD， and experimental groups were subsequently established according to the relative proportions of these constituents. CCK-8 assay evaluated cell viability under different treatments. Enzyme-linked immunosorbent assay （ELISA） measured levels of inflammatory factors （TNF-α， IL-1β， IL-6， IL-10） in the supernatant. Flow cytometry assessed the effects of treatments on M1-type polarization of BV2 cells. Western blot determined the expression levels of HMGB1， TLR4， and NF-κB-related proteins. ResultsCompared with the blank group， DMSO at concentrations ≤0.2% did not affect cell viability within 48 h. BV2 cell growth plateaued at 24 h after treatment with 200 mg·L^-1 HLJD. Under stimulation with 2 mg·L^-1 LPS， this concentration of HLJD effectively reduced NO release， and 6 h pre-treatment had a stronger inhibitory effect on NO than direct administration. HPLC results showed that 1 mg of HLJD freeze-dried powder contained approximately 24 μg of geniposide， 15 μg of baicalin， and 30 μg of berberine. Based on these ratios， experimental groups were blank， LPS （2 mg·L^-1）， HLJD （200 mg·L^-1）， monomer combination， geniposide （4.8 mg·L^-1）， baicalin （3 mg·L^-1）， and berberine （6 mg·L^-1）. The monomer combination group consisted of all three active constituents dissolved together. LPS and HLJD or its active constituents did not affect cell viability compared with the blank group. LPS significantly increased TNF-α， IL-1β， IL-6， and IL-10 in the supernatant （P<0.01）. HLJD and its active constituents significantly reduced pro-inflammatory factors TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01） while upregulating anti-inflammatory IL-10 （P<0.01）， with the monomer combination showing the strongest effect （P<0.05， P<0.01）. Compared with the blank group， LPS significantly increased the proportion of CD80⁺CD86⁺ （M1-type） BV2 cells （P<0.01）. HLJD and its constituents partially inhibited M1 polarization （P<0.05， P<0.01）， with the monomer combination exhibiting the most pronounced effect （P<0.05， P<0.01）. Compared with the blank group， LPS upregulated HMGB1， TLR4， and NF-κB-related proteins （P<0.01）， whereas HLJD and its active constituents significantly reduced their expression （P<0.05， P<0.01）， with the monomer combination having the strongest regulatory effect （P<0.05， P<0.01）. ConclusionHLJD and its major active constituents （geniposide， baicalin， berberine） can inhibit LPS-induced inflammatory responses in BV2 cells. The combination of the three active constituents demonstrates the most potent anti-inflammatory effect， significantly attenuating M1-type polarization of BV2 cells via the HMGB1/TLR4/NF-κB signaling pathway.

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.

Astragalus membranaceus possesses the function of enhancing immunity, protecting the liver, diuretic, anti-aging, anti-stress, anti-hypertensive, and more extensive antibacterial effects. Polysaccharides, one kind of the major active ingredients of A. membranaceus, are considered to be responsible for their versatile use. Now, a systematic summary of research progress and prospects of polysaccharides from A. membranaceus polysaccharides (AMPs) is necessary to facilitate their further study and application. In this review, the optimal extraction methods, structural features, biological activities, and applications of AMPs were emphasized. The structure-activity relationships are also analyzed and elucidated. Solvent, ultrasonic, microwave, enzyme-assisted, ultra-high pressure, and combined methods have been used to extract AMPs. Among them, solvent extraction is the most commonly used method because it is simple and easy to operate, but the efficiency needs to be improved further. The ultra-high pressure method is the most efficient but has a low economic return. AMPs exhibited various bioactivities, including immunomodulation, antitumor, and antidiabete. The structure-activity relationships revealed that different structure configurations, chain conformations, and physical properties would have different bioactivities. However, the new method for purification of certain polysaccharides, detailed structure-activity relationships (SAR), mechanisms of bioactivities, and quality control of AMPs need to be extensively investigated.

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.

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As the important source of bone cells, osteoblasts are involved in bone formation and repair, and play a key role in maintaining bone balance. If the osteogenic differentiation process in vivo is disrupted, a variety of bone-related diseases may occur. Natural products, which have a wide range of sources, a wide variety of physiological activities, and few toxic side-effects, have been found in recent years to be able to regulate osteoblast differentiation. Based on the sources of natural products, this paper reviews the intervention of natural products from plant, animal and microbial sources on osteogenic differentiation, aiming to provide a theoretical basis for natural products in the treatment of bone diseases.