The efficacy and safety of short-term and low-dose IL-2 combined with tocilizumab to treat rheumatoid arthritis.

Background: Immunotherapy targeting factors related to immune imbalance has been widely employed for RA treatment. This study aimed to evaluate the efficacy and safety of low-dose interleukin (IL)-2 combined with tocilizumab (TCZ), a biologics targeting IL-6, in RA patients. Methods: Fifty adults with active RA who met the criteria with complete clinical data were recruited, and divided into three groups: control group (n=15), IL-2 group (n=26), and IL-2+TCZ group (n=9). In addition to basic treatment, participants in the IL-2 group received IL-2 (0.5 MIU/day), while participants in the IL-2+TCZ group received IL-2 (0.5 MIU/day) along with one dose of TCZ (8 mg/kg, maximum dose: 800 mg). All subjects underwent condition assessment, laboratory indicators and safety indicators detection, and records before treatment and one week after treatment. Results: Compared with the baseline, all three groups showed significant improvement in disease conditions, as evidenced by significantly reduced disease activity indicators. The low-dose IL-2 and combination treatment groups demonstrated a violent proliferation of Tregs, while the absolute number of Th1, Th2, and Th17 cells in the latter group showed a decreasing trend. The decrease in the Th17/Treg ratio was more pronounced in the IL-2+TCZ groups. No significant adverse reactions were observed in any of the patients. Conclusion: Exogenous low doses of IL-2 combined TCZ were found to be safe and effective in reducing effector T cells and appropriately increasing Treg levels in RA patients with high effector T cell levels. This approach helps regulate immune homeostasis and contributes to the prevention of disease deterioration. Clinical trial registration: https://www.chictr.org.cn/showprojEN.html?proj=13909, identifier ChiCTR-INR-16009546.

Nondestructive testing of runny salted egg yolk based on improved ConvNeXt-T.

Salted egg yolks from salted duck eggs are widely utilized in the domestic and international food industry as both raw materials and ingredients. When salted egg yolks are not fully cured and matured, they exist in a fluid state, with a mixture of solid and liquid internally. Due to this composition, they are susceptible to deterioration during storage and usage, necessitating their detection and classification. In this study, a dataset specifically for salted egg yolks was established, and the ConvNeXt-T model, employed as the benchmark model, underwent two notable improvements. First, a lightweight location-aware circular convolution (ParC) was introduced, utilizing a ParC-block to replace a portion of the original ConvNeXt-T block. This enhancement aimed to overcome the limitations of convolution in extracting global feature information while integrating the global sensing capability of vision transformer and the localization capability of convolution. Additionally, the activation function was modified through substitution. These improvements resulted in the final model. Experimental results indicate that the enhanced model exhibits faster convergence on the custom salted egg yolk dataset compared to the baseline model. Furthermore, a significant reduction of model parameters by a factor of 4 led to a 2.167 percentage point improvement in the accuracy of the test set. The ParC-ConvNeXt-SMU-T model achieved an accuracy of 96.833% with 26.8 million parameters. Notably, the improved model demonstrates exceptional effectiveness in recognizing salted egg yolks. PRACTICAL APPLICATION: This study can be widely applied in the process of salted egg yolk production and quality inspection, which can improve the actual sorting efficiency of salted egg yolks and reduce the labor cost at the same time. It can also be used for nondestructive testing of salted egg yolks by governmental enterprises and other regulatory authorities.

Evaluation of toothpastes for treating root carious lesions - a laboratory-based pilot study.

BACKGROUND: Root caries is preventable and can be arrested at any stage of disease development. The aim of this study was to investigate the potential mineral exchange and fluorapatite formation within artificial root carious lesions (ARCLs) using different toothpastes containing 5,000 ppm F, 1,450 ppm F or bioactive glass (BG) with 540 ppm F. MATERIALS AND METHODS: The crowns of each extracted sound tooth were removed. The remaining roots were divided into four parts (n = 12). Each sample was randomly allocated into one of four groups: Group 1 (Deionised water); Group 2 (BG with 540 ppm F); Group 3 (1,450 ppm F) and Group 4 (5,000 ppm F). ARCLs were developed using demineralisation solution (pH 4.8). The samples were then pH-cycled in 13 days using demineralisation solution (6 h) and remineralisation solution (pH 7) (16 h). Standard tooth brushing was carried out twice a day with the assigned toothpaste. X-ray Microtomography (XMT) was performed for each sample at baseline, following ARCL formation and after 13-day pH-cycling. Scanning Electron Microscope (SEM) and 19F Magic angle spinning nuclear magnetic resonance (19F-MAS-NMR) were also performed. RESULTS: XMT results showed that the highest mineral content increase (mean ± SD) was Group 4 (0.09 ± 0.05), whilst the mineral content decreased in Group 1 (-0.08 ± 0.06) after 13-day pH-cycling, however there was evidence of mineral loss within the subsurface for Groups 1, 3 and 4 (p < 0.05). SEM scans showed that mineral contents within the surface of dentine tubules were high in comparison to the subsurface in all toothpaste groups. There was evidence of dentine tubules being either partially or completely occluded in toothpaste groups. 19F-MAS-NMR showed peaks between - 103 and - 104ppm corresponding to fluorapatite formation in Groups 3 and 4. CONCLUSION: Within the limitation of this laboratory-based study, all toothpastes were potentially effective to increase the mineral density of artificial root caries on the surface, however there was evidence of mineral loss within the subsurface for Groups 1, 3 and 4.

3DCellComposer - A Versatile Pipeline Utilizing 2D Cell Segmentation Methods for 3D Cell Segmentation.

Background: Cell segmentation is crucial in bioimage informatics, as its accuracy directly impacts conclusions drawn from cellular analyses. While many approaches to 2D cell segmentation have been described, 3D cell segmentation has received much less attention. 3D segmentation faces significant challenges, including limited training data availability due to the difficulty of the task for human annotators, and inherent three-dimensional complexity. As a result, existing 3D cell segmentation methods often lack broad applicability across different imaging modalities. Results: To address this, we developed a generalizable approach for using 2D cell segmentation methods to produce accurate 3D cell segmentations. We implemented this approach in 3DCellComposer, a versatile, open-source package that allows users to choose any existing 2D segmentation model appropriate for their tissue or cell type(s) without requiring any additional training. Importantly, we have enhanced our open source CellSegmentationEvaluator quality evaluation tool to support 3D images. It provides metrics that allow selection of the best approach for a given imaging source and modality, without the need for human annotations to assess performance. Using these metrics, we demonstrated that our approach produced high-quality 3D segmentations of tissue images, and that it could outperform an existing 3D segmentation method on the cell culture images with which it was trained. Conclusions: 3DCellComposer, when paired with well-trained 2D segmentation models, provides an important alternative to acquiring human-annotated 3D images for new sample types or imaging modalities and then training 3D segmentation models using them. It is expected to be of significant value for large scale projects such as the Human BioMolecular Atlas Program.

Quantitative Pattern of hPTMs by Mass Spectrometry-Based Proteomics with Implications for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is known for its aggressive nature, and TNBC management is currently challenging due to the lack of effective targets. Despite the importance of histone post-translational modifications (hPTMs) in breast cancer, their associations with molecular subtypes of breast cancer, especially TNBC, are poorly understood. In this study, a combination of untargeted and targeted proteomics approaches, supplemented by a derivatization method, was applied to breast cancer cells and tissue samples. Untargeted proteomics of eight breast cancer cell lines belonging to different molecular subtypes revealed 36 modified peptides with 12 lysine modification sites in histone H3, and the most frequently reported top 5 histone H3 methylation and acetylation sites were covered. Then, targeted proteomics was carried out to quantify the total 20 target hPTMs at the covered modification sites (i.e., mono-, di-, trimethylation, and acetylation for each site), indicating the difficulty in distinguishing TNBC cells from normal cells. Subsequently, the analysis in TNBC patients revealed significant expression differences in 4 specific hPTMs (H3K14ac, H3K27me1, H3K36me2, and H3K36me3) between TNBC and adjacent normal tissue samples. These unique hPTM patterns allowed for the differentiation of TNBC from normal cases. This finding provides promising implications for advancing targeted treatment strategies for TNBC in the future.

Disinfection byproducts and their cytotoxicity contribution from dissolved black carbon in source water during chlor(am)ination.

Dissolved black carbon (DBC), the soluble component of black carbon, which mainly comes from the incomplete combustion of fossil fuels or biomass, is widely spread in source water and significantly contributes to the formation of dissolved organic matter (DOM). However, the origin of DBC in different types of source water in China has not been well studied, as well as its subsequent transformation and toxicity contribution during disinfection of source water DOM by chlor(am)ine. In this study, DBC from 17 different source water in East China at different seasons was collected. The δ13C compositions indicated that straw burning was the main origin of DBC in source water. After simulated chlor(am)ination of DBC, 5 categories of aliphatic disinfection byproducts (DBPs) including trihalomethanes, haloacetic acids, haloacetonitriles, haloketones, halonitromethanes and 6 categories of aromatic DBPs including halophenols, halonitrophenols, halohydroxybenzaldehyde, halohydroxybenzoic acid, halobenzoquinones and haloaniline were detected. Compared with chlorination of DBC, higher levels of nitrogenous DBPs and aromatic DBPs were generated during chloramination. Detected DBPs accounted for 42 % of total organic halogen. What's more, Chinese hamster ovary cells cytotoxicity tests showed that the cytotoxicity of DBPs formed by chlor(am)ination of DBC was 4 times higher than that by chlor(am)ination of DOM. Haloacetonitriles contributed to the highest cytotoxicity in the chloramination of DBC, and haloacetic acids contributed to the highest cytotoxicity in chlorination. 67 % of the total cytotoxicity attributed to the undetected DBPs. As a result, DBPs generated from DBC contributed to 11.7 % of the total cytotoxicity in the chlor(am)ination of the source water DOM although DBC only took up 2 % of DOC in the source water. Results obtained from this study systematically revealed the DBPs formation from DBC and their potential cytotoxicity contribution in the chlor(am)ination of source water DOM, which should not be ignored in drinking water treatment.

A Non-Destructive Detection and Grading Method of the Internal Quality of Preserved Eggs Based on an Improved ConvNext.

As a traditional delicacy in China, preserved eggs inevitably experience instances of substandard quality during the production process. Chinese preserved egg production facilities can only rely on experienced workers to select the preserved eggs. However, the manual selection of preserved eggs presents challenges such as a low efficiency, subjective judgments, high costs, and hindered industrial production processes. In response to these challenges, this study procured the transmitted imagery of preserved eggs and refined the ConvNeXt network across four pivotal dimensions: the dimensionality reduction of model feature maps, the integration of multi-scale feature fusion (MSFF), the incorporation of a global attention mechanism (GAM) module, and the amalgamation of the cross-entropy loss function with focal loss. The resultant refined model, ConvNeXt_PEgg, attained proficiency in classifying and grading preserved eggs. Notably, the improved model achieved a classification accuracy of 92.6% across the five categories of preserved eggs, with a grading accuracy of 95.9% spanning three levels. Moreover, in contrast to its predecessor, the refined model witnessed a 24.5% reduction in the parameter volume, alongside a 3.2 percentage point augmentation in the classification accuracy and a 2.8 percentage point boost in the grading accuracy. Through meticulous comparative analysis, each enhancement exhibited varying degrees of performance elevation. Evidently, the refined model outshone a plethora of classical models, underscoring its efficacy in discerning the internal quality of preserved eggs. With its potential for real-world implementation, this technology portends to heighten the economic viability of manufacturing facilities.

Bimetallic H2 Addition and Intramolecular Caryl-H Activation Mediated by an Iron-Zinc Hydride.

Heteronuclear Fe(µ-H)Zn hydride Cp*Fe(1,2-Cy2PC6H4)HZnEt (3) undergoes reversible intramolecular Caryl-H reductive elimination through coupling of the cyclometalated phosphinoaryl ligand and the hydride, giving rise to a formal Fe(0)-Zn(II) species. Addition of CO intercepts this equilibrium, affording Cp*(Cy2PPh)(CO)Fe-ZnEt that features a dative Fe-Zn bond. Significantly, this system achieves bimetallic H2 addition, as demonstrated by the transformation of the monohydride Fe(µ-H)Zn to a deuterated dihydride Fe-(µ-D)2-Zn upon reaction with D2.

Advances in metabolic reprogramming of NK cells in the tumor microenvironment on the impact of NK therapy.

Natural killer (NK) cells are unique from other immune cells in that they can rapidly kill multiple neighboring cells without the need for antigenic pre-sensitization once the cells display surface markers associated with oncogenic transformation. Given the dynamic role of NK cells in tumor surveillance, NK cell-based immunotherapy is rapidly becoming a "new force" in tumor immunotherapy. However, challenges remain in the use of NK cell immunotherapy in the treatment of solid tumors. Many metabolic features of the tumor microenvironment (TME) of solid tumors, including oxygen and nutrient (e.g., glucose, amino acids) deprivation, accumulation of specific metabolites (e.g., lactate, adenosine), and limited availability of signaling molecules that allow for metabolic reorganization, multifactorial shaping of the immune-suppressing TME impairs tumor-infiltrating NK cell function. This becomes a key barrier limiting the success of NK cell immunotherapy in solid tumors. Restoration of endogenous NK cells in the TME or overt transfer of functionally improved NK cells holds great promise in cancer therapy. In this paper, we summarize the metabolic biology of NK cells, discuss the effects of TME on NK cell metabolism and effector functions, and review emerging strategies for targeting metabolism-improved NK cell immunotherapy in the TME to circumvent these barriers to achieve superior efficacy of NK cell immunotherapy.

Preparation and thermal responsiveness of microencapsulated fluorinated liquids for automatic fire extinguishing.

Most early-stage fires originating in small confined spaces may not be effectively mitigated by automatic fire-extinguishing systems. Leveraging the unique controlled release capability and barrier properties of microcapsules presents a promising avenue for developing multifunctional and intelligent fire-extinguishing agents tailored for early-stage fire suppression. This paper introduces two types of microcapsules that integrate automatic detection and fire extinguishing functions, utilizing fluorinated liquids specifically perfluoro(2-methyl-3-pentanone) and 1,1,1,2,2,3,4,5,5,5 decafluoro-3-methoxy-4(trifluoromethyl)-pentane as core materials. The preparation process was optimized, and the thermal response of the microcapsules was evaluated by directly incorporating them into combustible materials. The results indicated a correlation between the preparation method, coating efficiency, and thermal stability of microcapsules with the core-wall materials. When the fluoride solution in the core material reaches the thermal response threshold temperature, the gas pressure generated during vaporization and phase change can break through the shell, enabling early active fire protection. Beyond a specific threshold of additive microcapsules in the material, the material exhibits self-extinguishing potential during combustion. In cases where the additive amount falls short of achieving self-extinguishing, the fire-resistant performance of materials can be enhanced through various measures. For instance, reducing the amount of fire-extinguishing agents, delaying the ignition time of fuel, and lowering the heat release rate during combustion are effective strategies. Moreover, the degree of improvement is related to the additional amount and the type of core-wall materials. The thermal-response mechanism of microcapsules constitutes a comprehensive mechanism with physical and chemical effects. The finding of this research offer a new technical approach for microencapsulating high-boiling-point gas extinguishing agents, facilitating intelligent and precise prevention of early fires resulting from combustible materials.

Photo-Switchable Peroxidase/Catalase-Like Activity of Carbon Quantum Dots.

Nanozymes possess multi-enzyme activities over the natural enzymes, which produce multi-pathway synergistic effects for varies of biomedical applications. Unfortunately, their multi-enzyme activities are in fighting, significantly reducing the synergistic effects. Dynamic regulation of their multi-enzyme activities is the bottleneck for intelligent therapies. Herein, we construct a novel oxygen-nitrogen functionalized carbon quantum dots (O/N-CQDs) with peroxidase-like (Reactive oxygen species (ROS) producer) activity. Interestingly, the peroxidase-like activity can be reversibly converted to catalase-like (ROS scavenger) activity under visible light irradiation. It is found that both the peroxidase/catalase-like activity of O/N-CQDs can be precisely manipulated by the light intensity. The mechanism of switchable enzyme activities is attributed to the polarization of quinoid nitrogen in polyaniline (PANI) precursor retained on O/N-CQDs under visible light, which consumes the ROS to produce O2 and H2O. As a proof-of-concept demonstration, we are able to non-intrusively up and down regulate the ROS level in cells successfully by simply switching off and on the light respectively, potentially facilitating the precise medicine based on the development of the disease. Indeed, the photo-switchable peroxidase/catalase-like activity of O/N-CQDs opens a non-invasive strategy for better manipulations of the multi-activity of nanozymes, promising their wider and more intelligent biomedical applications.

Portable, intelligent MIECL sensing platform for ciprofloxacin detection using a fast convolutional neural networks-assisted Tb@Lu2O3 nanoemitter.

Environmental pollution caused by ciprofloxacin is a major problem of global public health. A machine learning-assisted portable smartphone-based visualized molecularly imprinted electrochemiluminescence (MIECL) sensor was developed for the highly selective and sensitive detection of ciprofloxacin (CFX) in food. To boost the efficiency of electrochemiluminescence (ECL), oxygen vacancies (OVs) enrichment was introduced into the flower-like Tb@Lu2O3 nanoemitter. With the specific recognition reaction between MIP as capture probes and CFX as detection target, the ECL signal significantly decreased. According to, CFX analysis was determined by traditional ECL analyzer detector in the concentration range from 5 × 10-4 to 5 × 102 µmol L-1 with the detection limit (LOD) of 0.095 nmol L-1 (S/N = 3). Analysis of luminescence images using fast electrochemiluminescence judgment network (FEJ-Net) models, achieving portable and intelligent quick analysis of CFX. The proposed MIECL sensor was used for CFX analysis in real meat samples and satisfactory results, as well as efficient selectivity and good stability.

Prognostic factors of fungal infection in anti-melanoma differentiation-associated gene 5 antibody-positive associated interstitial lung disease.

OBJECTIVE: To investigate the potential risk factors for mortality in fungal infection in anti-melanoma differentiation-associated gene 5 antibody-positive associated interstitial lung disease (MDA5-ILD). METHODS: Patients diagnosed with MDA5-ILD from April 2017 to November 2022 were included. The demographic data, laboratory examinations, therapeutic and follow-up information were recorded. Fungal infection diagnosis was established based on a combinations of host factors, clinical features and mycologic evidences. High-dose corticosteroid therapy was defined as the initial corticosteroid doses > 240mg/d. The primary endpoint was mortality. Potential factors for fungal infection occurrence and prognostic factors were analyzed using logistic regression analysis and Cox proportional hazards regression. RESULTS: In total, 121 patients with MDA5-ILD were included. During follow-up, 41 (33.9%) patients had suffered fungal infection and 39.0% (16/41) of whom had ever received high-dose corticosteroid therapy. The median interval from corticosteroid use to the occurrence of fungal infection was 29 (10-48) days. The mean survival time of patients with fungal infection was 234.32 ± 464.76 days. The mortality in MDA5-ILD with fungal infection was 85.4% (35/41), which was significantly higher than those without (85.4% VS 56.3%, P < 0.001). High-dose corticosteroid therapy (P = 0.049) was independent risk factor for fungal infection occurrence. Decreased serum albumin level (P = 0.024) and high-dose corticosteroid therapy (P = 0.008) were both associated with increased mortality in MDA5-ILD patients with fungal infection. CONCLUSION: Fungal infection is associated with an increased mortality in MDA5-ILD. The serum albumin level and corticosteroid dose should be taken into consideration when treating MDA5-ILD. Key Points • This study showed fungal infection is associated with an increased mortality in MDA5-ILD. In MDA5-ILD patients with fungal infection, the presence of decreased serum albumin level and high-dose corticosteroid therapy were identified as predictors for mortality.

Causal Relationship between Parkinson's Disease with Heart and Vascular Disease: A Two-Sample Mendelian Randomization Study.

INTRODUCTION: The aim of this study was to investigate the causal relationship between Parkinson's disease (PD) and myocardial infarction (MI), atrial fibrillation and flutter (AF), and venous thromboembolism (VTE) by Mendelian randomization (MR) analysis. METHODS: By using data from publicly available genome-wide association studies from databases, single nucleotide polymorphisms were screened as instrumental variables, and the MR analysis was finished by inverse-variance weighted (IVW), MR-egger, weighted median methods. RESULTS: The primary IVW method showed a negative association between genetically predicted PD and risk of MI (OR = 0.9989; 95% CI: 0.9980-0.9998; p = 0.02). However, PD was not significantly associated with AF or VTE. CONCLUSION: This study suggests a negative association between PD with MI, which implies that PD has a protective effect on MI.

Fabrication of levofloxacin-loaded porcine acellular dermal matrix hydrogel and functional assessment in urinary tract infection.

Bacterial cystitis, a commonly occurring urinary tract infection (UTI), is renowned for its extensive prevalence and tendency to recur. Despite the extensive utilization of levofloxacin as a conventional therapeutic approach for bacterial cystitis, its effectiveness is impeded by adverse toxic effects, drug resistance concerns, and its influence on the gut microbiota. This study introduces Lev@PADM, a hydrogel with antibacterial properties that demonstrates efficacy in the treatment of bacterial cystitis. Lev@PADM is produced by combining levofloxacin with decellularized porcine acellular dermal matrix hydrogel and exhibits remarkable biocompatibility. Lev@PADM demonstrates excellent stability as a hydrogel at body temperature, enabling direct administration to the site of infection through intravesical injection. This localized delivery route circumvents the systemic circulation of levofloxacin, resulting in a swift and substantial elevation of the antimicrobial agent's concentration specifically at the site of infection. The in vivo experimental findings provide evidence that Lev@PADM effectively prolongs the duration of levofloxacin's action, impedes the retention and invasion of E.coli in the urinary tract, diminishes the infiltration of innate immune cells into infected tissues, and simultaneously preserves the composition of the intestinal microbiota. These results indicate that, in comparison to the exclusive administration of levofloxacin, Lev@PADM offers notable benefits in terms of preserving the integrity of the bladder epithelial barrier and suppressing the recurrence of urinary tract infections.

Boric acid templating synthesis of highly-dense yet ultramicroporous carbons for compact capacitive energy storage.

Carbon-based supercapacitors have shown great promise for miniaturized electronics and electric vehicles, but are usually limited by their low volumetric performance, which is largely due to the inefficient utilization of carbon pores in charge storage. Herein, we develop a reliable and scalable boric acid templating technique to prepare boron and oxygen co-modified highly-dense yet ultramicroporous carbons (BUMCs). The carbons are featured with high density (up to 1.62 g cm-3), large specific surface area (up to 1050 m2 g-1), narrow pore distribution (0.4-0.6 nm) and exquisite pore surface functionalities (mainly -BC2O, -BCO2, and -COH groups). Consequently, the carbons show exceptionally compact capacitive energy storage. The optimal BUMC-0.5 delivers an outstanding volumetric capacitance of 431 F cm-3 and a high-rate capability in 1 M H2SO4. In particular, an ever-reported high volumetric energy density of 32.6 Wh L-1 can be harvested in an aqueous symmetric supercapacitor. Our results demonstrate that the -BC2O and -BCO2 groups on the ultramicropore walls can facilitate the internal SO42- ion transport, thus leading to an unprecedented high utilization efficiency of ultramicropores for charge storage. This work provides a new paradigm for construction and utilization of dense and ultramicroporous carbons for compact energy storage.

Multidimensional Transcriptomics Unveils RNF34 as a Prognostic Biomarker and Potential Indicator of Chemotherapy Sensitivity in Wilms' Tumour.

Nephroblastoma, colloquially known as Wilms' tumour (WT), is the predominant malignant renal neoplasm arising in the paediatric population. Modern therapeutic approaches for WT incorporate a synergistic combination of surgical intervention, radiotherapy, and chemotherapy, which substantially ameliorate the overall patient survival rate. Despite this, the optimal sequence of chemotherapy and surgical intervention remains a matter of contention, with each strategy presenting its own strengths and weaknesses that could influence clinical decision-making. To make some headway on this clinical dilemma, we deployed a multidimensional transcriptomics integration approach by analysing bulk RNA sequencing data with 136 samples, as well as single-nucleus RNA sequencing (snRNA-seq) and paired spatial transcriptome sequencing (stRNA) data from 32 WT specimens. Our findings identified a distinct elevation of RNF34 expression within WT samples, which correlated with unfavourable prognostic outcomes. Leveraging the Genomics of Drug Sensitivity in Cancer (GDSC), we simultaneously revealed that patients with high expression of RNF34 have higher sensitivity to commonly used chemotherapy drugs for WT. Furthermore, our analysis of snRNA and stRNA data unveiled a reduced proportion of RNF34 expression in neoplastic cells after chemotherapy. Moreover, stRNA data delineated a significant association between a higher proportion of RNF34 expression in cancer cells and adverse features such as anaplastic histology and tumour recurrence. Intriguingly, we also observed a close association between elevated RNF34 expression and a characteristic exhausted tumour immune microenvironment. Collectively, our findings underscore the pivotal role of RNF34 in the prognostic prediction potential and treatment sensitivity of WT. This comprehensive analysis can potentially inform and refine clinical decision-making for WT patients and guide future studies towards the development of optimized, rational therapeutic strategies.

Brucea javanica derived exosome-like nanovesicles deliver miRNAs for cancer therapy.

Triple-negative breast cancer (TNBC) is characterized by complex heterogeneity, high recurrence and metastasis rates, and short overall survival, owing to the lack of endocrine and targeted receptors, which necessitates chemotherapy as the major treatment regimen. Exosome-like nanovesicles derived from medicinal plants have shown great potential as novel biotherapeutics for cancer therapy by delivering their incorporated nucleic acids, especially microRNAs (miRNAs), to mammalian cells. In this study, we isolated exosome-like nanovesicles derived from B. javanica (BF-Exos) and investigated their influence and underlying molecular mechanisms in TNBC. We found that BF-Exos delivered 10 functional miRNAs to 4T1 cells, significantly retarding the growth and metastasis of 4T1 cells by regulating the PI3K/Akt/mTOR signaling pathway and promoting ROS/caspase-mediated apoptosis. Moreover, BF-Exos were shown to inhibit the secretion of vascular endothelial growth factor, contributing to anti-angiogenesis in the tumor microenvironment. In vivo, BF-Exos inhibited tumor growth, metastasis, and angiogenesis in breast tumor mouse models, while maintaining high biosafety. Overall, BF-Exos are considered promising nanoplatforms for the delivery of medicinal plant-derived nucleic acids, with great potential to be developed into novel biotherapeutics for the treatment of TNBC.

Exploring the association between two groups of metals with potentially opposing renal effects and renal function in middle-aged and older adults: Evidence from an explainable machine learning method.

BACKGROUND: Machine learning models have promising applications in capturing the complex relationship between mixtures of exposures and outcomes. OBJECTIVE: Our study aimed at introducing an explainable machine learning (EML) model to assess the association between metal mixtures with potentially opposing renal effects and renal function in middle-aged and older adults. METHODS: This study extracted data from two cycle years of the National Health and Nutrition Examination Survey (NHANES). Participants aged 45 years or older with complete data on six metals (lead, cadmium, manganese, mercury, and selenium) and related covariates were enrolled. The EML model was developed by the optimized machine learning model together with Shapley Additive exPlanations (SHAP) to assess the chronic kidney disease (CKD) risk with metal mixtures. The results from EML were further compared in detail with multiple logistic regression (MLR) and Bayesian kernel machine regression (BKMR). RESULTS: After adjusting for included covariates, MLR pointed out the lead and arsenic were generally positively associated with CKD, but manganese had a negative association. In the BKMR analysis, each metal was found to have a non-linear association with the risk of CKD, and interactions can exist between metals, especially for arsenic and lead. The EML ranked the feature importance: lead, manganese, arsenic and selenium were close behind in importance after gender, age or BMI for participants with CKD. Strong interactions between mercury and lead, manganese and cadmium and arsenic and manganese were identified by partial dependence plot (PDP) of SHAP and bivariate exposure-response effect plots of BKMR. The EML model determined the "trigger point" at which the risk of CKD abruptly changed. CONCLUSION: Co-exposure to metals with different nephrotoxicity could have different joint association with renal function, and EML can be a powerful method for studying complex exposure mixtures.