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Acute myeloid leukaemia (AML) is a highly heterogeneous disease, which lead to various findings in transcriptomic research. This study addresses these challenges by integrating 34 datasets, including 26 control groups, 6 prognostic datasets and 2 single-cell RNA sequencing (scRNA-seq) datasets to identify 10,000 AML-related genes (ARGs). We focused on genes with low variability and high consistency and successfully discovered 191 AML signatures (ASs). Leveraging machine learning techniques, specifically the XGBoost model and our custom framework, we classified AML subtypes with both scRNA-seq and bulk RNA-seq data, complementing the ELN2022 classification approach. Our research also identified promising treatments for AML through drug repurposing, with solasonine showing potential efficacy for high-risk AML patients, supported by molecular docking and transcriptomic analyses. To enhance reproducibility and customizability, we developed CSAMLdb, a user-friendly database platform. It facilitates the reuse and personalized analysis of nearly all results obtained in this research, including single-gene prognostics, multi-gene scoring, enrichment analysis, machine learning risk assessment, drug repositioning analysis and literature abstract named entity recognition. CSAMLdb is available at http://www.csamldb.com.

Asunto(s)

Reposicionamiento de Medicamentos , Perfilación de la Expresión Génica , Leucemia Mieloide Aguda , Transcriptoma , Humanos , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/tratamiento farmacológico , Reposicionamiento de Medicamentos/métodos , Transcriptoma/genética , Perfilación de la Expresión Génica/métodos , Aprendizaje Automático , Reproducibilidad de los Resultados , Pronóstico , Regulación Leucémica de la Expresión Génica/efectos de los fármacos , Biología Computacional/métodos , Simulación del Acoplamiento Molecular , Bases de Datos Genéticas

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Metabolic dysregulation is a key driver of cellular senescence, contributing to the progression of systemic aging. The heterogeneity of senescent cells and their metabolic shifts are complex and unexplored. A microfluidic SlipChip integrated with surface-enhanced Raman spectroscopy (SERS), termed SlipChip-SERS, is developed for single-cell metabolism analysis. This SlipChip-SERS enables compartmentalization of single cells, parallel delivery of saponin and nanoparticles to release intracellular metabolites and to realize SERS detection with simple slipping operations. Analysis of different cancer cell lines using SlipChip-SERS demonstrated its capability for sensitive and multiplexed metabolic profiling of individual cells. When applied to human primary fibroblasts of different ages, it identified 12 differential metabolites, with spermine validated as a potent inducer of cellular senescence. Prolonged exposure to spermine can induce a classic senescence phenotype, such as increased senescence-associated ß-glactosidase activity, elevated expression of senescence-related genes and reduced LMNB1 levels. Additionally, the senescence-inducing capacity of spermine in HUVECs and WRL-68 cells is confirmed, and exogenous spermine treatment increased the accumulation and release of H2O2. Overall, a novel SlipChip-SERS system is developed for single-cell metabolic analysis, revealing spermine as a potential inducer of senescence across multiple cell types, which may offer new strategies for addressing ageing and ageing-related diseases.

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OBJECTIVE: This study aimed to leverage real-world electronic medical record (EMR) data to develop interpretable machine learning models for diagnosis of Kawasaki disease, while also exploring and prioritizing the significant risk factors. METHODS: A comprehensive study was conducted on 4,087 pediatric patients at the Children's Hospital of Chongqing, China. The study collected demographic data, physical examination results, and laboratory findings. Statistical analyses were performed using SPSS 26.0. The optimal feature subset was employed to develop intelligent diagnostic prediction models based on the Light Gradient Boosting Machine (LGBM), Explainable Boosting Machine (EBM), Gradient Boosting Classifier (GBC), Fast Interpretable Greedy-Tree Sums (FIGS), Decision Tree (DT), AdaBoost Classifier (AdaBoost), and Logistic Regression (LR). Model performance was evaluated in three dimensions: discriminative ability via Receiver Operating Characteristic curves, calibration accuracy using calibration curves, and interpretability through Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). RESULTS: In this study, Kawasaki disease was diagnosed in 2,971 participants. Analysis was conducted on 31 indicators, including red blood cell distribution width and erythrocyte sedimentation rate. The EBM model demonstrated superior performance compared to other models, with an Area Under the Curve (AUC) of 0.97, second only to the GBC model. Furthermore, the EBM model exhibited the highest calibration accuracy and maintained its interpretability without relying on external analytical tools like SHAP and LIME, thus reducing interpretation biases. Platelet distribution width, total protein, and erythrocyte sedimentation rate were identified by the model as significant predictors for the diagnosis of Kawasaki disease. CONCLUSIONS: This study employed diverse machine learning models for early diagnosis of Kawasaki disease. The findings demonstrated that interpretable models, like EBM, outperformed traditional machine learning models in terms of both interpretability and performance. Ensuring consistency between predictive models and clinical evidence is crucial for the successful integration of artificial intelligence into real-world clinical practice.

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The limited optical penetration depth and hypoxic tumor microenvironment (TME) are key factors that hinder the practical applications of conventional photodynamic therapy (PDT). To fundamentally address these issues, self-luminescent photosensitizers (PSs) can achieve efficient PDT. Herein, a self-chemiluminescence (CL)-triggered Ir complex PS, namely, IrL2, with low-O2-dependence type I photochemical processes is reported for efficient PDT. The rational design achieves efficient chemiluminescence resonance energy transfer (CRET) from covalently bonded luminol units to the Ir complex in IrL2 under the catalysis of H2O2 and hemoglobin (Hb) to generate O2•- and 1O2. Liposome IrL2H nanoparticles (NPs) are constructed by loading IrL2 and Hb. The intracellular H2O2 and loaded Hb catalyze the luminol part of IrL2H, and the Ir2 part is then excited to produce types I and II reactive oxygen species (ROS) through CRET, inducing cell death, even under hypoxic conditions, and promoting cell apoptosis. IrL2H is used for tumor imaging and inhibits tumor growth in 4T1-bearing mouse models through intratumoral injection without external light sources. This work provides new designs for transition metal complex PSs that conquer the limitations of external light sources and the hypoxic TME in PDT.

Asunto(s)

Iridio , Fotoquimioterapia , Fármacos Fotosensibilizantes , Fármacos Fotosensibilizantes/química , Fármacos Fotosensibilizantes/farmacología , Fármacos Fotosensibilizantes/síntesis química , Animales , Iridio/química , Iridio/farmacología , Ratones , Complejos de Coordinación/química , Complejos de Coordinación/farmacología , Complejos de Coordinación/síntesis química , Luminiscencia , Antineoplásicos/farmacología , Antineoplásicos/química , Antineoplásicos/síntesis química , Apoptosis/efectos de los fármacos , Humanos , Ratones Endogámicos BALB C , Línea Celular Tumoral , Ensayos de Selección de Medicamentos Antitumorales , Hipoxia Tumoral/efectos de los fármacos , Proliferación Celular/efectos de los fármacos , Femenino , Supervivencia Celular/efectos de los fármacos , Especies Reactivas de Oxígeno/metabolismo , Estructura Molecular

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A long-wavelength triggered cationic iridium(III) complex, Ir5, and its corresponding nanoparticles with the ability to generate type I and type II reactive oxygen species have been synthesised. The complex targets mitochondria and achieves an excellent photodynamic therapy effect in hypoxic cancer cells.

Asunto(s)

Complejos de Coordinación , Iridio , Nanopartículas , Fotoquimioterapia , Fármacos Fotosensibilizantes , Iridio/química , Iridio/farmacología , Humanos , Fármacos Fotosensibilizantes/química , Fármacos Fotosensibilizantes/farmacología , Fármacos Fotosensibilizantes/síntesis química , Complejos de Coordinación/química , Complejos de Coordinación/farmacología , Complejos de Coordinación/síntesis química , Nanopartículas/química , Especies Reactivas de Oxígeno/metabolismo , Antineoplásicos/química , Antineoplásicos/farmacología , Antineoplásicos/síntesis química , Línea Celular Tumoral , Supervivencia Celular/efectos de los fármacos , Neoplasias/tratamiento farmacológico , Ensayos de Selección de Medicamentos Antitumorales

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BACKGROUND: Prolonged mechanical ventilation is associated with an increased risk of mortality in these patients. However, there exists a significant clinical need for novel indicators that can complement traditional weaning evaluation methods and effectively guide ventilator weaning. OBJECTIVES: To investigate the specific relationship between mechanical power normalized to dynamic lung compliance (Cdyn-MP) and weaning outcomes in patients on mechanical ventilation for more than 24 hours, as well as those who underwent a T-tube weaning strategy. METHODS: A retrospective cohort study was conducted using the Medical Information Mart for Intensive Care-IV v1.0 database (MIMIC-IV v1.0). Patients who received invasive mechanical ventilation for more than 24 hours and underwent a T-tube ventilation strategy for weaning were enrolled. Patients were divided into two groups based on their weaning outcome: weaning success and failure. Ventilation parameter data were collected every 4 hours during the first 24 hours before the first spontaneous breathing trial (SBT). RESULTS: Of all the 3,695 patients, 1,421 (38.5%) experienced weaning failure. Univariate logistic regression analysis revealed that the risk of weaning failure increased as the Cdyn-MP level rose (OR 1.34, 95% CI 1.31-1.38, P<0.001). After adjusting for age, body mass index, disease severity, and pre-weaning disease status, patients with high Cdyn-MP quartiles in the 4 hours prior to the SBT had a significantly greater risk of weaning failure than those with low Cdyn-MP quartiles (odds ratio 10.37, 95% CI 7.56-14.24). These findings were robust and consistent in both subgroup and sensitivity analyses. CONCLUSION: The increased Cdyn-MP before SBT was independently associated with a higher risk of weaning failure in mechanically ventilated patients. Cdyn-MP has the potential to be a useful indicator for guiding the need for ventilator weaning and complementing traditional weaning evaluation methods.

Asunto(s)

Respiración Artificial , Desconexión del Ventilador , Humanos , Desconexión del Ventilador/métodos , Masculino , Femenino , Persona de Mediana Edad , Estudios Retrospectivos , Anciano , Respiración Artificial/métodos , Rendimiento Pulmonar

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Studies have indicated cancer-associated fibroblasts (CAFs) could have a significant impact in gastric cancer (GC) progression and chemotherapy resistance. However, the gene related to cancer fibroblasts that can be used as biomarkers to judge the occurrence of gastric cancer has not been fully explored. Based on two Gene Expression Omnibus (GEO) datasets, we focus on differentially expressed genes which may act as CAFs markers related to GC. Through COX regression, LASSO regression and Kaplan-Meier survival analysis, we discovered three upregulated genes (GLT8D2, GNAS and EDA) associated with poor GC patients' survival. By single-cell analysis and nomogram, we found that EDA may affect fibroblast production and disease prognosis in GC patients. EDA expression showed a positive correlation with 5-Fluorouracil IC50 values. Immunohistochemistry (IHC) and real time PCR indicated elevated EDA levels in GC tissues and cells. Enrichment analysis revealed that EDA was closely linked to immune system regulation. IHC and single-cell analysis indicated that EDA gene was associated with cancer fibroblasts marker FGF12 and influence cell interferon-gamma response, which may play a role in regulating immune-related characteristics. In summary, we concluded that EDA may be used as a new therapeutic CAFs marker for GC.

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The functional heterogeneity and ecological niche of prostate cancer stem cells (PCSCs), which are major drivers of prostate cancer development and treatment resistance, have attracted considerable research attention. Cancer-associated fibroblasts (CAFs), which are crucial components of the tumor microenvironment (TME), substantially affect PCSC stemness. Additionally, CAFs promote PCSC growth and survival by releasing signaling molecules and modifying the surrounding environment. Conversely, PCSCs may affect the characteristics and behavior of CAFs by producing various molecules. This crosstalk mechanism is potentially crucial for prostate cancer progression and the development of treatment resistance. Using organoids to model the TME enables an in-depth study of CAF-PCSC interactions, providing a valuable preclinical tool to accurately evaluate potential target genes and design novel treatment strategies for prostate cancer. The objective of this review is to discuss the current research on the multilevel and multitarget regulatory mechanisms underlying CAF-PCSC interactions and crosstalk, aiming to inform therapeutic approaches that address challenges in prostate cancer treatment.

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Patients with multiple myeloma (MM) experience relapse and drug resistance; therefore, novel treatments are essential. Clotrimazole (CTZ) is a wide-spectrum antifungal drug with antitumor activity. However, CTZ's effects on MM are unclear. We investigated CTZ's effect on MM cell proliferation and apoptosis induction mechanisms. CTZ's effects on MM.1S, NCI- H929, KMS-11, and U266 cell growth were investigated using Cell Counting Kit-8 (CCK-8) assay. The apoptotic cell percentage was quantified with annexin V-fluorescein isothiocyanate/7-amino actinomycin D staining. Mitochondrial membrane potential (MMP) and cell cycle progression were evaluated. Reactive oxygen species (ROS) levels were measured via fluorescence microscopy. Expression of apoptosis-related and nuclear factor (NF)-κB signaling proteins was analyzed using western blotting. The CCK-8 assay indicated that CTZ inhibited cell proliferation based on both dose and exposure time. Flow cytometry revealed that CTZ decreased apoptosis and MMP and induced G0/G1 arrest. Immunofluorescence demonstrated that CTZ dose-dependently elevated in both total and mitochondrial ROS production. Western blotting showed that CTZ enhanced Bax and cleaved poly ADP-ribose polymerase and caspase-3 while decreasing Bcl-2, p-p65, and p-IκBα. Therefore, CTZ inhibits MM cell proliferation by promoting ROS-mediated mitochondrial apoptosis, inducing G0/G1 arrest, inhibiting the NF-κB pathway, and has the potential for treating MM.

Asunto(s)

Apoptosis , Proliferación Celular , Clotrimazol , Potencial de la Membrana Mitocondrial , Mitocondrias , Mieloma Múltiple , Especies Reactivas de Oxígeno , Humanos , Mieloma Múltiple/patología , Mieloma Múltiple/tratamiento farmacológico , Mieloma Múltiple/metabolismo , Apoptosis/efectos de los fármacos , Línea Celular Tumoral , Proliferación Celular/efectos de los fármacos , Mitocondrias/efectos de los fármacos , Mitocondrias/metabolismo , Especies Reactivas de Oxígeno/metabolismo , Potencial de la Membrana Mitocondrial/efectos de los fármacos , Clotrimazol/farmacología , Fase de Descanso del Ciclo Celular/efectos de los fármacos , Puntos de Control de la Fase G1 del Ciclo Celular/efectos de los fármacos , Transducción de Señal/efectos de los fármacos , FN-kappa B/metabolismo , Antineoplásicos/farmacología , Puntos de Control del Ciclo Celular/efectos de los fármacos

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Corneal transplantation is a common treatment for corneal diseases. Secondary glaucoma after corneal transplantation is the second leading cause of failure of keratoplasty. This article reviews the mechanism and treatment of secondary glaucoma after corneal transplantation.

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Background: Osteosarcoma (OS) is a malignancy originating from mesenchymal tissue. Microfibril-associated protein 2 (MFAP2) plays a crucial role in cancer, notably promoting epithelial-mesenchymal transition (EMT). However, its involvement in OS remains unexplored. Methods: MFAP2 was silenced in U2OS cells using shRNA targeting MFAP2 (sh-MFAP2) and validated by quantitative real-time polymerase chain reaction (qRT-PCR). We extracted gene chip data of MFAP2 from multiple databases (GSE28424, GSE42572, and GSE126209). Correlation analyses between MFAP2 and the Notch1 pathway identified through the gene set variation analysis (GSVA) enrichment analysis were conducted using the Pearson correlation method. Cellular behaviors (viability, migration, and invasion) were assessed via the Cell Counting Kit-8 (CCK-8), wound healing, and Transwell assays. EMT markers (N-cadherin, vimentin, and ß-catenin) and Notch1 levels were examined by western blotting and qRT-PCR. Cell morphology was observed microscopically to evaluate EMT. Finally, the role of MFAP2 in OS was validated through a xenograft tumor model. Results: OS cell lines exhibited higher MFAP2 mRNA expression than normal osteoblasts. MFAP2 knockdown in U2OS cells significantly reduced viability, migration, and invasion, along with downregulation of N-cadherin and vimentin, as well as upregulation of ß-catenin. MFAP2 significantly correlated with the Notch1 pathway in OS and its knockdown inhibited Notch1 protein expression. Furthermore, Notch1 activation reversed the inhibitory effects of MFAP2 knockdown on the malignant characteristic of U2OS cells. Additionally, MFAP2 knockdown inhibited tumor growth, expression levels of EMT markers, and Notch1 expression in OS tumor tissues. Conclusions: Our study revealed that MFAP2 was an upstream regulator of the Notch1 signaling pathway to promote EMT in OS. These findings suggested MFAP2 as a potential OS therapy target.

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Nucleus pulposus (NP) cell pyroptosis is crucial for intervertebral disc degeneration (IDD). However, the precise mechanisms underlying pyroptosis in IDD remain elusive. Therefore, this study aimed to investigate how dickkopf-1 (DKK1) influences NP cell pyroptosis and delineate the regulatory mechanisms of IDD. Behavioral tests and histological examinations were conducted in rat IDD models to assess the effect of DKK1 on the structure and function of intervertebral discs. Detected pyroptosis levels using Hoechst 33,342/propidium iodide (PI) double staining, and determined pyroptosis-related protein expression via western blotting. The cellular mechanisms of DKK1 in pyroptosis were explored in interleukin (IL)-1ß-induced NP cells transfected with or without DKK1 overexpression plasmids (oe-DKK1). In addition, IL-1ß-treated NP cells transfected with sh-EZH2 and/or sh-DKK1 were utilized to clarify the interplay between the enhancer of zeste homologue 2 (EZH2) and DKK1 in pyroptosis. Additionally, the epigenetic regulation of DKK1 by EZH2 was explored in NP cells treated with the EZH2 inhibitors GSK126/DZNep. DKK1 expression decreased in IDD rats. Transfection with oe-DKK1 reduced pro-inflammatory factors and extracellular matrix markers in IDD rats. In IL-1ß-induced NP cells, DKK1 overexpression suppressed pyroptosis and inhibited the NLRP3 and NAIP/NLRC4 inflammasome activation. EZH2 knockdown increased DKK1 expression and reduced pyroptosis-related proteins. Conversely, DKK1 downregulation reversed the inhibitory effects of EZH2 knockdown on pyroptosis. Furthermore, EZH2 suppressed DKK1 expression via H3K27 methylation at the DKK1 promoter. EZH2 negatively regulates DKK1 expression via H3K27me3 methylation, promoting NP cell pyroptosis in IDD patients. This regulatory effect involves the activation of NLRP3 and NAIP/NLRC4 inflammasomes.

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Halogens (chlorine, bromine, and iodine) are known to profoundly influence atmospheric oxidants (hydroxyl radical (OH), hydroperoxyl radical (HO2), ozone (O3), and nitrate radical (NO3)) in the troposphere and subsequently affecting air quality. However, their impact on atmospheric oxidation and air pollution in coastal areas in China is poorly characterized. In this study, we use the WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model with full halogen chemistry and process analysis to assess the influences and pathways of halogens on atmospheric oxidants in the Yangtze River Delta (YRD) region, a typical coastal city cluster in China. Halogens cause the annual OH radical increase by up to 16.4% and NO3 decrease by up to 45.3%. O3 increases by 2.0% in the YRD but decreases by 3.3% in marine environment. Halogen induced changes in atmospheric oxidants lead to a general increase of atmospheric oxidation capacity by 5.1% (maximum 48.4%). The production rate of OH (POH) in the YRD is enhanced by anthropogenic chlorine through both increased HO2 pathway and hypohalous acid photolysis pathway, while POH over ocean is enhanced by oceanic halogens through converting HO2 into hypohalous acid. Anthropogenic chlorine enhances both O3 and NO3 production (PNO3) rates through influencing their precursors while oceanic halogens reduce PNO3 and directly destroy ozone. Iodine contributed most (on average of 91% in oceanic halogens) in reducing production rates of oxidants. Thus, halogen emissions and potential effects of halogens on air quality need to be considered in air quality policies and regulations in the YRD region.

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The combustion processes and catalytic after-treatment of ammonia/hydrogen-fueled engines, including NOx storage and reduction (NSR) and noble-metal selective catalytic reduction (SCR), can produce the byproduct N2O, a potent greenhouse gas that weakens the zero-carbon attribute of these fuels. Currently, the mechanism of N2O formation on DeNOx catalysts remains unclear due to limited research on catalytic after-treatment for such engines and the complexity of surface catalytic reactions. To elucidate the formation of N2O on the DeNOx catalysts of ammonia/hydrogen fuel engines, the impact factors on N2O formation on platinum catalysts (typical catalysts in NSR and noble-metal SCR) were investigated using first-principles molecular dynamics (FPMD). By employing the blue-moon ensemble enhanced sampling method and the slow-growth approach for free energy surface exploration, together with density functional theory (DFT) for electronic structure analysis, a linear relationship between the spin splitting of the d states of Pt clusters and N2O formation energy barriers was revealed, along with the increased structural sensitivity of Pt clusters with fewer atoms. It is highlighted that the energy barrier for N2O formation is determined by the matching degree of energy levels between molecules and surfaces. These findings provide atomic-scale insights into N2O formation on DeNOx catalysts for ammonia/hydrogen-fueled engines, facilitating N2O emission control for carbon-free engines.

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Hepatitis C virus (HCV) can cause a range of kidney diseases. HCV is the primary cause of mixed cryoglobulinaemia, which leads to cryoglobulinaemic vasculitis and cryoglobulinaemic glomerulonephritis (GN). Patients with acute cryoglobulinaemic vasculitis often exhibit acute kidney disease due to HCV infection, which typically progresses to acute kidney injury (AKI). HCV also increases the risk of chronic kidney disease (CKD) and the likelihood of developing end-stage renal disease (ESRD). Currently, direct-acting antiviral agents (DAAs) can be used to treat kidney disease at different stages. This review focuses on key findings regarding HCV and kidney disease, discusses the impact of DAAs, and highlights the need for further research and treatment.

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In this work, we introduced a siderophore information database (SIDERTE), a digitized siderophore information database containing 649 unique structures. Leveraging this digitalized data set, we gained a systematic overview of siderophores by their clustering patterns in the chemical space. Building upon this, we developed a functional group-based method for predicting new iron-binding molecules with experimental validation. Expanding our approach to the collection of open natural products (COCONUT) database, we predicted a staggering 3199 siderophore candidates, showcasing remarkable structure diversity that is largely unexplored. Our study provides a valuable resource for accelerating the discovery of novel iron-binding molecules and advancing our understanding of siderophores.

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Total organic halogen (TOX) is used to describe total amount of halogenated DBPs. Typically, once a chlor(am)inated water sample is collected, it is necessary to add a quenching agent to quench the residual disinfectant so that further reactions to form more DBPs during the holding time can be prevented. In this study, we evaluated the effects of four quenching agents: ammonium chloride (NH4Cl), ascorbic acid, sodium sulfite (Na2SO3), and sodium thiosulfate (Na2S2O3) on the decomposition of TOX, aliphatic and aromatic halogenated DBPs under various quenching conditions (quenching time, pH, quenching ratio, temperature). The results showed that ascorbic acid had the least impact on TOX. Ascorbic acid appeared to be the most suitable quenching agent for aliphatic halogenated DBPs, especially since it could preserve more haloacetonitriles than other quenching agents. Both ascorbic acid and Na2SO3 could be used for the analysis of aromatic halogenated DBPs. The lower pH (pH 6.0), not excessive quenching agents and lower temperature (4 ºC) were all conducive to the preservation of TOX and halogenated DBPs. Importantly, unknown TOX (UTOX) also contained significantly toxic components. It was also found that addition of quenching agents might lead to underestimation of UTOX by researchers. SYNOPSIS: The quenching agents and quenching conditions for the analysis of total organic halogen, aliphatic and aromatic halogenated DBPs formed from chlor(am)ination were investigated.

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BACKGROUND: This study aimed to develop a higher performance nomogram based on explainable machine learning methods, and to predict the risk of death of stroke patients within 30 days based on clinical characteristics on the first day of intensive care units (ICU) admission. METHODS: Data relating to stroke patients were extracted from the Medical Information Marketplace of the Intensive Care (MIMIC) IV and III database. The LightGBM machine learning approach together with Shapely additive explanations (termed as explain machine learning, EML) was used to select clinical features and define cut-off points for the selected features. These selected features and cut-off points were then evaluated using the Cox proportional hazards regression model and Kaplan-Meier survival curves. Finally, logistic regression-based nomograms for predicting 30-day mortality of stroke patients were constructed using original variables and variables dichotomized by cut-off points, respectively. The performance of two nomograms were evaluated in overall and individual dimension. RESULTS: A total of 2982 stroke patients and 64 clinical features were included, and the 30-day mortality rate was 23.6% in the MIMIC-IV datasets. 10 variables ("sofa (sepsis-related organ failure assessment)", "minimum glucose", "maximum sodium", "age", "mean spo2 (blood oxygen saturation)", "maximum temperature", "maximum heart rate", "minimum bun (blood urea nitrogen)", "minimum wbc (white blood cells)" and "charlson comorbidity index") and respective cut-off points were defined from the EML. In the Cox proportional hazards regression model (Cox regression) and Kaplan-Meier survival curves, after grouping stroke patients according to the cut-off point of each variable, patients belonging to the high-risk subgroup were associated with higher 30-day mortality than those in the low-risk subgroup. The evaluation of nomograms found that the EML-based nomogram not only outperformed the conventional nomogram in NIR (net reclassification index), brier score and clinical net benefits in overall dimension, but also significant improved in individual dimension especially for low "maximum temperature" patients. CONCLUSIONS: The 10 selected first-day ICU admission clinical features require greater attention for stroke patients. And the nomogram based on explainable machine learning will have greater clinical application.

Asunto(s)

Unidades de Cuidados Intensivos , Aprendizaje Automático , Nomogramas , Accidente Cerebrovascular , Humanos , Masculino , Femenino , Anciano , Persona de Mediana Edad , Accidente Cerebrovascular/mortalidad , Medición de Riesgo , Anciano de 80 o más Años , Pronóstico

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Hepatocellular carcinoma is the most common form of primary liver cancer and poses a significant challenge to the medical community because of its high mortality rate. In recent years, ferroptosis, a unique form of cell death, has garnered widespread attention. Ferroptosis, which is characterized by iron-dependent lipid peroxidation and mitochondrial alterations, is closely associated with the pathological processes of various diseases, including hepatocellular carcinoma. Long non-coding RNAs (lncRNAs), are a type of functional RNA, and play crucial regulatory roles in a variety of biological processes. In this manuscript, we review the regulatory roles of lncRNAs in the key aspects of ferroptosis, and summarize the research progress on ferroptosis-related lncRNAs in hepatocellular carcinoma.

Asunto(s)

Carcinoma Hepatocelular , Ferroptosis , Neoplasias Hepáticas , ARN Largo no Codificante , Humanos , Ferroptosis/genética , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/metabolismo , Carcinoma Hepatocelular/patología , ARN Largo no Codificante/genética , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/patología , Neoplasias Hepáticas/metabolismo , Animales , Regulación Neoplásica de la Expresión Génica

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The application of ChatGPTin the medical field has sparked debate regarding its accuracy. To address this issue, we present a Multi-Role ChatGPT Framework (MRCF), designed to improve ChatGPT's performance in medical data analysis by optimizing prompt words, integrating real-world data, and implementing quality control protocols. Compared to the singular ChatGPT model, MRCF significantly outperforms traditional manual analysis in interpreting medical data, exhibiting fewer random errors, higher accuracy, and better identification of incorrect information. Notably, MRCF is over 600 times more time-efficient than conventional manual annotation methods and costs only one-tenth as much. Leveraging MRCF, we have established two user-friendly databases for efficient and straightforward drug repositioning analysis. This research not only enhances the accuracy and efficiency of ChatGPT in medical data science applications but also offers valuable insights for data analysis models across various professional domains.

Asunto(s)

Análisis de Datos , Humanos , Bases de Datos Factuales , Reposicionamiento de Medicamentos/métodos , Algoritmos