Understanding regulating effects of protein-anionic octenyl succinic anhydride-modified starch interactions on the structural, rheological, digestibility and release properties of starch.

BACKGROUND: Proteins and anionic octenyl succinic anhydride (OSA)-modified starch (OSA-starch) are common ingredients in food systems. The interactions between OSA-starch and protein are found to alter the structural and functional properties of the protein-OSA-starch complexes. In this regard, the close understanding of the relationship among the molecular interactions between whey protein isolate (WPI) and OSA-high amylose corn starch (HAS), structure changes and rheological, digestibility and release properties of WPI-OSA-HAS was investigated. RESULTS: The molecular interactions of WPI-OSA-HAS were significant for increasing the surface rough, solubility, storage modulus and loss modulus, but decreasing the R1047/1022 values. For the nutritional evaluation, the anti-digestibility of WPI-OSA-HAS was enhanced with increased resistant starch + slowly digestible starch contents and decreased equilibrium hydrolysis percentage and kinetic constant. During the digestion, part of the starch granule, OSA groups and WPI were lost, but the loss was lower than for OSA-HAS. Furthermore, the results of curcumin-loaded WPI-OSA-HAS in simulated gastrointestinal fluids demonstrated that curcumin could be gradually released to simulate colonic fluid. Notably, the interaction between WPI and OSA-HAS depended on the WPI concentration with the stronger molecular interactions obtained at 35% concentration. CONCLUSION: These results provided important information concerning how to adjust the rheological, anti-digestibility and release properties of WPI-OSA-HAS through altering the electrostatic interactions and hydrophobic interactions of WPI-OSA-HAS. © 2024 Society of Chemical Industry.

Effects of OSA-starch-fatty acid interactions on the structural, digestibility and release characteristics of high amylose corn starch.

This study investigated the effects of octenyl succinic anhydride (OSA)-starch-fatty acid (FA) interactions on the structural, digestibility and release characteristics of high amylose corn starch (HAS). FTIR and XRD analysis showed that the hydrophobic interaction between HAS and FA promoted the covalent binding between OSA and HAS. With the increasing of the FA chain length, the complex index, degree of substitution, R1047/1022 and relative crystallinity of OSA-HAS-FA increased first and then decreased, whereas the first-order rate coefficient and percentage of digested in infinite time showed an opposite trend. Structural changes and the molecular interactions of OSA-HAS-FA with 12­carbon FA resulted in highest resistant starch content (45.43%) and encapsulation efficiency of curcumin (Cur) (47.98%). In vitro release test revealed that Cur could be gradually released from OSA-HAS-FA in simulated gastric, intestinal and colonic fluids. Results provided novel insights into HAS-FA complex grafted with OSA as carrier for colon-specific of functional materials.

Population pharmacokinetics of daptomycin in critically ill patients receiving extracorporeal membrane oxygenation.

BACKGROUND: Daptomycin is widely used in critically ill patients for Gram-positive bacterial infections. Extracorporeal membrane oxygenation (ECMO) is increasingly used in this population and can potentially alter the pharmacokinetic (PK) behaviour of antibiotics. However, the effect of ECMO has not been evaluated in daptomycin. Our study aims to explore the effect of ECMO on daptomycin in critically ill patients through population pharmacokinetic (PopPK) analysis and to determine optimal dosage regimens based on both efficacy and safety considerations. METHODS: A prospective, open-label PK study was carried out in critically ill patients with or without ECMO. The total concentration of daptomycin was determined by UPLC-MS/MS. NONMEM was used for PopPK analysis and Monte Carlo simulations. RESULTS: Two hundred and ninety-three plasma samples were collected from 36 critically ill patients, 24 of whom received ECMO support. A two-compartment model with first-order elimination can best describe the PK of daptomycin. Creatinine clearance (CLCR) significantly affects the clearance of daptomycin while ECMO has no significant effect on the PK parameters. Monte Carlo simulations showed that, when the MICs for bacteria are  ≥1 mg/L, the currently recommended dosage regimen is insufficient for critically ill patients with CLCR > 30 mL/min. Our simulations suggest 10 mg/kg for patients with CLCR between 30 and 90 mL/min, and 12 mg/kg for patients with CLCR higher than 90 mL/min. CONCLUSIONS: This is the first PopPK model of daptomycin in ECMO patients. Optimal dosage regimens considering efficacy, safety, and pathogens were provided for critical patients based on pharmacokinetic-pharmacodynamic analysis.

DEVELOPMENT AND VALIDATION OF A NOMOGRAM FOR PREDICTING 28-DAY IN-HOSPITAL MORTALITY IN SEPSIS PATIENTS BASED ON AN OPTIMIZED ACUTE PHYSIOLOGY AND CHRONIC HEALTH EVALUATION II SCORE.

ABSTRACT: Purpose : The objective of this study is to establish a nomogram that correlates optimized Acute Physiology and Chronic Health Evaluation II (APACHE II) score with sepsis-related indicators, aiming to provide a robust model for early prediction of sepsis prognosis in clinical practice and serve as a valuable reference for improved diagnosis and treatment strategies. Methods : This retrospective study extracted sepsis patients meeting the inclusion criteria from the MIMIC-IV database to form the training group. An optimized APACHE II score integrated with relevant indicators was developed using a nomogram for predicting the prognosis of sepsis patients. External validation was conducted using data from the intensive care unit at Lanzhou University Second Hospital. Results : The study enrolled 1805 patients in the training cohort and 203 patients in the validation cohort. A multifactor analysis was conducted to identify factors affecting patient mortality within 28 days, resulting in the development of an optimized score by simplifying evaluation indicators from APACHE II score. The results showed that the optimized score (area under the ROC curve [AUC] = 0.715) had a higher area under receiver operating characteristic curve than Sequential Organ Failure Assessment score (AUC = 0.637) but slightly lower than APACHE II score (AUC = 0.720). Significant indicators identified through multifactor analysis included platelet count, total bilirubin level, albumin level, prothrombin time, activated partial thromboplastin time, mechanical ventilation use and renal replacement therapy use. These seven indicators were combined with optimized score to construct a nomogram based on these seven indicators. The nomogram demonstrated good clinical predictive value in both training cohort (AUC = 0.803) and validation cohort (AUC = 0.750). Calibration curves and decision curve analyses also confirmed its good predictive ability, surpassing the APACHE II score and Sequential Organ Failure Assessment score in identifying high-risk patients. Conclusions : The nomogram was established in this study using the MIMIC-IV database and validated with external data, demonstrating its robust discriminability, calibration, and clinical practicability for predicting 28-day mortality in sepsis patients. These findings aim to provide substantial support for clinicians' decision making.

Classification of cognitive ability of healthy older individuals using resting-state functional connectivity magnetic resonance imaging and an extreme learning machine.

BACKGROUND: Quantitative determination of the correlation between cognitive ability and functional biomarkers in the older brain is essential. To identify biomarkers associated with cognitive performance in the older, this study combined an index model specific for resting-state functional connectivity (FC) with a supervised machine learning method. METHODS: Performance scores on conventional cognitive test scores and resting-state functional MRI data were obtained for 98 healthy older individuals and 90 healthy youth from two public databases. Based on the test scores, the older cohort was categorized into two groups: excellent and poor. A resting-state FC scores model (rs-FCSM) was constructed for each older individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using this model. To suggest the effectiveness of constructed model, the scores of these brain areas were used as feature matrix inputs for training an extreme learning machine. classification accuracy (CA) was then tested in separate groups and validated by N-fold cross-validation. RESULTS: This learning study could effectively classify the cognitive status of healthy older individuals according to the model scores of frontal lobe, temporal lobe, and parietal lobe with a mean accuracy of 86.67%, which is higher than that achieved using conventional correlation analysis. CONCLUSION: This classification study of the rs-FCSM may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms.

Enzyme-Empowered "Two Birds with One Stone" Strategy for Amplifying Tumor Apoptosis and Metabolic Clearance.

Nanomedicine has reshaped the landscape of cancer treatment. However, its efficacy is still hampered by innate tumor defense systems that rely on adenosine triphosphate (ATP) for fuel, including damage repair, apoptosis resistance, and immune evasion. Inspired by the naturally enzymatic reaction of glucose oxidase (GOx) with glucose, here a novel "two birds with one stone" technique for amplifying enzyme-mediated tumor apoptosis and enzyme-promoted metabolic clearance is proposed and achieved using GOx-functionalized rhenium nanoclusters-doped polypyrrole (Re@ReP-G). Re@ReP-G reduces ATP production while increasing H2O2 concentrations in the tumor microenvironment through GOx-induced enzymatic oxidation, which in turn results in the downregulation of defense (HSP70 and HSP90) and anti-apoptotic Bcl-2 proteins, the upregulation of pro-apoptotic Bax, and the release of cytochrome c. These processes are further facilitated by laser-induced hyperthermia effect, ultimately leading to severe tumor apoptosis. As an enzymatic byproduct, H2O2 catalyzes the conversion of rhenium nanoclusters in Re@ReP-G nanostructures into rhenate from the outside in, which accelerates their metabolic clearance in vivo. This Re@ReP-G-based "two birds with one stone" therapeutic strategy provides an effective tool for amplifying tumor apoptosis and safe metabolic mechanisms.

Adaptive Segmentation Algorithm for Subtle Defect Images on the Surface of Magnetic Ring Using 2D-Gabor Filter Bank.

In order to realize the unsupervised segmentation of subtle defect images on the surface of small magnetic rings and improve the segmentation accuracy and computational efficiency, here, an adaptive threshold segmentation method is proposed based on the improved multi-scale and multi-directional 2D-Gabor filter bank. Firstly, the improved multi-scale and multi-directional 2D-Gabor filter bank was used to filter and reduce the noise on the defect image, suppress the noise pollution inside the target area and the background area, and enhance the difference between the magnetic ring defect and the background. Secondly, this study analyzed the grayscale statistical characteristics of the processed image; the segmentation threshold was constructed according to the gray statistical law of the image; and the adaptive segmentation of subtle defect images on the surface of small magnetic rings was realized. Finally, a classifier based on a BP neural network is designed to classify the scar images and crack images determined by different threshold segmentation methods. The classification accuracies of the iterative method, the OTSU method, the maximum entropy method, and the adaptive threshold segmentation method are, respectively, 85%, 87.5%, 95%, and 97.5%. The adaptive threshold segmentation method proposed in this paper has the highest classification accuracy. Through verification and comparison, the proposed algorithm can segment defects quickly and accurately and suppress noise interference effectively. It is better than other traditional image threshold segmentation methods, validated by both segmentation accuracy and computational efficiency. At the same time, the real-time performance of our algorithm was performed on the advanced SEED-DVS8168 platform.

Gsα Regulates Macrophage Foam Cell Formation During Atherosclerosis.

BACKGROUND: Many cardiovascular pathologies are induced by signaling through G-protein-coupled receptors via Gsα (G protein stimulatory α subunit) proteins. However, the specific cellular mechanisms that are driven by Gsα and contribute to the development of atherosclerosis remain unclear. METHODS: High-throughput screening involving data from single-cell and bulk sequencing were used to explore the expression of Gsα in atherosclerosis. The differentially expression and activity of Gsα were analyzed by immunofluorescence and cAMP measurements. Macrophage-specific Gsα knockout (Mac-GsαKO) mice were generated to study the effect on atherosclerosis. The role of Gsα was determined by transplanting bone marrow and performing assays for foam cell formation, Dil-ox-LDL (oxidized low-density lipoprotein) uptake, chromatin immunoprecipitation, and luciferase reporter assays. RESULTS: ScRNA-seq showed elevated Gnas in atherosclerotic mouse aorta's cholesterol metabolism macrophage cluster, while bulk sequencing confirmed increased GNAS expression in human plaque macrophage content. A significant upregulation of Gsα and active Gsα occurred in macrophages from human and mouse plaques. Ox-LDL could translocate Gsα from macrophage lipid rafts in short-term and promote Gnas transcription through ERK1/2 activation and C/EBPß phosphorylation via oxidative stress in long-term. Atherosclerotic lesions from Mac-GsαKO mice displayed decreased lipid deposition compared with those from control mice. Additionally, Gsα deficiency alleviated lipid uptake and foam cell formation. Mechanistically, Gsα increased the levels of cAMP and transcriptional activity of the cAMP response element binding protein, which resulted in increased expression of CD36 and SR-A1. In the translational experiments, inhibiting Gsα activation with suramin or cpGN13 reduced lipid uptake, foam cell formation, and the progression of atherosclerotic plaques in mice in vivo. CONCLUSIONS: Gsα activation is enhanced during atherosclerotic progression and increases lipid uptake and foam cell formation. The genetic or chemical inactivation of Gsα inhibit the development of atherosclerosis in mice, suggesting that drugs targeting Gsα may be useful in the treatment of atherosclerosis.

The influence of big five personality traits on anxiety: The chain mediating effect of general self-efficacy and academic burnout.

BACKGROUND: As an important factor affecting personal health, anxiety has always been valued by people. Prior research has consistently shown that personality traits is associated with anxiety level,but little is known about the inner mechanism of this relationship. To fill the gap, the present research aims to explore the chain mediating role of general self-efficacy and academic burnout in the relationship between big five personality and anxiety. METHODS: This cross-sectional study was performed from September to November 2022. Self-reported questionnaires including the Big Five Personality Questionnaire, General Self-Efficacy Scale, College Student's academic burnout Scale, Generalized Anxiety Scale and demographic characteristics were distributed to 2505 college students in a university in Hebei Province, of which 2,471 were valid. Statistical analysis was carried out through SPSS26.0 and SPSS PROCESS macro. RESULTS: Results showed four of the big five personality characters (i.e., extraversion, agreeableness, conscientiousness, and openness) were negatively correlated with anxiety. Neuroticism was positively correlated with anxiety. Moreover, general self-efficacy was found to be negatively correlated with academic burnout and anxiety; academic burnout was positively correlated with anxiety. Finally, general self-efficacy and academic burnout mediated the relationship between personality traits (i.e., extraversion, agreeableness, neuroticism, openness) and anxiety. CONCLUSIONS: Personality traits (i.e., extraversion, agreeableness, neuroticism, and openness) could influence anxiety through the chain mediating effects of general self-efficacy and academic burnout. Interventions focusing on anxiety reduction may be successful in increasing general self-efficacy and decreasing students' academic burnout.

Textured Asymmetric Membrane Electrode Assemblies of Piezoelectric Phosphorene and Ti3C2Tx MXene Heterostructures for Enhanced Electrochemical Stability and Kinetics in LIBs.

Black phosphorus with a superior theoretical capacity (2596 mAh g-1) and high conductivity is regarded as one of the powerful candidates for lithium-ion battery (LIB) anode materials, whereas the severe volume expansion and sluggish kinetics still impede its applications in LIBs. By contrast, the exfoliated two-dimensional phosphorene owns negligible volume variation, and its intrinsic piezoelectricity is considered to be beneficial to the Li-ion transfer kinetics, while its positive influence has not been discussed yet. Herein, a phosphorene/MXene heterostructure-textured nanopiezocomposite is proposed with even phosphorene distribution and enhanced piezo-electrochemical coupling as an applicable free-standing asymmetric membrane electrode beyond the skin effect for enhanced Li-ion storage. The experimental and simulation analysis reveals that the embedded phosphorene nanosheets not only provide abundant active sites for Li-ions, but also endow the nanocomposite with favorable piezoelectricity, thus promoting the Li-ion transfer kinetics by generating the piezoelectric field serving as an extra accelerator. By waltzing with the MXene framework, the optimized electrode exhibits enhanced kinetics and stability, achieving stable cycling performances for 1,000 cycles at 2 A g-1, and delivering a high reversible capacity of 524 mAh g-1 at - 20 â„ƒ, indicating the positive influence of the structural merits of self-assembled nanopiezocomposites on promoting stability and kinetics.

Renalase mediates macrophage-to-fibroblast crosstalk to attenuate pressure overload-induced pathological myocardial fibrosis.

A potential antifibrotic mechanism in pathological myocardial remodeling is the recruitment of beneficial functional subpopulations of macrophages or the transformation of their phenotype. Macrophages are required to activate molecular cascades that regulate fibroblast behavior. Identifying mediators that activate the antifibrotic macrophage phenotype is tantamount to identifying the button that retards pathological remodeling of the myocardium; however, relevant studies are inadequate. Circulating renalase (RNLS) is mainly of renal origin, and cardiac myocytes also secrete it autonomously. Our previous studies revealed that RNLS delivers cell signaling to exert multiple cardiovascular protective effects, including the improvement of myocardial ischemia, and heart failure. Here, we further investigated the potential mechanism by which macrophage phenotypic transformation is targeted by RNLS to mediate stress load-induced myocardial fibrosis. Mice subjected to transverse aortic constriction (TAC) were used as a model of myocardial fibrosis. The co-incubation of macrophages and cardiac fibroblasts was used to study intercellular signaling. The results showed that RNLS co-localized with macrophages and reduced protein expression after cardiac pressure overload. TAC mice exhibited improved cardiac function and alleviated left ventricular fibrosis when exogenous RNLS was administered. Flow sorting showed that RNLS is essential for macrophage polarization towards a restorative phenotype (M2-like), thereby inhibiting myofibroblast activation, as proven by both mouse RAW264.7 and bone marrow-derived macrophage models. Mechanistically, we found that activated protein kinase B is a major pathway by which RNLS promotes M2 polarization in macrophages. RNLS may serve as a prognostic biomarker and a potential clinical candidate for the treatment of myocardial fibrosis.

Effects of levosimendan on the outcome of veno-arterial extracorporeal membrane oxygenation: a systematic review and meta-analysis.

OBJECTIVES: For patients with severe cardiopulmonary failure, such as cardiogenic shock, veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is primarily utilized to preserve their life by providing continuous extracorporeal respiration and circulation. However, because of the complexity of patients' underlying diseases and serious complications, successful weaning from ECMO is often difficult. At present, there have been limited studies on ECMO weaning strategies, so the principal purpose of this meta-analysis is to examine how levosimendan contributes to the weaning of extracorporeal membrane oxygenation. METHODS: The Cochrane Library, Embase, Web of Science, and PubMed were browsed for all potentially related research about clinical benefits of levosimendan in weaning patients receiving VA-ECMO and included 15 of them. The main outcome is success of weaning from extracorporeal membrane oxygenation, with the secondary outcomes of 1-month mortality (28 or 30 days), ECMO duration, hospital or intensive care unit (ICU) length of stay, and use of vasoactive drugs. RESULTS: 1772 patients altogether from 15 publications were incorporated in our meta-analysis. We used fixed and random-effect models to combine odds ratio (OR) and 95% confidence interval (CI) for dichotomous outcomes and standardized mean difference (SMD) for continuous outcomes. The weaning success rate in the levosimendan group was considerably higher in contrast to the comparison (OR = 2.78, 95% CI 1.80-4.30; P < 0.00001; I2 = 65%), and subgroup analysis showed that there was less heterogeneity in patients after cardiac surgery (OR = 2.06, 95% CI, 1.35-3.12; P = 0.0007; I2 = 17%). In addition, the effect of levosimendan on improving weaning success rate was statistically significant only at 0.2 mcg/kg/min (OR = 2.45, 95% CI, 1.11-5.40; P = 0.03; I2 = 38%). At the same time, the 28-day or 30-day proportion of deaths in the sample receiving levosimendan also decreased (OR = 0.47, 95% CI, 0.28-0.79; P = 0.004; I2 = 73%), and the difference was statistically significant. In terms of secondary outcomes, we found that individuals undergoing levosimendan treatment had a longer duration of VA-ECMO support. CONCLUSIONS: In patients receiving VA-ECMO, levosimendan treatment considerably raised the weaning success rate and helped lower mortality. Since most of the evidence comes from retrospective studies, more randomized multicenter trials are required to verify the conclusion.

Probabilistic Dual-Space Fusion for Real-Time Human-Robot Interaction.

For robots in human environments, learning complex and demanding interaction skills from humans and responding quickly to human motions are highly desirable. A common challenge for interaction tasks is that the robot has to satisfy both the task space and the joint space constraints on its motion trajectories in real time. Few studies have addressed the issue of hyperspace constraints in human-robot interaction, whereas researchers have investigated it in robot imitation learning. In this work, we propose a method of dual-space feature fusion to enhance the accuracy of the inferred trajectories in both task space and joint space; then, we introduce a linear mapping operator (LMO) to map the inferred task space trajectory to a joint space trajectory. Finally, we combine the dual-space fusion, LMO, and phase estimation into a unified probabilistic framework. We evaluate our dual-space feature fusion capability and real-time performance in the task of a robot following a human-handheld object and a ball-hitting experiment. Our inference accuracy in both task space and joint space is superior to standard Interaction Primitives (IP) which only use single-space inference (by more than 33%); the inference accuracy of the second order LMO is comparable to the kinematic-based mapping method, and the computation time of our unified inference framework is reduced by 54.87% relative to the comparison method.

Severe fever with thrombocytopenia syndrome virus induces platelet activation and apoptosis via a reactive oxygen species-dependent pathway.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease caused by the SFTS virus (SFTSV) and with a high fatality rate. Thrombocytopenia is a major clinical manifestation observed in SFTS patients, but the underlying mechanism remains largely unclear. Here, we explored the effects of SFTSV infection on platelet function in vivo in severely infected SFTSV IFNar-/- mice and on mouse and human platelet function in vitro. Results showed that SFTSV-induced platelet clearance acceleration may be the main reason for thrombocytopenia. SFTSV-potentiated platelet activation and apoptosis were also observed in infected mice. Further investigation showed that SFTSV infection induced platelet reactive oxygen species (ROS) production and mitochondrial dysfunction. In vitro experiments revealed that administration of SFTSV or SFTSV glycoprotein (Gn) increased activation, apoptosis, ROS production, and mitochondrial dysfunction in separated mouse platelets, which could be effectively ameliorated by the application of antioxidants (NAC (N-acetyl-l-cysteine), SKQ1 (10-(6'-plastoquinonyl) decyltriphenylphosphonium) and resveratrol). In vivo experiments showed that the antioxidants partially rescued SFTSV infection-induced thrombocytopenia by improving excessive ROS production and mitochondrial dysfunction and down-regulating platelet apoptosis and activation. Furthermore, while SFTSV and Gn directly potentiated human platelet activation, it was completely abolished by antioxidants. This study revealed that SFTSV and Gn can directly trigger platelet activation and apoptosis in an ROS-MAPK-dependent manner, which may contribute to thrombocytopenia and hemorrhage during infection, but can be abolished by antioxidants.

Staged management of a large ischemic heel ulcer in a diabetes patient: a case report.

Heel ulcer is one of the severe complications of patients with diabetes mellitus, which poses a high risk for foot infection and amputation, especially in patients with peripheral arterial disease and neuropathy. Researchers have searched for new treatments for treating diabetic foot ulcers in recent years. In this case report, we demonstrated the treatment of large ischemic ulcers for the first time in a diabetic patient. The overall treatment goal of this patient was designed to improve blood supply to her diseased lower extremities and close the ulcer. This two-stage reconstruction approach resulted in an ulcer-free, stable, plantigrade foot at postoperative follow-up.

Hypertensive Disorders in Pregnancy: Global Burden From 1990 to 2019, Current Research Hotspots and Emerging Trends.

Hypertensive disorders in pregnancy (HDP) constitute a worldwide health problem for pregnant women and their infants. This study provided HDP burden over 1990 to 2019 by region and age distribution, and predicted changes in related values for the next 25 years. We then conducted an econometric analysis of the author distribution, collaborative networks, keyword burst clustering, and spatio-temporal analysis of HDP-related publications from 2012 to 2022 to access current scientific developments and hotspots. The number of pregnant women with HDP has been increasing over the past 30 years, with regional and age-stratified differences in the burden of disease. Additionally, projections suggest an increase of deaths due to maternal HDP among adolescents younger than 20 years. Current research is mostly centered on pre-eclampsia, with hot keywords including trophoblast, immune tolerance, frozen-thawed embryo transfer, aspirin, gestational diabetes association, and biomarkers. Researches on the pathological mechanism, classification, and subtypes of HDP need to be further advanced.

LncRNA NRON promotes tumorigenesis by enhancing MDM2 activity toward tumor suppressor substrates.

The E3 ligase MDM2 promotes tumor growth and progression by inducing ubiquitin-mediated degradation of P53 and other tumor-suppressing proteins. Here, we identified an MDM2-interacting lncRNA NRON, which promotes tumor formation by suppressing both P53-dependent and independent pathways. NRON binds to MDM2 and MDMX (MDM4) via two different stem-loops, respectively, and induces their heterogenous dimerization, thereby enhancing the E3 ligase activity of MDM2 toward its tumor-suppressing substrates, including P53, RB1, and NFAT1. NRON knockdown dramatically inhibits tumor cell growth in vitro and in vivo. More importantly, NRON overexpression promotes oncogenic transformation by inducing anchorage-independent growth in vitro and facilitating tumor formation in immunocompromised mice. Clinically, NRON expression is significantly associated with poor clinical outcome in breast cancer patients. Together, our data uncover a pivotal role of lncRNA that induces malignant transformation of epithelial cells by inhibiting multiple tumor suppressor proteins.

Interpretable deep learning architectures for improving drug response prediction performance: myth or reality?

MOTIVATION: Interpretable deep learning (DL) models that can provide biological insights, in addition to accurate predictions, are of great interest to the biomedical community. Recently, interpretable DL models that incorporate signaling pathways have been proposed for drug response prediction (DRP). While these models improve interpretability, it is unclear whether this comes at the cost of less accurate DRPs, or a prediction improvement can also be obtained. RESULTS: We comprehensively and systematically assessed four state-of-the-art interpretable DL models using three pathway collections to assess their ability in making accurate predictions on unseen samples from the same dataset, as well as their generalizability to an independent dataset. Our results showed that models that explicitly incorporate pathway information in the form of a latent layer perform worse compared to models that incorporate this information implicitly. However, in most evaluation setups, the best performance was achieved using a black-box multilayer perceptron, and the performance of a random forests baseline was comparable to those of the interpretable models. Replacing the signaling pathways with randomly generated pathways showed a comparable performance for the majority of the models. Finally, the performance of all models deteriorated when applied to an independent dataset. These results highlight the importance of systematic evaluation of newly proposed models using carefully selected baselines. We provide different evaluation setups and baseline models that can be used to achieve this goal. AVAILABILITY AND IMPLEMENTATION: Implemented models and datasets are provided at https://doi.org/10.5281/zenodo.7787178 and https://doi.org/10.5281/zenodo.7101665, respectively.