Dysregulated Wnt/ß-catenin signaling confers resistance to cuproptosis in cancer cells.

Cuproptosis is characterized by the aggregation of lipoylated enzymes of the tricarboxylic acid cycle and subsequent loss of iron-sulfur cluster proteins as a unique copper-dependent form of regulated cell death. As dysregulation of copper homeostasis can induce cuproptosis, there is emerging interest in exploiting cuproptosis for cancer therapy. However, the molecular drivers of cancer cell evasion of cuproptosis were previously undefined. Here, we found that cuproptosis activates the Wnt/ß-catenin pathway. Mechanistically, copper binds PDK1 and promotes its interaction with AKT, resulting in activation of the Wnt/ß-catenin pathway and cancer stem cell (CSC) properties. Notably, aberrant activation of Wnt/ß-catenin signaling conferred resistance of CSCs to cuproptosis. Further studies showed the ß-catenin/TCF4 transcriptional complex directly binds the ATP7B promoter, inducing its expression. ATP7B effluxes copper ions, reducing intracellular copper and inhibiting cuproptosis. Knockdown of TCF4 or pharmacological Wnt/ß-catenin blockade increased the sensitivity of CSCs to elesclomol-Cu-induced cuproptosis. These findings reveal a link between copper homeostasis regulated by the Wnt/ß-catenin pathway and cuproptosis sensitivity, and suggest a precision medicine strategy for cancer treatment through selective cuproptosis induction.

Anatomical Changes during Chestnut (Castanea mollissima BL.) Gall Development Stages Induced by the Gall Wasp Dryocosmus kuriphilus (Hymenoptera: Cynipidae).

This study delved into the larval development and the morphological and anatomical transformations that occur in the galls of chestnut trees (Castanea mollissima BL.) and are induced by the chestnut gall wasp Dryocosmus kuriphilus Yasumatsu (GWDK) across various stages: initial, growth, differentiation, maturity, and lignification. Chestnut galls in the five development stages were collected. Gall structural characteristics were observed with an anatomical stereomicroscope, and anatomical changes in galls were analyzed with staining and scanning electron microscope techniques. The chestnut gall wasp laid its eggs on young leaves and buds. Chestnut gall wasp parasitism caused plant tissues to form a gall chamber, with parenchyma, protective, and epidermal layers. The development of the gall structure caused by the infestation of the GWDK gall led to the weakening of the reactive oxygen species (ROS) elimination ability of the host. The accumulation of ROS led to cell wall peroxidation, resulting in structural damage and diminished host resistance, and the parenchyma layer exhibited significant nutrient supply and thickening. The thickness of the protective and epidermal layers varied notably across different growth stages. The oviposition of the chestnut gall wasp induced modifications in the original plant tissues, with gall formation being most favorable in young tissues, correlating with the maturity level of the host plant tissues. Variances in the internal structures of the galls primarily stemmed from nutrient supplementation, while those in the external structure were attributed to defensive characteristics. This research contributes a foundational understanding of gall development induced by the chestnut gall wasp in Chinese chestnut, offering valuable insights into the intricate interplay between insect infestation and plant physiology.

Tailoring local chemical fluctuation of high-entropy structures in thermoelectric materials.

In high-entropy materials, local chemical fluctuation from multiple elements inhabiting the same crystallographic site plays a crucial role in their unique properties. Using atomic-resolution chemical mapping, we identified the respective contributions of different element characteristics on the local chemical fluctuation of high-entropy structures in thermoelectric materials. Electronegativity and mass had a comparable influence on the fluctuations of constituent elements, while the radius made a slight contribution. The local chemical fluctuation was further tailored by selecting specific elements to induce large lattice distortion and strong strain fluctuation to lower lattice thermal conductivity independent of increased entropy. The chemical bond fluctuation induced by the electronegativity difference had a noticeable contribution to the composition-dependent lattice thermal conductivity in addition to the known fluctuations of mass and strain field. Our findings provide a fundamental principle for tuning local chemical fluctuation and lattice thermal conductivity in high-entropy thermoelectric materials.

Predicting epidemic threshold in complex networks by graph neural network.

To achieve precision in predicting an epidemic threshold in complex networks, we have developed a novel threshold graph neural network (TGNN) that takes into account both the network topology and the spreading dynamical process, which together contribute to the epidemic threshold. The proposed TGNN could effectively and accurately predict the epidemic threshold in homogeneous networks, characterized by a small variance in the degree distribution, such as Erdos-Rényi random networks. Usability has also been validated when the range of the effective spreading rate is altered. Furthermore, extensive experiments in ER networks and scale-free networks validate the adaptability of the TGNN to different network topologies without the necessity for retaining. The adaptability of the TGNN is further validated in real-world networks.

Deep learning based retinal vessel segmentation and hypertensive retinopathy quantification using heterogeneous features cross-attention neural network.

Retinal vessels play a pivotal role as biomarkers in the detection of retinal diseases, including hypertensive retinopathy. The manual identification of these retinal vessels is both resource-intensive and time-consuming. The fidelity of vessel segmentation in automated methods directly depends on the fundus images' quality. In instances of sub-optimal image quality, applying deep learning-based methodologies emerges as a more effective approach for precise segmentation. We propose a heterogeneous neural network combining the benefit of local semantic information extraction of convolutional neural network and long-range spatial features mining of transformer network structures. Such cross-attention network structure boosts the model's ability to tackle vessel structures in the retinal images. Experiments on four publicly available datasets demonstrate our model's superior performance on vessel segmentation and the big potential of hypertensive retinopathy quantification.

A novel doxorubicin/CTLA-4 blocker co-loaded drug delivery system improves efficacy and safety in antitumor therapy.

Doxorubicin's antitumor effectiveness may be constrained with ineffective tumor penetration, systemic adverse effects, as well as drug resistance. The co-loading of immune checkpoint inhibitors and doxorubicin into liposomes can produce synergistic benefits and address problems, including quick drug clearance, toxicity, and low drug penetration efficiency. In our previous study, we modified a nanobody targeting CTLA-4 onto liposomes (LPS-Nb36) to be an extremely potent CTLA-4 signal blocker which improve the CD8+ T-cell activity against tumors under physiological conditions. In this study, we designed a drug delivery system (LPS-RGD-Nb36-DOX) based on LPS-Nb36 that realized the doxorubicin and anti-CTLA-4 Nb co-loaded and RGD modification, and was applied to antitumor therapy. We tested whether LPS-RGD-Nb36-DOX could targets the tumor by in vivo animal photography, and more importantly, promote cytotoxic T cells proliferation, pro-inflammatory cytokine production, and cytotoxicity. Our findings demonstrated that the combination of activated CD8+ T cells with doxorubicin/anti-CTLA-4 Nb co-loaded liposomes can effectively eradicate tumor cells both in vivo and in vitro. This combination therapy is anticipated to have synergistic antitumor effects. More importantly, it has the potential to reduce the dose of chemotherapeutic drugs and improve safety.

Targeted Modulation of Redox and Immune Homeostasis in Acute Lung Injury Using a Thioether-Functionalized Dendrimer.

Acute lung injury (ALI) is the pathophysiological precursor of acute respiratory distress syndrome. It is characterized by increased oxidative stress and exaggerated inflammatory response that disrupts redox reactions and immune homeostasis in the lungs, thereby posing significant clinical challenges. In this study, an internally functionalized thioether-enriched dendrimer Sr-G4-PEG is developed, to scavenge both proinflammatory cytokines and reactive oxygen species (ROS) and restore homeostasis during ALI treatment. The dendrimers are synthesized using an efficient and orthogonal thiol-ene "click" chemistry approach that involves incorporating thioether moieties within the dendritic architectures to neutralize the ROS. The ROS scavenging of Sr-G4-PEG manifests in its capacity to sequester proinflammatory cytokines. The synergistic effects of scavenging ROS and sequestering inflammatory cytokines by Sr-G4-PEG contribute to redox remodeling and immune homeostasis, along with the modulation of the NLRP3-pyroptosis pathway. Treatment with Sr-G4-PEG enhances the therapeutic efficacy of ALIs by alleviating alveolar bleeding, reducing inflammatory cell infiltration, and suppressing the release of inflammatory cytokines. These results suggest that Sr-G4-PEG is a potent nanotechnological candidate for remodeling redox and immune homeostasis in the treatment of ALIs, demonstrating the great potential of dendrimer-based nanomedicine for the treatment of respiratory pathologies.

The impact of magnesium on shivering incidence in cardiac surgery patients: A systematic review.

Background and objective: This scientific review involves a sequential analysis of randomized trial research focused on the incidence of shivering in patients undergoing cardiac surgery. The study conducted a comprehensive search of different databases, up to the end of 2020. Only randomized trials comparing magnesium administration with either placebo or no treatment in patients expected to experience shivering were included. The primary objective was to evaluate shivering occurrence, distinguishing between patients receiving general anesthesia and those not. Secondary outcomes included serum magnesium concentrations, intubation time, post-anesthesia care unit stay, hospitalization duration, and side effects. Data collection included patient demographics and various factors related to magnesium administration. Material and methods: This scientific review analyzed 64 clinical trials meeting inclusion criteria, encompassing a total of 4303 patients. Magnesium was administered via different routes, primarily intravenous, epidural, and intraperitoneal, and compared against placebo or control. Data included demographics, magnesium dosage, administration method, and outcomes. Heterogeneity was assessed using the I2 statistic. Some studies were excluded due to unavailability of data or non-responsiveness from authors. Result: and discussion: Out of 2546 initially identified articles, 64 trials were selected for analysis. IV magnesium effectively reduced shivering, with epidural and intraperitoneal routes showing even greater efficacy. IV magnesium demonstrated cost-effectiveness and a favorable safety profile, not increasing adverse effects. The exact dose-response relationship of magnesium remains unclear. The results also indicated no significant impact on sedation, extubation time, or gastrointestinal distress. However, further research is needed to determine the optimal magnesium dose and to explore its potential effects on blood pressure and heart rate, particularly regarding pruritus prevention. Conclusion: This study highlights the efficacy of intravenous (IV) magnesium in preventing shivering after cardiac surgery. Both epidural and intraperitoneal routes have shown promising results. The safety profile of magnesium administration appears favorable, as it reduces the incidence of shivering without significantly increasing costs. However, further investigation is required to establish the ideal magnesium dosage and explore its potential effects on blood pressure, heart rate, and pruritus prevention, especially in various patient groups.

Different-grain-sized boehmite nanoparticles for stable all-solid-state lithium metal batteries.

PEO is one of the common composite polymer electrolyte vehicles; however, the presence of crystalline phase at room temperature, high interface impedance, and low oxidation resistance (<4.0 V) limit its application in stable all-solid-state lithium metal batteries. Herein, we designed a PEO-based solid polymer electrolyte (SPE) by adding boehmite nanoparticles to address the above-mentioned issues. Different-grain-sized boehmite nanoparticles were synthesized by adjusting the hydrothermal temperature. Moreover, the impacts of these distinct grain-sized boehmite nanoparticles used to fabricate boehmite/PEO polymer electrolytes (BPEs) on the performance of all-solid-state lithium metal batteries were investigated. It was found that with the increase in boehmite's grain size, BPEs show better performance. The best BPE exhibited an improved Li+ transference number (0.59), high ionic conductivity (1.25 × 10-4 S m-1), and wide electrochemical window (∼4.5 V) at 60 °C. The assembled lithium symmetric battery can stably undergo 500 hours of lithium plating/stripping at 0.1 mA cm-2. At the same time, the LiFePO4/BPE/Li battery exhibits excellent cycling stability after 100 cycles at 0.5C. This reasonable design strategy with a superior capacity retention rate (86%) demonstrates great potential in achieving high ionic conductivity and good interface stability for all-solid-state lithium metal batteries simultaneously.

A Hexanuclear Gadolinium(III)-Based Nanoprobe for Magnetic Resonance Imaging of Tumor Apoptosis.

Magnetic resonance imaging (MRI) is instrumental in the noninvasive evaluation of tumor tissues in patients subjected to chemotherapy, thereby yielding essential diagnostic data crucial for the prognosis of tumors and the formulation of therapeutic strategies. Currently, commercially available MRI contrast agents (CAs) predominantly consist of mononuclear gadolinium(III) complexes. Because there is only one Gd(III) atom per molecule, these CAs often require administration in high doses to achieve the desired contrast quality, which inevitably leads to some adverse events. Herein, we develop a six-nuclei, apoptosis-targeting T1 CA, Gd6-ZnDPA nanoprobe, which consists of a hexanuclear gadolinium nanocluster (Gd6) with an apoptosis-targeting group (ZnDPA). The amplification of Gd(III) by the hexanuclear structure generates its high longitudinal relaxivity (44.67 mM-1 s-1, 1T) and low r1/r2 ratio (0.68, 1T). Based on the Solomon-Bloembergen-Morgan (SBM) theory, this notable improvement is primarily ascribed to a long correlation tumbling time (τR). More importantly, the Gd6-ZnDPA nanoprobe shows excellent tumor apoptosis properties with an enhanced MR signal ratio (∼74%) and a long MRI imaging acquisition time window (∼48 h) in 4T1 tumor-bearing mice. This study introduces an experimental gadolinium-based CA for the potential imaging of tumor apoptosis in the context of MRI.

A high-quality chromosome-scale genome assembly of blood orange, an important pigmented sweet orange variety.

Blood orange (BO) is a rare red-fleshed sweet orange (SWO) with a high anthocyanin content and is associated with numerous health-related benefits. Here, we reported a high-quality chromosome-scale genome assembly for Neixiu (NX) BO, reaching 336.63 Mb in length with contig and scaffold N50 values of 30.6 Mb. Furthermore, 96% of the assembled sequences were successfully anchored to 9 pseudo-chromosomes. The genome assembly also revealed the presence of 37.87% transposon elements and 7.64% tandem repeats, and the annotation of 30,395 protein-coding genes. A high level of genome synteny was observed between BO and SWO, further supporting their genetic similarity. The speciation event that gave rise to the Citrus species predated the duplication event found within them. The genome-wide variation between NX and SWO was also compared. This first high-quality BO genome will serve as a fundamental basis for future studies on functional genomics and genome evolution.

Pseudo-nanostructure and trapped-hole release induce high thermoelectric performance in PbTe.

Thermoelectric materials can realize direct and mutual conversion between electricity and heat. However, developing a strategy to improve high thermoelectric performance is challenging because of strongly entangled electrical and thermal transport properties. We demonstrate a case in which both pseudo-nanostructures of vacancy clusters and dynamic charge-carrier regulation of trapped-hole release have been achieved in p-type lead telluride-based materials, enabling the simultaneous regulations of phonon and charge carrier transports. We realized a peak zT value up to 2.8 at 850 kelvin and an average zT value of 1.65 at 300 to 850 kelvin. We also achieved an energy conversion efficiency of ~15.5% at a temperature difference of 554 kelvin in a segmented module. Our demonstration shows promise for mid-temperature thermoelectrics across a range of different applications.

A low-cost and eco-friendly recombinant protein expression system using copper-containing industrial wastewater.

The development of innovative methods for highly efficient production of recombinant proteins remains a prominent focus of research in the biotechnology field, primarily due to the fact that current commercial protein expression systems rely on expensive chemical inducers, such as isopropyl ß-D-thiogalactoside (IPTG). In our study, we designed a novel approach for protein expression by creating a plasmid that responds to copper. This specialized plasmid was engineered through the fusion of a copper-sensing element with an optimized multiple cloning site (MCS) sequence. This MCS sequence can be easily customized by inserting the coding sequences of target recombinant proteins. Once the plasmid was generated, it was introduced into an engineered Escherichia coli strain lacking copA and cueO. With this modified E. coli strain, we demonstrated that the presence of copper ions can efficiently trigger the induction of recombinant protein expression, resulting in the production of active proteins. Most importantly, this expression system can directly utilize copper-containing industrial wastewater as an inducer for protein expression while simultaneously removing copper from the wastewater. Thus, this study provides a low-cost and eco-friendly strategy for the large-scale recombinant protein production. To the best of our knowledge, this is the first report on the induction of recombinant proteins using industrial wastewater.

Development of 3D Printed Biodegradable, Entirely X-ray Visible Stents for Rabbit Carotid Artery Implantation.

Biodegradable stents are considered a promising strategy for the endovascular treatment of cerebrovascular diseases. The visualization of biodegradable stents is of significance during the implantation and long-term follow-up. Endowing biodegradable stents with X-ray radiopacity can overcome the weakness of intrinsic radioparency of polymers. Hence, this work focuses on the development of an entirely X-ray visible biodegradable stent (PCL-KIO3) composed of polycaprolactone (PCL) and potassium iodate via physical blending and 3D printing. The in vitro results show that the introduction of potassium iodate makes the 3D-printed PCL stents visualizable under X-ray. So far, there is inadequate study about polymeric stent visualization in vivo. Therefore, PCL-KIO3 stents are implanted into the rabbit carotid artery to evaluate the biosafety and visibility performance. During stent deployment, the visualization of the PCL-KIO3 stent effectively helps to understand the position and dilation status of stents. At 6-month follow-up, the PCL-KIO3 stent could still be observed under X-ray and maintains excellent vessel patency. To sum up, this study demonstrates that PCL-KIO3 stent may provide a robust strategy for biodegradable stent visualization.

Superstructure-Assisted Single-Atom Catalysis on Tungsten Carbides for Bifunctional Oxygen Reactions.

Single-atom catalysis (SAC) attracts wide interest for zinc-air batteries that require high-performance bifunctional electrocatalysts for oxygen reactions. However, catalyst design is still highly challenging because of the insufficient driving force for promoting multiple-electron transfer kinetics. Herein, we report a superstructure-assisted SAC on tungsten carbides for oxygen evolution and reduction reactions. In addition to the usual single atomic sites, strikingly, we reveal the presence of highly ordered Co superstructures in the interfacial region with tungsten carbides that induce internal strain and promote bifunctional catalysis. Theoretical calculations show that the combined effects from superstructures and single atoms strongly reduce the adsorption energy of intermediates and overpotential of both oxygen reactions. The catalyst therefore presented impressive bifunctional activity with an ultralow potential gap of 0.623 V and delivered a high power density of 188.5 mW cm-2 for assembled zinc-air batteries. This work opens up new opportunities for atomic catalysis.

An Integrated Clinical and Computerized Tomography-Based Radiomic Feature Model to Separate Benign from Malignant Pleural Effusion.

INTRODUCTION: Distinguishing between malignant pleural effusion (MPE) and benign pleural effusion (BPE) poses a challenge in clinical practice. We aimed to construct and validate a combined model integrating radiomic features and clinical factors using computerized tomography (CT) images to differentiate between MPE and BPE. METHODS: A retrospective inclusion of 315 patients with pleural effusion (PE) was conducted in this study (training cohort: n = 220; test cohort: n = 95). Radiomic features were extracted from CT images, and the dimensionality reduction and selection processes were carried out to obtain the optimal radiomic features. Logistic regression (LR), support vector machine (SVM), and random forest were employed to construct radiomic models. LR analyses were utilized to identify independent clinical risk factors to develop a clinical model. The combined model was created by integrating the optimal radiomic features with the independent clinical predictive factors. The discriminative ability of each model was assessed by receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). RESULTS: Out of the total 1,834 radiomic features extracted, 15 optimal radiomic features explicitly related to MPE were picked to develop the radiomic model. Among the radiomic models, the SVM model demonstrated the highest predictive performance [area under the curve (AUC), training cohort: 0.876, test cohort: 0.774]. Six clinically independent predictive factors, including age, effusion laterality, procalcitonin, carcinoembryonic antigen, carbohydrate antigen 125 (CA125), and neuron-specific enolase (NSE), were selected for constructing the clinical model. The combined model (AUC: 0.932, 0.870) exhibited superior discriminative performance in the training and test cohorts compared to the clinical model (AUC: 0.850, 0.820) and the radiomic model (AUC: 0.876, 0.774). The calibration curves and DCA further confirmed the practicality of the combined model. CONCLUSION: This study presented the development and validation of a combined model for distinguishing MPE and BPE. The combined model was a powerful tool for assisting in the clinical diagnosis of PE patients.

Neoadjuvant Immunotherapy With Ipilimumab Plus Nivolumab in Mismatch Repair Deficient/Microsatellite Instability-High Colorectal Cancer: A Preliminary Report of Case Series.

BACKGROUND: Although ipilimumab plus nivolumab have significantly improved the survival of metastatic colorectal cancer (CRC) with mismatch repair deficient (dMMR) /microsatellite instability-high (MSI-H), the data on neoadjuvant setting is limited. PATIENTS AND METHODS: We enrolled 11 patients with advanced dMMR/MSI-H CRC. 10 patients were locally advanced and 1 was metastatic. Ten patients were treated with 1 dose of ipilimumab (1 mg/kg) and 2 doses of nivolumab (3 mg/kg), and 1 patient was treated with 1 dose of ipilimumab (1 mg/kg) and 2 doses of nivolumab (3 mg/kg) with 2 cycles. All the patients underwent surgery after immunotherapy. The aim of the study was to evaluate the safety and short-term efficacy of this strategy. RESULTS: Pathologic responses were observed in 11/11 (100%) dMMR/MSI-H tumors, with 9/11 (81.8%) achieving complete responses. Among these 9 cases with complete responses, 1 achieved a radiological noncomplete response after treatment with 1 dose of ipilimumab (1 mg/kg) and 2 doses of nivolumab (3 mg/kg), so another cycle of treatment with 1 dose of ipilimumab (1 mg/kg) and 2 doses of nivolumab (3 mg/kg) was administered, followed by surgery. The postoperative pathological evaluation was a complete response. Seven patients (63.6%) developed grade I/II adverse events. No patients developed grade III/IV adverse events or postoperative complications. CONCLUSION: Neoadjuvant immunotherapy with ipilimumab plus nivolumab induced tumor regression with a major clinical and pathological response in advanced dMMR/MSI-H CRC. Notably, patients do not achieve a complete response to neoadjuvant immunotherapy, additional neoadjuvant immunotherapy may offer benefits. Further research is needed to assess the long-term efficacy of this strategy.

Stacked deep learning approach for efficient SARS-CoV-2 detection in blood samples.

Identifying COVID-19 through blood sample analysis is crucial in managing the disease and improving patient outcomes. Despite its advantages, the current test demands certified laboratories, expensive equipment, trained personnel, and 3-4 h for results, with a notable false-negative rate of 15%-20%. This study proposes a stacked deep-learning approach for detecting COVID-19 in blood samples to distinguish uninfected individuals from those infected with the virus. Three stacked deep learning architectures, namely the StackMean, StackMax, and StackRF algorithms, are introduced to improve the detection quality of single deep learning models. To counter the class imbalance phenomenon in the training data, the Synthetic Minority Oversampling Technique (SMOTE) algorithm is also implemented, resulting in increased specificity and sensitivity. The efficacy of the methods is assessed by utilizing blood samples obtained from hospitals in Brazil and Italy. Results revealed that the StackMax method greatly boosted the deep learning and traditional machine learning methods' capability to distinguish COVID-19-positive cases from normal cases, while SMOTE increased the specificity and sensitivity of the stacked models. Hypothesis testing is performed to determine if there is a significant statistical difference in the performance between the compared detection methods. Additionally, the significance of blood sample features in identifying COVID-19 is analyzed using the XGBoost (eXtreme Gradient Boosting) technique for feature importance identification. Overall, this methodology could potentially enhance the timely and precise identification of COVID-19 in blood samples.

Integrated Transcriptomic and Proteomic Analysis Identifies Novel Regulatory Genes Associated with Plant Growth Regulator-Induced Astringency in Grape Berries.

Astringency influences the sensory characteristics and flavor quality of table grapes. We tested the astringency sensory attributes of berries and investigated the concentration of flavan-3-ols/proanthocyanidins (PAs) in skins after the application of the plant growth regulators CPPU and GA3 to the flowers and young berries of the "Summer Black" grape. Our results showed that CPPU and GA3 applications increase sensory astringency perception scores and flavan-3-ol/proanthocyanidin concentrations. Using integrated transcriptomic and proteomic analysis, differentially expressed transcripts and proteins associated with growth regulator treatment were identified, including those for flavonoid biosynthesis that contribute to the changes in sensory astringency levels. Transient overexpression of candidate astringency-related regulatory genes in grape leaves revealed that VvWRKY71, in combination with VvMYBPA1 and VvMYC1, could promote the biosynthesis of proanthocyanidins, while overexpression of VvNAC83 reduced the accumulation of proanthocyanidins. However, in transient promoter studies in Nicotiana benthamiana, VvWRKY71 repressed the promoter of VvMYBPA2, while VvNAC83 had no significant effect on the promoter activity of four PA-related genes, and VvMYBPA1 was shown to activate its own promoter. This study provides new insights into the molecular mechanisms of sensory astringency formation induced by plant growth regulators in grape berries.