Utilization of chitosan nanocomposites loaded with quantum dots enables efficient and traceable DNA delivery.

Chitosan is widely employed in gene carriers due to its excellent gene loading capacity, ease of modification, and exceptional biodegradability. However, low gene delivery efficiency, high cytotoxicity, and lack of tracer biomimetic properties limit its clinical use. To address these issues, a novel biomimetic tracking gene delivery carrier, RBCm-C50kQT, was constructed by using the design scheme of cell membrane coated carbon quantum dots/chitosan. This carrier improves stability and tracking performance while embedding the cell membrane enhances biosafety. RBCm-C50kQT effectively carries and protects DNA, improving uptake and transfection efficiency with reduced cytotoxicity. It maintains strong fluorescence tracking and shows high uptake efficiencies of 83.62 % and 77.45 % in 293 T and HeLa cells, respectively, with maximum transfection efficiencies of 68.80 % and 45.47 %. This advancement supports gene therapy improvements and paves the way for future clinical applications.

Enhancing P-wave localization for accurate detection of second-degree and third-degree atrioventricular conduction blocks.

OBJECTIVE: This paper tackles the challenge of accurately detecting second-degree and third-degree atrioventricular block AVB) in electrocardiogram (ECG) signals through automated algorithms. The inaccurate detection of P-waves poses a difficulty in this process. To address this limitation, we propose a reliable method that significantly improves the performances of AVB detection by precisely localizing P-waves. APPROACH: Our proposed P-WaveNet utilized an attention mechanism to extract spatial and temporal features, and employs a BiLSTM module to capture inter-temporal dependencies within the ECG signal. To overcome the scarcity of data for second-degree and third-degree AVB (2AVB,3AVB), a mathematical approach was employed to synthesize pseudo-data. By combining P-wave positions identified by the P-WaveNet with key medical features such as RR interval rhythm and PR intervals, we established a classification rule enabling automatic AVB detection. MAIN RESULTS: The P-WaveNet achieved an F1 score of 93.62% and 91.42% for P-wave localization on the QTDB and LUDB datasets, respectively. In the BUTPDB dataset, the F1 scores for P-wave localization in ECG signals with 2AVB and 3AVB were 98.29% and 62.65%, respectively. Across two independent datasets, the AVB detection algorithm achieved F1 scores of 83.33% and 84.15% for 2AVB and 3AVB, respectively. SIGNIFICANCE: Our proposed P-WaveNet demonstrates accurate identification of P-waves in complex ECGs, significantly enhancing AVB detection efficacy. This paper's contributions stem from the fusion of medical expertise with data augmentation techniques and ECG classification. The proposed P-WaveNet demonstrates potential clinical applicability.

Dual Grain Refinement Effect for Pure Aluminum with the Addition of Micrometer-Sized TiB2 Particles.

The inefficiency of grain refinement processes has traditionally been attributed to the limited utilization of heterogeneous nucleation particles within master alloy systems, resulting in the formation of abundant inactive particles. This study aims to investigate the alternative influences of particles by incorporating external micrometer-sized TiB2 particles into the grain refinement process. Through a series of experiments, the refinement efficiency, grain refinement mechanism, and resultant microstructure of TiB2 particle-induced grain refinement specimens are comprehensively examined using various microscopy and analytical techniques, including polarization microscopy (OM), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and transmission electron microscopy (TEM). Our findings demonstrate a direct correlation between increased levels of TiB2 particles and enhanced grain refinement efficiency. Moreover, the microstructure analysis reveals the distribution of TiB2 particles along grain boundaries, forming a coating due to self-assembly phenomena, while regions with a lower particle content may exhibit irregular grain structures. DSC analysis further confirms reduced undercooling, indicating the occurrence of heterogeneous nucleation events. However, TEM observations suggest that heterogeneous nucleation is not significantly influenced by the growth restriction factor attributed to TiAl3 2DC compounds. The grain refinement mechanism involving TiB2 particles is elucidated to entail both heterogeneous nucleation and physical growth restriction effects. Specifically, a reduction in average grain size is attributed not only to heterogeneous nucleation but also to the physical growth restriction effect facilitated by the TiB2 particle coating. This study offers insights into leveraging particles that do not participate in heterogeneous nucleation within master alloy-based grain refinement systems.

Construction of intelligent response gene vector based on MOF/Fe3O4/AuNRs for tumor-targeted gene delivery.

Metal-organic frameworks (MOFs) have the potential to efficiently carry cargo due to their excellent porosity and high surface area. Nevertheless, conventional MOFs and their derivatives exhibit low efficiency in transporting nucleic acids and other small molecules, as well as having poor colloidal stability. In this study, a ZIF-90 loaded with iron oxide nanoparticles and Au nanorods was prepared, and then surface-functionalized with polyethyleneimine (PEI) to create a multifunctional nanocomposite (AFZP25k) with pH, photothermal, and magnetic responsiveness. AFZP25k can condense plasmid DNA to form AFZP25k/DNA complexes, with a maximum binding efficiency of 92.85 %. DNA release assay showed significant light and pH responsiveness, with over 80 % cumulative release after 6 h of incubation. When an external magnetic field is applied, the cellular uptake efficiency in HeLa cells reached 81.51 %, with low cytotoxicity and specific distribution. In vitro transfection experiments demonstrated a gene transfection efficiency of 44.77 % in HeLa cells. Following near-infrared irradiation, the uptake efficiency and transfection efficiency of AFZP25k in HeLa cells increased by 21.3 % and 13.59 % respectively. The findings indicate the potential of AFZP25k as an efficient and targeted gene delivery vector in cancer gene therapy.

Room-temperature spin-valve devices without spacer layers based on Fe3GaTe2 van der Waals homojunctions.

In the advancement of spintronic devices, spin valves play a critical role, especially in the sensor and information industries. The emergence of two-dimensional (2D) van der Waals (vdW) magnetic materials has opened up new possibilities for the development of high-performance spin-valve devices. However, the Curie temperature (TC) of most 2D vdW ferromagnets falls below room temperature, resulting in a scarcity of room-temperature spin-valve devices. In this study, we have prepared spin-valve devices without spacer layers based on Fe3GaTe2 vdW homojunctions and observed notable two-state magnetoresistance (MR) from 2 K to room temperature. A maximum MR of 50% surpasses some heterojunctions with spacer-layer structures and it remains 0.6% at room temperature. Furthermore, spin-valve devices exhibit favorable ohmic contact and low operating current as low as 10 nA. These findings demonstrate the enormous potential of Fe3GaTe2-based room-temperature devices and the simplified two-layer structure shows significant prospect in the context of the ongoing trend towards miniaturization of contemporary devices.

EPDR1 promotes PD-L1 expression and tumor immune evasion by inhibiting TRIM21-dependent ubiquitylation of IkappaB kinase-ß.

While immune checkpoint blockade (ICB) has shown promise for clinical cancer therapy, its efficacy has only been observed in a limited subset of patients and the underlying mechanisms regulating innate and acquired resistance to ICB of tumor cells remain poorly understood. Here, we identified ependymin-related protein 1 (EPDR1) as an important tumor-intrinsic regulator of PD-L1 expression and tumor immune evasion. Aberrant expression of EPDR1 in hepatocellular carcinoma is associated with immunosuppression. Mechanistically, EPDR1 binds to E3 ligase TRIM21 and disrupts its interaction with IkappaB kinase-b, suppressing its ubiquitylation and autophagosomal degradation and enhancing NF-κB-mediated transcriptional activation of PD-L1. Further, we validated through a mouse liver cancer model that EPDR1 mediates exhaustion of CD8+ T cells and promotes tumor progression. In addition, we observed a positive correlation between EPDR1 and PD-L1 expression in both human and mouse liver cancer samples. Collectively, our study reveals a previously unappreciated role of EPDR1 in orchestrating tumor immune evasion and cancer progression.

Cross-Modality Person Re-Identification Method with Joint-Modality Generation and Feature Enhancement.

In order to minimize the disparity between visible and infrared modalities and enhance pedestrian feature representation, a cross-modality person re-identification method is proposed, which integrates modality generation and feature enhancement. Specifically, a lightweight network is used for dimension reduction and augmentation of visible images, and intermediate modalities are generated to bridge the gap between visible images and infrared images. The Convolutional Block Attention Module is embedded into the ResNet50 backbone network to selectively emphasize key features sequentially from both channel and spatial dimensions. Additionally, the Gradient Centralization algorithm is introduced into the Stochastic Gradient Descent optimizer to accelerate convergence speed and improve generalization capability of the network model. Experimental results on SYSU-MM01 and RegDB datasets demonstrate that our improved network model achieves significant performance gains, with an increase in Rank-1 accuracy of 7.12% and 6.34%, as well as an improvement in mAP of 4.00% and 6.05%, respectively.

Room-Temperature Highly Efficient Nonvolatile Magnetization Switching by Current in van der Waals Fe3GaTe2 Devices.

The ability to manipulate magnetic states by a low electric current represents a fundamental desire in spintronics. In recent years, two-dimensional van der Waals (vdW) magnetic materials have attracted an extensive amount of attention due to their appreciable spin-orbit torque effect. However, for most known vdW ferromagnets, their relatively low Curie temperatures (TC) limit their applications. Consequently, low-power vdW spintronic devices that can operate at room temperature are in great demand. In this research, we fabricate nanodevices based on a solitary thin flake of vdW ferromagnet Fe3GaTe2, in which we successfully achieve nonvolatile and highly efficient magnetization switching by small currents at room temperature. Notably, the switching current density and the switching power dissipation are as low as 1.7 × 105 A/cm2 and 1.6 × 1013 W/m3, respectively, with an external magnetic field of 80 Oe; both are much reduced compared to those of conventional magnet/heavy metal heterostructure devices and other vdW devices.

Enhancing Person Re-Identification through Attention-Driven Global Features and Angular Loss Optimization.

To address challenges related to the inadequate representation and inaccurate discrimination of pedestrian attributes, we propose a novel method for person re-identification, which leverages global feature learning and classification optimization. Specifically, this approach integrates a Normalization-based Channel Attention Module into the fundamental ResNet50 backbone, utilizing a scaling factor to prioritize and enhance key pedestrian feature information. Furthermore, dynamic activation functions are employed to adaptively modulate the parameters of ReLU based on the input convolutional feature maps, thereby bolstering the nonlinear expression capabilities of the network model. By incorporating Arcface loss into the cross-entropy loss, the supervised model is trained to learn pedestrian features that exhibit significant inter-class variance while maintaining tight intra-class coherence. The evaluation of the enhanced model on two popular datasets, Market1501 and DukeMTMC-ReID, reveals improvements in Rank-1 accuracy by 1.28% and 1.4%, respectively, along with corresponding gains in the mean average precision (mAP) of 1.93% and 1.84%. These findings indicate that the proposed model is capable of extracting more robust pedestrian features, enhancing feature discriminability, and ultimately achieving superior recognition accuracy.

A novel insight into cancer therapy: Lipid metabolism in tumor-associated macrophages.

The tumor immune microenvironment (TIME) can limit the effectiveness and often leads to significant side effects of conventional cancer therapies. Consequently, there is a growing interest in identifying novel targets to enhance the efficacy of targeted cancer therapy. More research indicates that tumor-associated macrophages (TAMs), originating from peripheral blood monocytes generated from bone marrow myeloid progenitor cells, play a crucial role in the tumor microenvironment (TME) and are closely associated with resistance to traditional cancer therapies. Lipid metabolism alterations have been widely recognized as having a significant impact on tumors and their immune microenvironment. Lipids, lipid derivatives, and key substances in their metabolic pathways can influence the carcinogenesis and progression of cancer cells by modulating the phenotype, function, and activity of TAMs. Therefore, this review focuses on the reprogramming of lipid metabolism in cancer cells and their immune microenvironment, in which the TAMs are especially concentrated. Such changes impact TAMs activation and polarization, thereby affecting the tumor cell response to treatment. Furthermore, the article explores the potential of targeting the lipid metabolism of TAMs as a supplementary approach to conventional cancer therapies. It reviews and evaluates current strategies for enhancing efficacy through TAMs' lipid metabolism and proposes new lipid metabolism targets as potential synergistic options for chemo-radiotherapy and immunotherapy. These efforts aim to stimulate further research in this area.

A high-dose of ursodeoxycholic acid treatment alleviates liver inflammation by remodeling gut microbiota and bile acid profile in a mouse model of non-alcoholic steatohepatitis.

Ursodeoxycholic acid (UDCA) is a hydrophilic bile acid commonly used for treating cholestatic liver disease. However, its efficacy on non-alcoholic steatohepatitis (NASH) was controversial. This study aimed to investigate the impact of a high dosage of UDCA on a mouse model of NASH. Forty 6-week-old mice were fed a high-fat high-cholesterol (HFHC) diet for 12 weeks to establish a mouse model of NASH, and then divided into four groups: two groups transitioned to a normal diet, and the other two groups maintained the HFHC diet. Each group was administered a daily dosage of 300 mg/kg of UDCA or saline for a period of 8 weeks. The 16 s ribosomal RNA genes extracted from mice fecal pellets were sequenced using next-generation sequencing techniques. Serum bile acid profiles were quantified using liquid chromatography electrospray ionization tandem mass spectrometry method. The results showed that UDCA treatment ameliorated liver inflammation, without affecting liver fibrosis. UDCA treatment reduced the relative abundance of the genera Bacteroides, Parabacteroides, and Intestinimonas, whereas increased the relative abundance of the genera norank_f_Muribaculaceae and Parasutterella in the HFHC-maintaining groups. The serum levels of total bile acids and total primary bile acids increased, whereas those of endogenous primary bile acids decreased after UDCA treatment. Correlation analysis showed that primary bile acids were negatively correlated with the genera norank_f_Christensenellaceae and unclassified_f_Ruminococcaceae. In conclusion, a high dosage of UDCA can alleviate liver inflammation, probably by modifying the composition of gut microbiota and serum bile acid profiles in NASH mice.

A lightweight deep learning approach for detecting electrocardiographic lead misplacement.

Objective. Electrocardiographic (ECG) lead misplacement can result in distorted waveforms and amplitudes, significantly impacting accurate interpretation. Although lead misplacement is a relatively low-probability event, with an incidence ranging from 0.4% to 4%, the large number of ECG records in clinical practice necessitates the development of an effective detection method. This paper aimed to address this gap by presenting a novel lead misplacement detection method based on deep learning models.Approach. We developed two novel lightweight deep learning model for limb and chest lead misplacement detection, respectively. For limb lead misplacement detection, two limb leads and V6 were used as inputs, while for chest lead misplacement detection, six chest leads were used as inputs. Our models were trained and validated using the Chapman database, with an 8:2 train-validation split, and evaluated on the PTB-XL, PTB, and LUDB databases. Additionally, we examined the model interpretability on the LUDB databases. Limb lead misplacement simulations were performed using mathematical transformations, while chest lead misplacement scenarios were simulated by interchanging pairs of leads. The detection performance was assessed using metrics such as accuracy, precision, sensitivity, specificity, and Macro F1-score.Main results. Our experiments simulated three scenarios of limb lead misplacement and nine scenarios of chest lead misplacement. The proposed two models achieved Macro F1-scores ranging from 93.42% to 99.61% on two heterogeneous test sets, demonstrating their effectiveness in accurately detecting lead misplacement across various arrhythmias.Significance. The significance of this study lies in providing a reliable open-source algorithm for lead misplacement detection in ECG recordings. The source code is available athttps://github.com/wjcai/ECG_lead_check.

Multi-branch myocardial infarction detection and localization framework based on multi-instance learning and domain knowledge.

Objective. Myocardial infarction (MI) is a serious cardiovascular disease that can cause irreversible damage to the heart, making early identification and treatment crucial. However, automatic MI detection and localization from an electrocardiogram (ECG) remain challenging. In this study, we propose two models, MFB-SENET and MFB-DMIL, for MI detection and localization, respectively.Approach. The MFB-SENET model is designed to detect MI, while the MFB-DMIL model is designed to localize MI. The MI localization model employs a specialized attention mechanism to integrate multi-instance learning with domain knowledge. This approach incorporates handcrafted features and introduces a new loss function called lead-loss, to improve MI localization. Grad-CAM is employed to visualize the decision-making process.Main Results.The proposed method was evaluated on the PTB and PTB-XL databases. Under the inter-patient scheme, the accuracy of MI detection and localization on the PTB database reached 93.88% and 67.17%, respectively. The accuracy of MI detection and localization on the PTB-XL database were 94.89% and 85.83%, respectively.Significance. Our method achieved comparable or better performance than other state-of-the-art algorithms. The proposed method combined deep learning and medical domain knowledge, demonstrates effectiveness and reliability, holding promise as an efficient MI diagnostic tool to assist physicians in formulating accurate diagnoses.

HDAC6 Enhances Endoglin Expression through Deacetylation of Transcription Factor SP1, Potentiating BMP9-Induced Angiogenesis.

Histone deacetylase 6 (HDAC6) plays a crucial role in the acetylation of non-histone proteins and is notably implicated in angiogenesis, though its underlying mechanisms were previously not fully understood. This study conducted transcriptomic and proteomic analyses on vascular endothelial cells with HDAC6 knockdown, identifying endoglin (ENG) as a key downstream protein regulated by HDAC6. This protein is vital for maintaining vascular integrity and plays a complex role in angiogenesis, particularly in its interaction with bone morphogenetic protein 9 (BMP9). In experiments using human umbilical vein endothelial cells (HUVECs), the pro-angiogenic effects of BMP9 were observed, which diminished following the knockdown of HDAC6 and ENG. Western blot analysis revealed that BMP9 treatment increased SMAD1/5/9 phosphorylation, a process hindered by HDAC6 knockdown, correlating with reduced ENG expression. Mechanistically, our study indicates that HDAC6 modulates ENG transcription by influencing promoter activity, leading to increased acetylation of transcription factor SP1 and consequently altering its transcriptional activity. Additionally, the study delves into the structural role of HDAC6, particularly its CD2 domain, in regulating SP1 acetylation and subsequently ENG expression. In conclusion, the present study underscores the critical function of HDAC6 in modulating SP1 acetylation and ENG expression, thereby significantly affecting BMP9-mediated angiogenesis. This finding highlights the potential of HDAC6 as a therapeutic target in angiogenesis-related processes.

Spin Unlocked Vortex Beam Generation on Nonlinear Chiroptical Metasurfaces.

Optical vortices with spin and orbital angular momentum (SAM and OAM) states offer multiple degrees of freedom for manipulating optical fields and thus enable great potentials in optical information processing. Recently, the optical metasurface has become an important platform for vortex beam generation and steering. However, the strong spin-orbit interaction on such metasurfaces usually leads to spin locked OAM generation, which limits the complete control of the angular momentum state of light. Here, we propose to solve this constraint using geometric phase controlled nonlinear chiroptical metasurfaces. The metasurface consists of two types of plasmonic meta-atoms which have opposite handedness and exhibit a strong spin-dependent circular dichroism effect. By encoding specific phase singularities and phase gradients to different channels, we experimentally demonstrate the spin unlocked second harmonic beam steering. The proposed nonlinear chiroptical metasurfaces may have important applications in developing multifunctional nonlinear optical devices.

[Retracted] Exogenous hydrogen sulfide protects against high glucose­induced apoptosis and oxidative stress by inhibiting the STAT3/HIF­1α pathway in H9c2 cardiomyocytes.

[This retracts the article DOI: 10.3892/etm.2019.8036.].

Extracorporeal Versus Conventional Cardiopulmonary Resuscitation for In-Hospital Cardiac Arrest: A Propensity Score Matching Cohort Study.

OBJECTIVE: Comparing the effects of extracorporeal cardiopulmonary resuscitation (ECPR) and conventional cardiopulmonary resuscitation (CCPR) on outcomes in patients with in-hospital cardiac arrest (IHCA) in China. The benefits of ECPR over CCPR in patients with IHCA remain controversial. DESIGN: This article analyzed data from the BASeline Investigation of In-hospital Cardiac Arrest (BASIC-IHCA) study, which consecutively enrolled patients with IHCA from July 1, 2019, to December 31, 2020. Patients who received ECPR were selected as the case group and matched with patients who received CCPR as the control group by propensity score at a ratio of 1:4. A parallel questionnaire survey of participating hospitals was conducted, to collect data on ECPR cases from January 1, 2021 to November 30, 2021. The primary outcome was survival to discharge or 30-day survival. SETTING: We included 39 hospitals across 31 provinces in China. PATIENTS: Patients receiving cardiopulmonary resuscitation and without contraindications to ECPR were selected from the BASIC-IHCA database. Patients older than 75 years, not witnessed, or with cardiopulmonary resuscitation duration less than 10 min were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 4853 patients met the inclusion criteria before matching, with 34 undergoing ECPR (median age, 56.5 yr; 67.65% male) and 4819 underwent CCPR (median age, 59 yr; 64.52% male). There were 132 patients receiving CCPR and 33 patients receiving ECPR who were eventually matched. The ECPR group had significantly higher survival rates at discharge or 30-day survival (21.21% vs. 7.58%, p = 0.048). The ECPR group had significantly lower mortality rates (hazard ratio 0.57; 95% CI, 0.38-0.91) than the CCPR group at discharge or 30 days. Besides the BASIC-IHCA study, the volume of ECPR implementations and the survival rate of patients with ECPR (29.4% vs. 10.4%. p = 0.004) in participating hospitals significantly improved. CONCLUSIONS: ECPR may be beneficial compared with CCPR for patient survival after IHCA and should be considered for eligible patients with IHCA.

Nano-Drug Delivery Systems Targeting CAFs: A Promising Treatment for Pancreatic Cancer.

Currently, pancreatic cancer (PC) is one of the most lethal malignant tumors. PC is typically diagnosed at a late stage, exhibits a poor response to conventional treatment, and has a bleak prognosis. Unfortunately, PC's survival rate has not significantly improved since the 1960s. Cancer-associated fibroblasts (CAFs) are a key component of the pancreatic tumor microenvironment (TME). They play a vital role in maintaining the extracellular matrix and facilitating the intricate communication between cancer cells and infiltrated immune cells. Exploring therapeutic approaches targeting CAFs may reverse the current landscape of PC therapy. In recent years, nano-drug delivery systems have evolved rapidly and have been able to accurately target and precisely release drugs with little or no toxicity to the whole body. In this review, we will comprehensively discuss the origin, heterogeneity, potential targets, and recent advances in the nano-drug delivery system of CAFs in PC. We will also propose a novel integrated treatment regimen that utilizes a nano-drug delivery system to target CAFs in PC, combined with radiotherapy and immunotherapy. Additionally, we will address the challenges that this regimen currently faces.

Corrigendum: Influence of body composition assessment with bioelectrical impedance vector analysis in cancer patients undergoing surgery.

[This corrects the article DOI: 10.3389/fonc.2023.1132972.].

Layer-Number-Dependent Magnetism in the Co-Doped van der Waals Ferromagnet Fe3GaTe2.

Recently, van der Waals (vdW) antiferromagnets have been proposed to be crucial for spintronics due to their favorable properties compared to ferromagnets, including robustness against magnetic perturbation and high frequencies of spin dynamics. High-performance and energy-efficient spin functionalities often depend on the current-driven manipulation and detection of spin states, highlighting the significance of two-dimensional metallic antiferromagnets, which have not been much explored due to the lack of suitable materials. Here, we report a new metallic vdW antiferromagnet obtained from the ferromagnet Fe3GaTe2 by cobalt (Co) doping. Through the layer-number-dependent Hall resistance and magnetoresistance measurements, an evident odd-even layer-number effect has been observed in its few-layered flakes, suggesting that it could host an A-type antiferromagnetic structure. This peculiar layer-number-dependent magnetism in Co-doped Fe3GaTe2 helps unravel the complex magnetic structures in such doped vdW magnets, and our finding will enrich material candidates and spin functionalities for spintronic applications.