Non-alcoholic fatty liver disease increases the risk of biochemical recurrence in high-grade metastatic prostate cancer patients.

INTRODUCTION: Non-alcoholic fatty liver disease (NAFLD) has been reported to be helpful to identify high-risk individuals of developing prostate cancer. Our aim is to investigate the relationship between NAFLD and biochemical recurrence in metastatic prostate cancer patients. METHODS: We retrospectively investigated 602 patients with metastatic prostate cancer receiving the androgen deprivation therapy. Liver fat was estimated with liver-to-spleen ratio by computed tomography (CT) scans. The relationship between NAFLD and biochemical recurrence was investigated with Cox models. The model for biochemical recurrence was adjusted for multiple variables. RESULTS: NAFLD was significantly associated with biochemical recurrence in patients with Gleason score ≥4+3 when adjusting for each of body mass index (hazards ratio [HR] = 1.38; 95% confidence interval [CI] = 1.08-1.77; p = 0.01), visceral adipose tissue (HR = 1.36; 95% CI = 1.07-1.74; p = 0.01), hypertension (HR = 1.41; 95% CI = 1.10-1.80; p = 0.01), and diabetes mellitus (HR = 1.42; 95% CI = 1.11-1.82; p = 0.01), using age and prostate-specific antigen level as potential confounder. The 2-year biochemical recurrence rate in the Gleason score ≥4+3 patients with and without NAFLD was 84.0% (100/119) and 72.2% (130/180), respectively (p = 0.018). The median biochemical recurrence free survival of the Gleason score ≥4+3 patients with and without NAFLD were 17 and 21 months, respectively (p = 0.005). CONCLUSIONS: NAFLD is an independent risk factor for biochemical recurrence in patients with high-grade metastatic prostate cancer. If validated in prospective studies, future research should test whether treatment of NAFLD can lead to better prognosis.

A cryogenic on-chip microwave pulse generator for large-scale superconducting quantum computing.

For superconducting quantum processors, microwave signals are delivered to each qubit from room-temperature electronics to the cryogenic environment through coaxial cables. Limited by the heat load of cabling and the massive cost of electronics, such an architecture is not viable for millions of qubits required for fault-tolerant quantum computing. Monolithic integration of the control electronics and the qubits provides a promising solution, which, however, requires a coherent cryogenic microwave pulse generator that is compatible with superconducting quantum circuits. Here, we report such a signal source driven by digital-like signals, generating pulsed microwave emission with well-controlled phase, intensity, and frequency directly at millikelvin temperatures. We showcase high-fidelity readout of superconducting qubits with the microwave pulse generator. The device demonstrated here has a small footprint, negligible heat load, great flexibility to operate, and is fully compatible with today's superconducting quantum circuits, thus providing an enabling technology for large-scale superconducting quantum computers.

S3T-Net: A novel electroencephalogram signals-oriented emotion recognition model.

In this paper, a novel skipping spatial-spectral-temporal network (S3T-Net) is developed to handle intra-individual differences in electroencephalogram (EEG) signals for accurate, robust, and generalized emotion recognition. In particular, aiming at the 4D features extracted from the raw EEG signals, a multi-branch architecture is proposed to learn spatial-spectral cross-domain representations, which benefits enhancing the model generalization ability. Time dependency among different spatial-spectral features is further captured via a bi-directional long-short term memory module, which employs an attention mechanism to integrate context information. Moreover, a skip-change unit is designed to add another auxiliary pathway for updating model parameters, which alleviates the vanishing gradient problem in complex spatial-temporal network. Evaluation results show that the proposed S3T-Net outperforms other advanced models in terms of the emotion recognition accuracy, which yields an performance improvement of 0.23% , 0.13%, and 0.43% as compared to the sub-optimal model in three test scenes, respectively. In addition, the effectiveness and superiority of the key components of S3T-Net are demonstrated from various experiments. As a reliable and competent emotion recognition model, the proposed S3T-Net contributes to the development of intelligent sentiment analysis in human-computer interaction (HCI) realm.

An enhanced multimode phase imaging method based on the transport of intensity equation.

Label-free biological cell imaging relies on rapid multimode phase imaging of biological samples in natural settings. To improve image contrast, phase is encoded into intensity information using the differential interference contrast (DIC) and Zernike phase contrast (ZPC) techniques. To enable multimode contrast-enhanced observation of unstained specimens, this paper proposes an improved multimode phase imaging method based on the transport of intensity equation (TIE), which combines conventional microscopy with computational imaging. The ZPC imaging module based on adaptive aperture adjustment is applied when the quantitative phase results of biological samples have been obtained by solving the TIE. Simultaneously, a rotationally symmetric shear-based technique is used that can yield isotropic DIC. In this paper, we describe numerical simulation and optical experiments carried out to validate the accuracy and viability of this technology. The calculated Michelson contrast of the ZPC image in the resolution plate experiment increased from 0.196 to 0.394.

Efficacy and safety of percutaneous transhepatic biliary radiofrequency ablation in patients with malignant obstructive jaundice.

BACKGROUND: Percutaneous transhepatic cholangiodrainage (PTCD) and endoscopic retrograde cholangiopancreatography/endoscopic nasobiliary drainage are the most common clinical procedures for jaundice control in patients with unresectable malignant obstructive jaundice, yet the safety and effect of endobiliary radiofrequency ablation (EB-RFA) combined PTCD is rarely reported, in this article, we report our experience of EB-RFA combined PTCD in such patients. AIM: To retrospectively study the efficacy and safety of EB-RFA combined PTCD in patients with unresectable malignant obstructive jaundice. METHODS: Patients with unresectable malignant obstructive jaundice treated with EB-RFA under PTCD were selected, the bile ducts of the right posterior lobe was selected as the target bile ducts in all cases. The general conditions of all patients, preoperative tumour markers, total bilirubin (TBIL), direct bilirubin (DBIL), albumin (ALB), alkaline phosphatase (ALP), and glutamyl transferase (GGT) before and on the 7th day after the procedure, as well as perioperative complications, stent patency time and patient survival were recorded. RESULTS: All patients successfully completed the operation, TBIL and DBIL decreased significantly in all patients at the 7th postoperative day (P = 0.009 and 0.006, respectively); the values of ALB, ALP and GGT also decreased compared with the preoperative period, but the difference was not statistically significant. Perioperative biliary bleeding occurred in 2 patients, which was improved after transfusion of blood and other conservative treatments, pancreatitis appeared in 1 patient after the operation, no serious complication and death happened after operation. Except for 3 patients with loss of visits, the stent patency rate of the remaining 14 patients was 100% 71% and 29% at the 1st, 3rd, and 6th postoperative months respectively, with a median survival of 4 months. CONCLUSION: EB-RFA under PTCD in patients with unresectable malignant obstructive jaundice has a satisfactory therapeutic effect and high safety, which is worthy of further clinical practice.

A highly sensitive SERS substrate of porous membrane-Ag NPs for kidney cancer detection.

BACKGROUND: The substrate employed in surface-enhanced Raman spectroscopy (SERS) constitutes an essential element in the cancer detection methodology. In this research, we introduce a three-dimensional (3D) structured SERS substrate that integrates a porous membrane with silver nanoparticles to enhance SERS spectral signals through the utilization of the aggregation effect of silver nanoparticles. This enhancement is crucial because accurate detection results strongly depend on the intensity of specific peaks in Raman spectroscopy. A highly sensitive SERS substrate can significantly improve the accuracy of detection results. RESULTS: We collected 66 plasma samples from individuals with kidney cancer and control individuals, including both bladder cancer patients and healthy individuals. Then, we utilized substrates with and without porous membranes to acquire the SERS spectra of the samples, enabling us to evaluate the enhancement effect of our SERS substrate. The spectral analysis demonstrated enhanced peak intensities in the experimental group (with porous substrate) compared to the control group (without porous substrate). The uniformity and reproducibility of the SERS substrate are also significantly enhanced, which is very helpful for improving the accuracy of detection results. Additionally, the Principal Component Analysis-Linear Discriminant Analysis algorithm (PCA-LDA) was employed to classify the SERS spectra of both groups. In the experimental group, the classification accuracy was 98.5 % for kidney cancer, and 83.3 % for kidney and bladder cancer. Compared to the control group, it improved by 3 % and 12.6 % respectively. SIGNIFICANT: This indicates that our 3D structured SERS substrate combined with multivariate statistical algorithms PCA-LDA can not only improve the accuracy of SERS detection technology in single cancer detection, but also has great potential in multiple cancer detection. This 3D structured SERS substrate is expected to become a new auxiliary means for cancer detection.

First-Principles Study of Discharge Products and Their Stability for Lithium-Nitrogen Batteries.

Li-N2 batteries present a relatively novel approach to N2 immobilization, and an advanced N2/Li3N cycling method is introduced in this study. The low operating overpotential of metal-air batteries is quite favorable to their stable cycling performance, providing a prospect for the development of a new type of battery with extreme voltage. The battery system of Li-N2 uses N2 as the positive electrode, lithium metal as the negative electrode, and a conductive medium containing soluble lithium salts as the electrolyte. In accordance with its voltage-distribution trend, a variety of lithium-nitrogen molecule intermediates are produced during the discharge process. There is a lack of theoretical description of material changes at the microscopic level during the discharge process. In this paper, the first-principles approach is used to simulate and analyze possible material changes during the discharge process of Li-N2 batteries. The discharge process is simulated on a 4N-graphene anode substrate model, and simulations of its electrostatic potential, Density of States (DOS), HOMO (Highest Occupied Molecular Orbital) and LUMO (Lowest Unoccupied Molecular Orbital) aspects confirm that the experimentally found Li3N becomes the final stabilized product of the Li-N2 battery. It can also be seen in the density of states that graphene with adsorption of 4N transforms from semiconducting to metallic properties. In addition, the differential charge also indicates that the Li-N2 material has a strong adsorption effect on the substrate, which can play the dual role of electricity storage and nitrogen fixation.

A Single Component, Single Layer Flexile Foam Evaporator with the Higher Efficiency for Water Generation.

One of the greenest and promising ways to solve the problem of freshwater crisis is surface solar steam generation from seawater. A great number of photothermal materials with multi-component and multi-layered delicate yet complex structures often suffer from either low evaporation rate or high energy loss. Here, this work presents a single component foam evaporator with steam generation rate of up to 4.32 kg m-2 h-1 under 1 sun irradiation. The evaporator is constructed from an aniline oligomer as a single light-absorbing component, covalent linked with polyethylene glycol to form a monolithic polymer foam. Floating on the seawater, the foam has absorbance of 99.5% over the entire solar spectral range and low thermal conductivity (0.0077 W K-1m-1) that effectively retains heat in the material and at the interface. After 3 months of continuous outdoor natural sunlight irradiation, the evaporator maintains a stable and durable evaporation rate. Moreover, the materials have good mechanical properties (7.48 MPa young's modulus and 57.38% elongation at break) and excellent chemical resistance in 10 common organic solvents and aqueous solutions of pH = 1 to 14. This study provides a new system and strategy for desalination, steam power generation, treatment of polluted water and sewage, etc.

[Rapid determination of 15 N-nitrosamines in air-dried yak meat using one-step QuEChERS-gas chromatography-triple quadrupole mass spectrometry].

A method based on gas chromatography-triple quadrupole mass spectrometry (GC-MS/MS) coupled with one-step QuEChERS technique was developed for the simultaneous determination of 15 N-nitrosamines in air-dried yak meat. The hydration volume, extraction solvent, extracting salt, and cleaning material were optimized according to the characteristics of the N-nitrosamines and sample matrix. The optimized conditions were as follows: 10 mL of purified water for sample hydration, acetonitrile as the extraction solvent for the sample after hydration, 4.0 g of anhydrous MgSO4 and 1.0 g of NaCl as extracting salts, 500 mg of MgSO4+25 mg of C18+50 mg of PSA as cleaning materials. Favorable recoveries of the 15 N-nitrosamines were obtained when the extraction solution was incompletely dried. Thus, the final extract was dried to below 0.5 mL under a mild nitrogen stream and then redissolved to 0.5 mL with acetonitrile. After filtration, 200 µL of the sample was transferred to an autosampler vial for GC-MS/MS analysis. The 15 N-nitrosamines were determined using GC-MS/MS on a DB-HeavyWAX column (30 m×0.25 mm×0.25 µm) with an electron impact ion source in multiple-reaction monitoring (MRM) mode, and quantified using an external standard method. Under the optimized experimental conditions, the results showed that the calibration curves exhibited good linearities for the 15 N-nitrosamines, with correlation coefficients (r2) greater than 0.9990. The limits of detection (LODs) and the limits of quantification (LOQs) ranged from 0.05 to 0.20 µg/kg and from 0.10 to 0.50 µg/kg, respectively. At spiked levels of 1LOQ, 2LOQ, and 10LOQ, the average recoveries were 79.4%-102.1%, 80.6%-109.5%, and 83.0%-110.6%, respectively, and the relative standard deviations were in the range of 0.8%-16.0%. The low matrix effects of the 15 N-nitrosamines indicated the high sensitivity of the proposed method. The method was applied to detect representative commercial air-dried yak meat samples obtained using different processing techniques. Seven N-nitrosamines, including N-nitrosodimethylamine, N-nitrosodiisobutylamine, N-nitrosodibutylamine, N-methyl-N-phenylnitrous amide, N-ethyl-N-nitrosoaniline, N-nitrosopyrrolidine, and N-nitrosodiphenylamine were detected in all samples. The average contents of the seven N-nitrosamines was 0.08-20.18 µg/kg. The detection rates and average contents of the N-nitrosamines in cooked air-dried yak meat samples were higher than those in traditional raw air-dried yak meat samples. Compared with the manual QuEChERS method, the one-step QuEChERS method developed integrated the extraction and clean-up procedures into one single run, and the detection efficiency was considerably improved. The developed method is simple, rapid, highly sensitive, and insusceptible to human errors. Thus, it is useful for the determination of N-nitrosamines in air-dried yak meat and can be extended to the qualitative and quantitative analysis of N-nitrosamines in other meat products. It also provides method support and a data reference for the general determination of N-nitrosamines, which is of great significance for food safety.

Influence of microorganisms on flavor substances and functional components of sojae semen praeparatum during fermentation: A study integrating comparative metabolomics and high-throughput sequencing.

Sojae semen praeparatum (SSP), a fermented product known for its distinctive flavor and medicinal properties, undergoes a complex fermentation process due to the action of various microorganisms. Despite its widespread use, the effect of these microorganisms on the flavor compounds and functional components of SSP remains poorly understood. This study aimed to shed light on this aspect by identifying 20 metabolites as potential key flavor substances in SSP. Moreover, glycine and lysine were identified as crucial flavor substances. Additionally, 24 metabolites were identified as key functional components. The dominant microorganisms involved in the fermentation process were examined, revealing six genera of fungi and 12 genera of bacteria. At the species level, 16 microorganisms were identified as dominant through metagenome sequencing. Spearman correlation analysis demonstrated a strong association between dominant microorganisms and both flavor substances and functional components. Furthermore, the study validated the significance of four core functional microorganisms in improving the flavor and quality of SSP. This comprehensive exploration of functional microorganisms of SSP on key flavor substances/functional components during SSP fermentation. The study findings serve as a valuable reference for enhancing the overall flavor and quality of SSP.

Turtle peptide and its derivative peptide ameliorated DSS-induced ulcerative colitis by inhibiting inflammation and modulating the composition of the gut microbiota.

Ulcerative colitis (UC) is a recurrent intestinal disease with an increasing incidence worldwide that seriously affects the life of patients. Turtle peptide (TP) is a bioactive peptide extracted from turtles that has anti-inflammatory, antioxidant and anti-aging properties. However, studies investigating the effect of TP on the progression of UC are lacking. The aim of this study was to investigate effects and underlying mechanisms of TP and its derivative peptide GPAGPIGPV (GP-9) in alleviating UC in mice. The results showed that 500 mg/kg TP treatment significantly ameliorated colitis symptoms and oxidative stress in UC mice. TP alleviated intestinal barrier damage in UC mice by promoting mucosal repair and increasing the expression of tight junction proteins (ZO1, occludin and claudin-1). TP also modulated the composition of the gut microbiota by increasing the abundance of the beneficial bacteria Anaerotignum, Prevotellaceae_UCG-001, Alistipes, and Lachno-spiraceae_NK4A136_group and decreasing the abundance of the harmful bacteria Prevotella_9 and Parasutterella. Furthermore, we characterized the peptide composition of TP and found that GP-9 ameliorated the symptoms of dextran sodium sulfate (DSS)-induced colitis in mice by inhibiting the TLR4/NF-κB signaling pathway. In conclusion, TP and its derivative peptides ameliorated DSS-induced ulcerative colitis by inhibiting the expression of inflammatory factors and modulating the composition of the intestinal microbiota; this study provides a theoretical basis for the application of TP and its derivative peptides for their anti-inflammatory activity.

Low-abundance proteins-based label-free SERS approach for high precision detection of liver cancer with different stages.

BACKGROUND: Surface-enhanced Raman scattering (SERS) technology have unique advantages of rapid, simple, and highly sensitive in the detection of serum, it can be used for the detection of liver cancer. However, some protein biomarkers in body fluids are often present at ultra-low concentrations and severely interfered with by the high-abundance proteins (HAPs), which will affect the detection of specificity and accuracy in cancer screening based on the SERS immunoassay. Clearly, there is a need for an unlabeled SERS method based on low abundance proteins, which is rapid, noninvasive, and capable of high precision detection and screening of liver cancer. RESULTS: Serum samples were collected from 60 patients with liver cancer (27 patients with stage T1 and T2 liver cancer, 33 patients with stage T3 and T4 liver cancer) and 40 healthy volunteers. Herein, immunoglobulin and albumin were separated by immune sorption and Cohn ethanol fractionation. Then, the low abundance protein (LAPs) was enriched, and high-quality SERS spectral signals were detected and obtained. Finally, combined with the principal component analysis-linear discriminant analysis (PCA-LDA) algorithm, the SERS spectrum of early liver cancer (T1-T2) and advanced liver cancer (T3-T4) could be well distinguished from normal people, and the accuracy rate was 98.5% and 100%, respectively. Moreover, SERS technology based on serum LAPs extraction combined with the partial least square-support vector machine (PLS-SVM) successfully realized the classification and prediction of normal volunteers and liver cancer patients with different tumor (T) stages, and the diagnostic accuracy of PLS-SVM reached 87.5% in the unknown testing set. SIGNIFICANCE: The experimental results show that the serum LAPs SERS detection combined with multivariate statistical algorithms can be used for effectively distinguishing liver cancer patients from healthy volunteers, and even achieved the screening of early liver cancer with high accuracy (T1 and T2 stage). These results showed that serum LAPs SERS detection combined with a multivariate statistical diagnostic algorithm has certain application potential in early cancer screening.

Parallel wavelength-division-multiplexed signal transmission and dispersion compensation enabled by soliton microcombs and microrings.

The proliferation of computation-intensive technologies has led to a significant rise in the number of datacenters, posing challenges for high-speed and power-efficient datacenter interconnects (DCIs). Although inter-DCIs based on intensity modulation and direct detection (IM-DD) along with wavelength-division multiplexing technologies exhibit power-efficient and large-capacity properties, the requirement of multiple laser sources leads to high costs and limited scalability, and the chromatic dispersion (CD) restricts the transmission length of optical signals. Here we propose a scalable on-chip parallel IM-DD data transmission system enabled by a single-soliton Kerr microcomb and a reconfigurable microring resonator-based CD compensator. We experimentally demonstrate an aggregate line rate of 1.68 Tbit/s over a 20-km-long SMF. The extrapolated energy consumption for CD compensation of 40-km-SMFs is ~0.3 pJ/bit, which is calculated as being around 6 times less than that of the commercial 400G-ZR coherent transceivers. Our approach holds significant promise for achieving data rates exceeding 10 terabits.

Secreted clusterin inhibits tumorigenesis by modulating tumor cells and macrophages in human meningioma.

BACKGROUND: Meningioma is the most common primary intracranial tumor with a high frequency of postoperative recurrence, yet the biology of the meningioma malignancy process is still obscure. METHODS: To identify potential therapeutic targets and tumor suppressors, we performed single-cell transcriptome analysis through meningioma malignancy, which included 18 samples spanning normal meninges, benign and high-grade in situ tumors, and lung metastases, for extensive transcriptome characterization. Tumor suppressor candidate gene and molecular mechanism were functionally validated at the animal model and cellular levels. RESULTS: Comprehensive analysis and validation in mice and clinical cohorts indicated clusterin (CLU) had suppressive function for meningioma tumorigenesis and malignancy by inducing mitochondria damage and triggering type 1 interferon pathway dependent on its secreted isoform, and the inhibition effect was enhanced by TNFα as TNFα also induced type 1 interferon pathway. Meanwhile, both intra- and extracellular CLU overexpression enhanced macrophage polarization towards M1 phenotype and TNFα production, thus promoting tumor killing and phagocytosis. CONCLUSIONS: CLU might be a key brake of meningioma malignance by synchronously modulating tumor cells and their microenvironment. Our work provides comprehensive insights into meningioma malignancy and a potential therapeutic strategy.

RtNAC055 promotes drought tolerance via a stomatal closure pathway linked to methyl jasmonate/hydrogen peroxide signaling in Reaumuria trigyna.

The stomata regulate CO2 uptake and efficient water usage, thereby promoting drought stress tolerance. NAC proteins (NAM, ATAF1/2, and CUC2) participate in plant reactions following drought stress, but the molecular mechanisms underlying NAC-mediated regulation of stomatal movement are unclear. In this study, a novel NAC gene from Reaumuria trigyna, RtNAC055, was found to enhance drought tolerance via a stomatal closure pathway. It was regulated by RtMYC2 and integrated with jasmonic acid signaling and was predominantly expressed in stomata and root. The suppression of RtNAC055 could improve jasmonic acid and H2O2 production and increase the drought tolerance of transgenic R. trigyna callus. Ectopic expression of RtNAC055 in the Arabidopsis atnac055 mutant rescued its drought-sensitive phenotype by decreasing stomatal aperture. Under drought stress, overexpression of RtNAC055 in poplar promoted ROS (H2O2) accumulation in stomata, which accelerated stomatal closure and maintained a high photosynthetic rate. Drought upregulated the expression of PtRbohD/F, PtP5CS2, and PtDREB1.1, as well as antioxidant enzyme activities in heterologous expression poplars. RtNAC055 promoted H2O2 production in guard cells by directly binding to the promoter of RtRbohE, thus regulating stomatal closure. The stress-related genes RtDREB1.1/P5CS1 were directly regulated by RtNAC055. These results indicate that RtNAC055 regulates stomatal closure by maintaining the balance between the antioxidant system and H2O2 level, reducing the transpiration rate and water loss, and improving photosynthetic efficiency and drought resistance.

Prognostic Factors and Construction of Nomogram Prediction Model of Lung Cancer Patients Using Clinical and Blood Laboratory Parameters.

Objective: This work aimed to explore the prognostic risk factors of lung cancer (LC) patients and establish a line chart prediction model. Methods: A total of 322 LC patients were taken as the study subjects. They were randomly divided into a training set (n = 202) and a validation set (n = 120). Basic information and laboratory indicators were collected, and the progression-free survival (PFS) and overall survival (OS) were followed up. Single-factor and cyclooxygenase (COX) multivariate analyses were performed on the training set to construct a Nomogram prediction model, which was validated with 120 patients in the validation set, and Harrell's consistency was analyzed. Results: Single-factor analysis revealed significant differences in PFS (P<0.05) between genders, body mass index (BMI), carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), squamous cell carcinoma antigen (SCCA), treatment methods, treatment response evaluation, smoking status, presence of pericardial effusion, and programmed death ligand 1 (PD-L1) at 0 and 1-50%. Significant differences in OS (P<0.05) were observed for age, tumor location, treatment methods, White blood cells (WBC), uric acid (UA), CA125, pro-gastrin-releasing peptide (ProGRP), SCCA, cytokeratin fragment 21 (CYFRA21), and smoking status. COX analysis identified male gender, progressive disease (PD) as treatment response, and SCCA > 1.6 as risk factors for LC PFS. The consistency indices of the line chart models for predicting PFS and OS were 0.782 and 0.772, respectively. Conclusion: Male gender, treatment response of PD, and SCCA > 1.6 are independent risk factors affecting the survival of LC patients. The PFS line chart model demonstrates good concordance.

Enhanced multi-label cardiology diagnosis with channel-wise recurrent fusion.

The timely detection of abnormal electrocardiogram (ECG) signals is vital for preventing heart disease. However, traditional automated cardiology diagnostic methods have the limitation of being unable to simultaneously identify multiple diseases in a segment of ECG signals, and do not consider the potential correlations between the 12-lead ECG signals. To address these issues, this paper presents a novel network architecture, denoted as Branched Convolution and Channel Fusion Network (BCCF-Net), designed for the multi-label diagnosis of ECG cardiology to achieve simultaneous identification of multiple diseases. Among them, the BCCF-Net incorporates the Channel-wise Recurrent Fusion (CRF) network, which is designed to enhance the ability to explore potential correlation information between 12 leads. Furthermore, the utilization of the squeeze and excitation (SE) attention mechanism maximizes the potential of the convolutional neural network (CNN). In order to efficiently capture complex patterns in space and time across various scales, the multi branch convolution (MBC) module has been developed. Through extensive experiments on two public datasets with seven subtasks, the efficacy and robustness of the proposed ECG multi-label classification framework have been comprehensively evaluated. The results demonstrate the superior performance of the BCCF-Net compared to other state-of-the-art algorithms. The developed framework holds practical application in clinical settings, allowing for the refined diagnosis of cardiac arrhythmias through ECG signal analysis.

Danggui-Shaoyao-San (DSS) ameliorates the progression of osteoarthritis via suppressing the NF-κB signaling pathway: an in vitro and in vivo study combined with bioinformatics analysis.

BACKGROUND: Osteoarthritis (OA) is a common chronic age-related joint disease characterized primarily by inflammation of synovial membrane and degeneration of articular cartilage. Accumulating evidence has demonstrated that Danggui-Shaoyao-San (DSS) exerts significant anti-inflammatory effects, suggesting that it may play an important role in the treatment of knee osteoarthritis (KOA). METHODS: In the present study, DSS was prepared and analyzed by high-performance liquid chromatography (HPLC). Bioinformatics analyses were carried out to uncover the functions and possible molecular mechanisms by which DSS against KOA. Furthermore, the protective effects of DSS on lipopolysaccharide (LPS)-induced rat chondrocytes and cartilage degeneration in a rat OA model were investigated in vivo and in vitro. RESULTS: In total, 114 targets of DSS were identified, of which 60 candidate targets were related to KOA. The target enrichment analysis suggested that the NF-κB signaling pathway may be an effective mechanism of DSS. In vitro, we found that DSS significantly inhibited LPS-induced upregulation of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), interleukin-6 (IL-6), matrix metalloproteinase-3 (MMP3), and matrix metalloproteinase-13 (MMP13). Meanwhile, the degradation of collagen II was also reversed by DSS. Mechanistically, DSS dramatically suppressed LPS-induced activation of the nuclear factor kappa B (NF-κB) signaling pathway. In vivo, DSS treatment prevented cartilage degeneration in a rat OA model. CONCLUSIONS: DSS could ameliorate the progression of OA through suppressing the NF-κB signaling pathway. Our findings indicate that DSS may be a promising therapeutic approach for the treatment of KOA.

The fatty acid-related gene signature stratifies poor prognosis patients and characterizes TIME in cutaneous melanoma.

BACKGROUND: The aim of this study is to build a prognostic model for cutaneous melanoma (CM) using fatty acid-related genes and evaluate its capacity for predicting prognosis, identifying the tumor immune microenvironment (TIME) composition, and assessing drug sensitivity. METHODS: Through the analysis of transcriptional data from TCGA-SKCM and GTEx datasets, we screened for differentially expressed fatty acids-related genes (DEFAGs). Additionally, we employed clinical data from TCGA-SKCM and GSE65904 to identify genes associated with prognosis. Subsequently, utilizing all the identified prognosis-related fatty acid genes, we performed unsupervised clustering analysis using the ConsensusClusterPlus R package. We further validated the significant differences between subtypes through survival analysis and pathway analysis. To predict prognosis, we developed a LASSO-Cox prognostic signature. This signature's predictive ability was rigorously examined through multivariant Cox regression, survival analysis, and ROC curve analysis. Following this, we constructed a nomogram based on the aforementioned signature and evaluated its accuracy and clinical utility using calibration curves, cumulative hazard rates, and decision curve analysis. Using this signature, we stratified all cases into high- and low-risk groups and compared the differences in immune characteristics and drug treatment responsiveness between these two subgroups. Additionally, in this study, we provided preliminary confirmation of the pivotal role of CD1D in the TIME of CM. We analyzed its expression across various immune cell types and its correlation with intercellular communication using single-cell data from the GSE139249 dataset. RESULTS: In this study, a total of 84 DEFAGs were identified, among which 18 were associated with prognosis. Utilizing these 18 prognosis-related genes, all cases were categorized into three subtypes. Significant differences were observed between subtypes in terms of survival outcomes, the expression of the 18 DEFAGs, immune cell proportions, and enriched pathways. A LASSO-Cox regression analysis was performed on these 18 genes, leading to the development of a signature comprising 6 DEFAGs. Risk scores were calculated for all cases, dividing them into high-risk and low-risk groups. High-risk patients exhibited significantly poorer prognosis than low-risk patients, both in the training group (p < 0.001) and the test group (p = 0.002). Multivariate Cox regression analysis indicated that this signature could independently predict outcomes [HR = 2.03 (1.69-2.45), p < 0.001]. The area under the ROC curve for the training and test groups was 0.715 and 0.661, respectively. Combining risk scores with clinical factors including metastatic status and patient age, a nomogram was constructed, which demonstrated significant predictive power for 3  and 5 years patient outcomes. Furthermore, the high and low-risk subgroups displayed differences in the composition of various immune cells, including M1 macrophages, M0 macrophages, and CD8+ T cells. The low-risk subgroup exhibited higher StromalScore, ImmuneScore, and ESTIMATEScore (p < 0.001) and demonstrated better responsiveness to immune therapy for patients with PD1-positive and CTLA4-negative or positive expressions (p < 0.001). The signature gene CD1D was found to be mainly expressed in monocytes/macrophages and dendritic cells within the TIME. Through intercellular communication analysis, it was observed that cases with high CD1D expression exhibited significantly enhanced signal transductions from other immune cells to monocytes/macrophages, particularly the (HLA-A/B/C/E/F)-CD8A signaling from natural killer (NK) cells to monocytes/macrophages (p < 0.01). CONCLUSIONS: The prognostic signature constructed in this study, based on six fatty acid-related genes, exhibits strong capabilities in predicting patient outcomes, identifying the TIME, and assessing drug sensitivity. This signature can aid in patient risk stratification and provide guidance for clinical treatment strategies. Additionally, our research highlights the crucial role of CD1D in the CM's TIME, laying a theoretical foundation for future related studies.

A novel computational tool for tracking cancer energy hijacking from immune cells.

Recent studies revealed a new biological process that malignant cancer cells hijack mitochondria from nearby T cells, providing another potential mechanism for immune evasion. We further confirmed this process at the single-cell genomic level through MERCI, a novel algorithm for tracking mitochondrial (MT) transfer. Applied to human cancer samples, MERCI identified a new cancer phenotype linked to MT hijacking, correlating with rapid tumour proliferation and poor patient survival. This discovery offers insights into the limitations of current cancer immunotherapies and suggests new therapeutic avenues targeting MT transfer to enhance cancer treatment efficacy.