ABSTRACT
The cellular thermal shift assay (CETSA) is a biophysical technique allowing direct studies of ligand binding to proteins in cells and tissues. The proteome-wide implementation of CETSA with mass spectrometry detection (MS-CETSA) has now been successfully applied to discover targets for orphan clinical drugs and hits from phenotypic screens, to identify off-targets, and to explain poly-pharmacology and drug toxicity. Highly sensitive multidimensional MS-CETSA implementations can now also access binding of physiological ligands to proteins, such as metabolites, nucleic acids, and other proteins. MS-CETSA can thereby provide comprehensive information on modulations of protein interaction states in cellular processes, including downstream effects of drugs and transitions between different physiological cell states. Such horizontal information on ligandmodulation in cells is largely orthogonal to vertical information on the levels of different proteins and therefore opens novel opportunities to understand operational aspects of cellular proteomes.
Subject(s)
Drug Development/methods , Proteome/metabolism , Electrophoretic Mobility Shift Assay , Humans , Ligands , Mass Spectrometry , Protein Binding , Proteome/chemistry , ProteomicsABSTRACT
M family proteins are critical virulence determinants of Streptococci. Streptococcus equi subsp. zooepidemicus (SEZ) are Group C streptococci that cause meningitis in animals and humans. SzM, the M protein of SEZ, has been linked to SEZ brain invasion. Here, we demonstrate that SzM is important in SEZ disruption of the blood-brain barrier (BBB). SEZ release SzM-bound membrane vesicles (MVs), and endocytosis of these vesicles by human brain endothelial microvascular cells (hBMECs) results in SzM-dependent cytotoxicity. Furthermore, administration of SzM-bound MVs disrupted the murine BBB. A CRISPR screen revealed that SzM cytotoxicity in hBMECs depends on PTEN-related activation of autophagic cell death. Pharmacologic inhibition of PTEN activity prevented SEZ disruption of the murine BBB and delayed mortality. Our data show that MV delivery of SzM to host cells plays a key role in SEZ pathogenicity and suggests that MV delivery of streptococcal M family proteins is likely a common streptococcal virulence mechanism.
Subject(s)
Autophagic Cell Death , Streptococcal Infections , Streptococcus equi , Humans , Animals , Mice , Blood-Brain Barrier , Antigens, Bacterial , Streptococcus , Endothelial CellsABSTRACT
Cumulative studies have shown that many long non-coding RNAs (lncRNAs) are crucial in a number of diseases. Predicting potential lncRNA-disease associations (LDAs) can facilitate disease prevention, diagnosis and treatment. Therefore, it is vital to develop practical computational methods for LDA prediction. In this study, we propose a novel predictor named capsule network (CapsNet)-LDA for LDA prediction. CapsNet-LDA first uses a stacked autoencoder for acquiring the informative low-dimensional representations of the lncRNA-disease pairs under multiple views, then the attention mechanism is leveraged to implement an adaptive allocation of importance weights to them, and they are subsequently processed using a CapsNet-based architecture for predicting LDAs. Different from the conventional convolutional neural networks (CNNs) that have some restrictions with the usage of scalar neurons and pooling operations. the CapsNets use vector neurons instead of scalar neurons that have better robustness for the complex combination of features and they use dynamic routing processes for updating parameters. CapsNet-LDA is superior to other five state-of-the-art models on four benchmark datasets, four perturbed datasets and an independent test set in the comparison experiments, demonstrating that CapsNet-LDA has excellent performance and robustness against perturbation, as well as good generalization ability. The ablation studies verify the effectiveness of some modules of CapsNet-LDA. Moreover, the ability of multi-view data to improve performance is proven. Case studies further indicate that CapsNet-LDA can accurately predict novel LDAs for specific diseases.
Subject(s)
RNA, Long Noncoding , RNA, Long Noncoding/genetics , Neural Networks, ComputerABSTRACT
In the electrocatalytic CO2 reduction reaction (CO2RR), metal catalysts with an oxidation state generally demonstrate more favorable catalytic activity and selectivity than their corresponding metallic counterparts. However, the persistence of oxidative metal sites under reductive potentials is challenging since the transition to metallic states inevitably leads to catalytic degradation. Herein, a thorough review of research on oxidation-state stabilization in the CO2RR is presented, starting from fundamental concepts and highlighting the importance of oxidation state stabilization while revealing the relevance of dynamic oxidation states in product distribution. Subsequently, the functional mechanisms of various oxidation-state protection strategies are explained in detail, and in situ detection techniques are discussed. Finally, the prevailing and prospective challenges associated with oxidation-state protection research are discussed, identifying innovative opportunities for mechanistic insights, technology upgrades, and industrial platforms to enable the commercialization of the CO2RR.
ABSTRACT
Cannabinoids modulate dopamine (DA) transmission and DA-related behavior, which has been thought to be mediated initially by activation of cannabinoid CB1 receptors (CB1Rs) on GABA neurons. However, there is no behavioral evidence supporting it. In contrast, here we report that CB1Rs are also expressed in a subset of DA neurons and functionally underlie cannabinoid action in male and female mice. RNAscope in situ hybridization (ISH) assays demonstrated CB1 mRNA in tyrosine hydroxylase (TH)-positive DA neurons in the ventral tegmental area (VTA) and glutamate decarboxylase 1 (GAD1)-positive GABA neurons. The CB1R-expressing DA neurons were located mainly in the middle portion of the VTA with the number of CB1-TH colocalization progressively decreasing from the medial to the lateral VTA. Triple-staining assays indicated CB1R mRNA colocalization with both TH and vesicular glutamate transporter 2 (VgluT2, a glutamate neuronal marker) in the medial VTA close to the midline of the brain. Optogenetic activation of this population of DA neurons was rewarding as assessed by optical intracranial self-stimulation. Δ9-tetrahydrocannabinol (Δ9-THC) or ACEA (a selective CB1R agonist) dose-dependently inhibited optical intracranial self-stimulation in DAT-Cre control mice, but not in conditional knockout mice with the CB1R gene absent in DA neurons. In addition, deletion of CB1Rs from DA neurons attenuated Δ9-THC-induced reduction in DA release in the NAc, locomotion, and anxiety. Together, these findings indicate that CB1Rs are expressed in a subset of DA neurons that corelease DA and glutamate, and functionally underlie cannabinoid modulation of DA release and DA-related behavior.SIGNIFICANCE STATEMENT Cannabinoids produce a series of psychoactive effects, such as aversion, anxiety, and locomotor inhibition in rodents. However, the cellular and receptor mechanisms underlying these actions are not fully understood. Here we report that CB1 receptors are expressed not only in GABA neurons but also in a subset of dopamine neurons, which are located mainly in the medial VTA close to the midline of the midbrain and corelease dopamine and glutamate. Optogenetic activation of these dopamine neurons is rewarding, which is dose-dependently inhibited by cannabinoids. Selective deletion of CB1 receptor from dopamine neurons blocked cannabinoid-induced aversion, hypoactivity, and anxiolytic effects. These findings demonstrate that dopaminergic CB1 receptors play an important role in mediating cannabinoid action.
Subject(s)
Anti-Anxiety Agents , Cannabinoids , Female , Mice , Male , Animals , Cannabinoids/pharmacology , Dopaminergic Neurons/physiology , Anti-Anxiety Agents/pharmacology , Dronabinol/pharmacology , Dopamine/physiology , Receptors, Cannabinoid , Ventral Tegmental Area/physiology , Receptors, Dopamine , Mice, Knockout , Glutamic Acid/pharmacology , RNA, Messenger , Receptor, Cannabinoid, CB1/geneticsABSTRACT
RNA-protein interaction (RPI) is crucial to the life processes of diverse organisms. Various researchers have identified RPI through long-term and high-cost biological experiments. Although numerous machine learning and deep learning-based methods for predicting RPI currently exist, their robustness and generalizability have significant room for improvement. This study proposes LPI-MFF, an RPI prediction model based on multi-source information fusion, to address these issues. The LPI-MFF employed protein-protein interactions features, sequence features, secondary structure features, and physical and chemical properties as the information sources with the corresponding coding scheme, followed by the random forest algorithm for feature screening. Finally, all information was combined and a classification method based on convolutional neural networks is used. The experimental results of fivefold cross-validation demonstrated that the accuracy of LPI-MFF on RPI1807 and NPInter was 97.60% and 97.67%, respectively. In addition, the accuracy rate on the independent test set RPI1168 was 84.9%, and the accuracy rate on the Mus musculus dataset was 90.91%. Accordingly, LPI-MFF demonstrated greater robustness and generalization than other prevalent RPI prediction methods.
Subject(s)
Deep Learning , RNA, Long Noncoding , Animals , Mice , RNA, Long Noncoding/chemistry , Random Forest , Neural Networks, Computer , Machine Learning , Computational Biology/methodsABSTRACT
Traditional methods for the detection of pathogenic bacteria are time-consuming, less efficient, and sensitive, which affects infection control and bungles illness. Therefore, developing a method to remedy these problems is very important in the clinic to diagnose the pathogenic diseases and guide the rational use of antibiotics. Here, microfluidic electrochemical integrated sensor (MEIS) has been investigated, functionally for rapid, efficient separation and sensitive detection of pathogenic bacteria. Three-dimensional macroporous PDMS and Au nanotube-based electrode are successfully assembled into the modeling microchip, playing the functions of "3D chaotic flow separator" and "electrochemical detector," respectively. The 3D chaotic flow separator enhances the turbulence of the fluid, achieving an excellent bacteria capture efficiency. Meanwhile, the electrochemical detector provides a quantitative signal through enzyme-linked immunoelectrochemistry with improved sensitivity. The microfluidic electrochemical integrated sensor could successfully isolate Candida albicans (C. albicans) in the range of 30-3,000,000 CFU in the saliva matrix with over 95% capture efficiency and sensitively detect C. albicans in 1 h in oral saliva samples. The integrated device demonstrates great potential in the diagnosis of oral candidiasis and is also applicable in the detection of other pathogenic bacteria.
Subject(s)
Candida albicans , Electrochemical Techniques , Candida albicans/isolation & purification , Electrochemical Techniques/instrumentation , Microfluidic Analytical Techniques/instrumentation , Saliva/microbiology , Saliva/chemistry , Electrodes , Humans , Gold/chemistryABSTRACT
Herein, we synthesized anemone-like copper-based metal-organic frameworks (MOFs) loaded with gold-palladium nanoparticles (AuPd@Cu-MOFs) and polyethylenimine-reduced graphene oxide/gold-silver nanosheet composites (PEI-rGO/AuAg NSs) for the first time to construct the sensor and to detect T-2 toxin (T-2) using triple helix molecular switch (THMS) and signal amplification by swing-arm robot. The aptasensor used PEI-rGO/hexagonal AuAg NSs as the electrode modification materials and anemone-like AuPd@Cu-MOFs as the signal materials. The prepared PEI-rGO/hexagonal AuAg NSs had a large specific surface area, excellent electrical conductivity, and good stability, which successfully improved the electrochemical performance of the sensors. The AuPd@Cu-MOFs with high porosity provided a great deal of attachment sites for the signaling molecule thionine (Thi), thereby increasing the signal response. The aptasensor developed in this study demonstrated a remarkable detection limit of 0.054 fg mL-1 under optimized conditions. Furthermore, the successful detection of T-2 in real samples was achieved using the fabricated sensor. The simplicity of the THMS-based method, which entails modifying the aptamer sequence, allows for easy adaptation to different target analytes. Thus, the sensor holds immense potential for applications in quality supervision and food safety.
Subject(s)
Anemone , Aptamers, Nucleotide , Biosensing Techniques , Graphite , Metal Nanoparticles , Metal-Organic Frameworks , Robotics , T-2 Toxin , Metal-Organic Frameworks/chemistry , Copper/chemistry , Metal Nanoparticles/chemistry , Aptamers, Nucleotide/chemistry , Palladium , Graphite/chemistry , Gold/chemistry , Electrochemical Techniques/methods , Limit of Detection , Biosensing Techniques/methodsABSTRACT
BACKGROUND: Previous studies, including Mendelian randomization (MR), have demonstrated type 2 diabetes (T2D) and glycemic traits are associated with increased risk of metabolic dysfunction-associated steatotic liver disease (MASLD). However, few studies have explored the underlying pathway, such as the role of iron homeostasis. METHODS: We used a two-step MR approach to investigate the associations of genetic liability to T2D, glycemic traits, iron biomarkers, and liver diseases. We analyzed summary statistics from various genome-wide association studies of T2D (n = 933,970), glycemic traits (n ≤ 209,605), iron biomarkers (n ≤ 246,139), MASLD (n ≤ 972,707), and related biomarkers (alanine aminotransferase (ALT) and proton density fat fraction (PDFF)). Our primary analysis was based on inverse-variance weighting, followed by several sensitivity analyses. We also conducted mediation analyses and explored the role of liver iron in post hoc analysis. RESULTS: Genetic liability to T2D and elevated fasting insulin (FI) likely increased risk of liver steatosis (ORliability to T2D: 1.14 per doubling in the prevalence, 95% CI: 1.10, 1.19; ORFI: 3.31 per log pmol/l, 95% CI: 1.92, 5.72) and related biomarkers. Liability to T2D also likely increased the risk of developing liver cirrhosis. Genetically elevated ferritin, serum iron, and liver iron were associated with higher risk of liver steatosis (ORferritin: 1.25 per SD, 95% CI 1.07, 1.46; ORliver iron: 1.15 per SD, 95% CI: 1.05, 1.26) and liver cirrhosis (ORserum iron: 1.31, 95% CI: 1.06, 1.63; ORliver iron: 1.34, 95% CI: 1.07, 1.68). Ferritin partially mediated the association between FI and liver steatosis (proportion mediated: 7%, 95% CI: 2-12%). CONCLUSIONS: Our study provides credible evidence on the causal role of T2D and elevated insulin in liver steatosis and cirrhosis risk and indicates ferritin may play a mediating role in this association.
Subject(s)
Biomarkers , Diabetes Mellitus, Type 2 , Homeostasis , Iron , Liver Cirrhosis , Mendelian Randomization Analysis , Humans , Diabetes Mellitus, Type 2/genetics , Iron/blood , Iron/metabolism , Biomarkers/blood , Liver Cirrhosis/genetics , Fatty Liver/genetics , Genome-Wide Association Study , Blood Glucose/metabolismABSTRACT
Iron oxide nanoparticles (IONPs) have garnered significant attention as a promising platform for reactive oxygen species (ROS)-dependent disease treatment, owing to their remarkable biocompatibility and Fenton catalytic activity. However, the low catalytic activity of IONPs is a major hurdle in their clinical translation. To overcome this challenge, IONPs of different compositions are examined for their Fenton reaction under pharmacologically relevant conditions. The results show that wüstite (FeO) nanoparticles exhibit higher catalytic activity than magnetite (Fe3 O4 ) or maghemite (γ-Fe2 O3 ) of matched size and coating, despite having a similar surface oxidation state. Further analyses suggest that the high catalytic activity of wüstite nanoparticles can be attributed to the presence of internal low-valence iron (Fe0 and Fe2+ ), which accelerates the recycling of surface Fe3+ to Fe2+ through intraparticle electron transport. Additionally, ultrasmall wüstite nanoparticles are generated by tuning the thermodecomposition-based nanocrystal synthesis, resulting in a Fenton reaction rate 5.3 times higher than that of ferumoxytol, an FDA-approved IONP. Compared with ferumoxytol, wüstite nanoparticles substantially increase the level of intracellular ROS in mouse mammary carcinoma cells. This study presents a novel mechanism and pivotal improvement for the development of highly efficient ROS-inducing nanozymes, thereby expanding the horizons for their therapeutic applications.
Subject(s)
Ferrosoferric Oxide , Nanoparticles , Mice , Animals , Electron Transport , Reactive Oxygen Species , Ferric Compounds/chemistry , Ferrous CompoundsABSTRACT
Flexible composite polymer electrolytes (CPEs) with inorganic electrolyte fillers dispersed in polymer electrolytes integrate the merits of the polymer and inorganic electrolytes and have attracted much attention in recent years. In order to increase the electrochemical performance, especially the low lithium (Li)-ion transference number in traditional dual-ion Li salt-containing CPEs, single-ion conductive CPEs are synthesized with a single-ion polymer conductor (SIPC) as the matrix and Li6.4 La3 Zr1.4 Ta0.6 O12 (LLZTO) particles as the active fillers. The single-ion conductive CPEs show a high Li-ion transference number (up to 0.96), high room-temperature (RT) ionic conductivity (>1.0 × 10-4 S cm-1 ), wide electrochemical stability window (>5.0 V, vs Li/Li+ ), and excellent long-term cycling stability with Li metal at RT (3200 h). Based on the SIPC-LLZTO CPE, the solid-state lithium metal batteries with LiFePO4 - and LiCoO2 -based cathodes deliver average discharge capacities of 159 mAh g-1 for 600 cycles and 119 mAh g-1 for 200 cycles at RT, respectively. This study sheds light on the design of high-performance CPEs for next-generation solid-state lithium metal batteries.
ABSTRACT
The use of 2D materials to produce hydrogen (H2 ) fuel via photocatalytic water splitting has been intensively studied. However, the simultaneous fulfillment of the three essential requirements-high photon utilization, rapid carrier transfer, and low-barrier redox reactions-for wide-pH-range production of H2 still poses a significant challenge with no additional modulation. By employing the first-principles calculations, it has been observed that the Janus ZnXY2 structures (X = Si/Ge/Sn, Y = S/Se/Te) exhibit significantly enhanced built-in electric fields (0.20-0.36 eV Å-1 ), which address the limitations intrinsically. Compared to conventional Janus membranes, the ductile ZnSnSe2 and ZnSnTe2 monolayers have stronger regulation of electric fields, resulting in improved electron mobility and excitonic nature (Ebinding = 0.50/0.35 eV). Both monolayers exhibit lower energy barriers of hydrogen evolution reaction (HER, 0.98/0.86 eV, pH = 7) and resistance to photocorrosion across pH 0-7. Furthermore, the 1% tensile strain can further boost visible light utilization and intermediate absorption. The optimal AC-type bilayer stacking configuration is conducive to enhancing electric fields for photocatalysis. Overall, Janus ZnXY2 membranes overcome the major challenges faced by conventional 2D photocatalysts via intrinsic polarization and external amelioration, enabling efficient and controllable photocatalysis without the need for doping or heterojunctions.
ABSTRACT
With the development of electric vehicles, exploiting anode materials with high capacity and fast charging capability is an urgent requirement for lithium-ion batteries (LIBs). Borophene, with the merits of high capacity, high electronic conductivity and fast diffusion kinetics, holds great potential as anode for LIBs. However, it is difficult to fabricate for the intrinsic electron-deficiency of boron atom. Herein, heterogeneous-structured MoB2 (h-MoB2) with amorphous shell and crystalline core, is prepared by solid phase molten salt method. As demonstrated, crystalline core can encapsulate the honeycomb borophene within two adjacent Mo atoms, and amorphous shell can accommodate more lithium ions to strengthen the lithium storage capacity and diffusion kinetics. According to theoretical calculations, the lithium adsorption energy in MoB2 is about -2.7 eV, and the lithium diffusion energy barrier in MoB2 is calculated to be 0.199 eV, guaranteeing the enhanced adsorption capability and fast diffusion kinetic behavior of Li+ ions. As a result, h-MoB2 anode presents high capacity of 798 mAh g-1 at 0.1 A g-1, excellent rate performance of 183 mAh g-1 at 5 A g-1 and long-term cyclic stability for 1200 cycles. This work may inspire ideas for the fabrication of borophene analogs and two-dimensional metal borides.
ABSTRACT
SUMMARY: Limited by spatial resolution and visual contrast, bone scintigraphy interpretation is susceptible to subjective factors, which considerably affects the accuracy and repeatability of lesion detection and anatomical localization. In this work, we design and implement an end-to-end multi-task deep learning model to perform automatic lesion detection and anatomical localization in whole-body bone scintigraphy. A total of 617 whole-body bone scintigraphy cases including anterior and posterior views were retrospectively analyzed. The proposed semi-supervised model consists of two task flows. The first one, the lesion segmentation flow, received image patches and was trained in a supervised way. The other one, skeleton segmentation flow, was trained on as few as five labeled images in conjunction with the multi-atlas approach, in a semi-supervised way. The two flows joint in their encoder layers so each flow can capture more generalized distribution of the sample space and extract more abstract deep features. The experimental results show that the architecture achieved the highest precision in the finest bone segmentation task in both anterior and posterior images of whole-body scintigraphy. Such an end-to-end approach with very few manual annotation requirement would be suitable for algorithm deployment. Moreover, the proposed approach reliably balances unsupervised labels construction and supervised learning, providing useful insight for weakly labeled image analysis. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Subject(s)
Deep Learning , Retrospective Studies , Image Processing, Computer-Assisted/methods , Algorithms , Radionuclide Imaging , Supervised Machine LearningABSTRACT
BACKGROUND: Fatigue is one of the most common neurological symptoms reported post coronavirus disease 2019 (COVID-19) infection. In order to establish effective early intervention strategies, more emphasis should be placed on the correlation between fatigue and cortical neurophysiological changes, especially in healthcare workers, who are at a heightened risk of COVID-19 infection. METHODS: A prospective cohort study was conducted involving 29 COVID-19 medical workers and 24 healthy controls. The assessment included fatigue, sleep and health quality, psychological status, and physical capacity. Functional near-infrared spectroscopy (fNIRS) was employed to detect activation of brain regions. Bilateral primary motor cortex (M1) excitabilities were measured using single- and paired-pulse transcranial magnetic stimulation. Outcomes were assessed at 1, 3, and 6 months into the disease course. RESULTS: At 1-month post-COVID-19 infection, 37.9% of patients experienced severe fatigue symptoms, dropping to 10.3% at 3 months. Interestingly, the remarkable decreased activation/excitability of bilateral prefrontal lobe (PFC) and M1 were closely linked to fatigue symptoms after COVID-19. Notably, greater increase in M1 region excitability correlated with more significant fatigue improvement. Re-infected patients exhibited lower levels of brain activation and excitability compared to single-infection patients. CONCLUSIONS: Both single infection and reinfection of COVID-19 lead to decreased activation and excitability of the PFC and M1. The degree of excitability improvement in the M1 region correlates with a greater recovery in fatigue. Based on these findings, targeted interventions to enhance and regulate the excitability of M1 may represent a novel strategy for COVID-19 early rehabilitation. TRIAL REGISTRATION: The Ethics Review Committee of Xijing Hospital, No. KY20232051-F-1; www.chictr.org.cn , ChiCTR2300068444.
Subject(s)
COVID-19 , Fatigue , Health Personnel , Motor Cortex , Prefrontal Cortex , Transcranial Magnetic Stimulation , Humans , COVID-19/physiopathology , Fatigue/physiopathology , Male , Female , Longitudinal Studies , Adult , Prefrontal Cortex/physiopathology , Prefrontal Cortex/diagnostic imaging , Motor Cortex/physiopathology , Middle Aged , SARS-CoV-2/isolation & purification , Prospective Studies , Spectroscopy, Near-Infrared , Cohort StudiesABSTRACT
BACKGROUND AND OBJECTIVE: According to the Barcelona Clinic Liver Cancer (BCLC) algorithm, tumor burden and liver function, but not tumor biology, are the key factors in determining tumor staging and treatment modality, and evaluating treatment prognosis. The serum α-fetoprotein (AFP) level is an important characteristic of hepatocellular carcinoma (HCC) biology, and we aimed to evaluate its prognostic value for patients undergoing liver resection of early-stage HCC. METHODS: Patients who underwent curative liver resection for early-stage HCC were identified from a multi-institutional database. Patients were divided into three groups according to preoperative AFP levels: low (< 400 ng/mL), high (400-999 ng/mL), and extremely-high (≥ 1000 ng/mL) AFP groups. Overall survival (OS) and recurrence rates were compared among these three groups. RESULTS: Among 1284 patients, 720 (56.1%), 262 (20.4%), and 302 (23.5%) patients had preoperative low, high, and extremely-high AFP levels, respectively. The cumulative 5-year OS and recurrence rates were 71.3 and 38.9% among patients in the low AFP group, 66.3 and 48.5% in the high AFP group, and 45.7 and 67.2% in the extremely-high AFP group, respectively (both p < 0.001). Multivariate Cox regression analysis identified both high and extremely-high AFP levels to be independent risk factors of OS (hazard ratio [HR] 1.275 and 1.978, 95% confidence interval [CI] 1.004-1.620 and 1.588-2.464, respectively; p = 0.047 and p < 0.001, respectively) and recurrence (HR 1.290 and 2.050, 95% CI 1.047-1.588 and 1.692-2.484, respectively; p = 0.017 and p < 0.001, respectively). CONCLUSIONS: This study demonstrated the important prognostic value of preoperative AFP levels among patients undergoing resection for early-stage HCC. Incorporating AFP to prognostic estimation of the BCLC algorithm can help guide individualized risk stratification and identify neoadjuvant/adjuvant treatment necessity.
Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Humans , Carcinoma, Hepatocellular/pathology , Prognosis , Liver Neoplasms/pathology , alpha-Fetoproteins/analysis , Neoplasm Staging , Biology , Retrospective Studies , Neoplasm Recurrence, LocalABSTRACT
BACKGROUND: Hepatic pedicle clamping (HPC) is frequently utilized during hepatectomy to reduce intraoperative bleeding and diminish the need for intraoperative blood transfusion (IBT). The long-term prognostic implications of HPC following hepatectomy for hepatocellular carcinoma (HCC) remain under debate. This study aims to elucidate the association between HPC and oncologic outcomes after HCC resection, stratified by whether IBT was administered. PATIENTS AND METHODS: Prospectively collected data on patients with HCC who underwent curative resection from a multicenter database was studied. Patients were stratified into two cohorts on the basis of whether IBT was administered. The impact of HPC on long-term overall survival (OS) and recurrence-free survival (RFS) between the two cohorts was assessed by univariable and multivariable Cox regression analyses. RESULTS: Of 3362 patients, 535 received IBT. In the IBT cohort, using or not using HPC showed no significant difference in OS and RFS outcomes (5-year OS and RFS rates 27.9% vs. 24.6% and 13.8% vs. 12.0%, P = 0.810 and 0.530). However, in the non-IBT cohort of 2827 patients, the HPC subgroup demonstrated significantly decreased OS (5-year 45.9% vs. 56.5%, P < 0.001) and RFS (5-year 24.7% vs. 33.3%, P < 0.001) when compared with the subgroup without HPC. Multivariable Cox regression analysis identified HPC as an independent risk factor of OS and RFS [hazard ratios (HR) 1.16 and 1.12, P = 0.024 and 0.044, respectively] among patients who did not receive IBT. CONCLUSIONS: The impact of HPC on the oncological outcomes following hepatectomy for patients with HCC differed significantly whether IBT was administered, and HPC adversely impacted on long-term survival for patients without receiving IBT during hepatectomy.
Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Humans , Carcinoma, Hepatocellular/surgery , Hepatectomy , Liver Neoplasms/surgery , Constriction , Retrospective Studies , Prognosis , Blood TransfusionABSTRACT
BACKGROUND: To investigate the correlation between triglyceride glucose index (TyG) and collateral circulation in patients with chronic total occlusion (CTO) of coronary arteries in different glucose metabolic states. METHODS: A total of 681 patients who underwent coronary angiography between January 2020 and December 2021 to determine the presence of CTO lesions in at least one major coronary artery were retrospectively included in this study. Patients were categorized into a group with poor collateral circulation formation (Rentrop grade 0-1, n = 205) and a group with good collateral circulation formation (Rentrop grade 2-3, n = 476) according to the Rentrop scale. They were also categorized according to their glucose metabolism status: normal glucose regulation (NGR) (n = 139), prediabetes mellitus (Pre-DM) (n = 218), and diabetes mellitus (DM) (n = 324). Correlation between TyG index and collateral circulation formation was analyzed by logistic regression analysis and receiver operating characteristic (ROC) curves. RESULTS: Among patients with CTO, TyG index was significantly higher in the group with poor collateral circulation formation than in the group with good collateral circulation formation. Logistic regression analysis showed that TyG index was an independent risk factor for poor collateral circulation formation (OR 5.104, 95% CI 3.323-7.839, P < 0.001). The accuracy of TyG index in predicting collateral circulation formation was evaluated by the ROC curve, which had an area under the curve of 0.779 (95% CI 0.738-0.820, P < 0.001). The restrictive cubic spline curves showed that the risk of poor collateral circulation formation in the Pre-DM and DM groups was initially flat and finally increased rapidly, except for the NGR group. TyG index was significantly associated with an increased risk of poor collateral circulation formation in the Pre-DM and DM groups. CONCLUSIONS: TyG index was significantly associated with the risk of poor collateral circulation formation in patients with CTO, especially those with Pre-DM and DM.
Subject(s)
Coronary Occlusion , Coronary Vessels , Humans , Coronary Vessels/diagnostic imaging , Glucose , Retrospective Studies , Triglycerides , Collateral Circulation/physiology , Coronary Occlusion/diagnostic imaging , Blood Glucose , Coronary CirculationABSTRACT
High-grade B-cell lymphoma (HGBCL), the subtype of non-Hodgkin lymphoma, to be relapsed or refractory in patients after initial therapy or salvage chemotherapy. Dual dysregulation of MYC and BCL2 is one of the important pathogenic mechanisms. Thus, combined targeting of MYC and BCL2 appears to be a promising strategy. Dihydroorotate dehydrogenase (DHODH) is the fourth rate-limiting enzyme for the de novo biosynthesis of pyrimidine. It has been shown to be a potential therapeutic target for multiple diseases. In this study, the DHODH inhibitor brequinar exhibited growth inhibition, cell cycle blockade, and apoptosis promotion in HGBCL cell lines with MYC and BCL2 rearrangements. The combination of brequinar and BCL2 inhibitors venetoclax had a synergistic inhibitory effect on the survival of DHL cells through different pathways. Venetoclax could upregulate MCL-1 and MYC expression, which has been reported as a resistance mechanism of BCL2 inhibitors. Brequinar downregulated MCL-1 and MYC, which could potentially overcome drug resistance to venetoclax in HGBCL cells. Furthermore, brequinar could downregulate a broad range of genes, including ribosome biosynthesis genes, which might contribute to its anti-tumor effects. In vivo studies demonstrated synergetic tumor growth inhibition in xenograft models with brequinar and venetoclax combination treatment. These results provide preliminary evidence for the rational combination of DHODH and BCL2 blockade in HGBCL with abnormal MYC and BCL2.
Subject(s)
Bridged Bicyclo Compounds, Heterocyclic , Dihydroorotate Dehydrogenase , Drug Synergism , Oxidoreductases Acting on CH-CH Group Donors , Proto-Oncogene Proteins c-bcl-2 , Proto-Oncogene Proteins c-myc , Sulfonamides , Xenograft Model Antitumor Assays , Humans , Animals , Proto-Oncogene Proteins c-bcl-2/antagonists & inhibitors , Proto-Oncogene Proteins c-bcl-2/genetics , Proto-Oncogene Proteins c-bcl-2/metabolism , Mice , Sulfonamides/pharmacology , Sulfonamides/therapeutic use , Bridged Bicyclo Compounds, Heterocyclic/pharmacology , Bridged Bicyclo Compounds, Heterocyclic/therapeutic use , Proto-Oncogene Proteins c-myc/genetics , Proto-Oncogene Proteins c-myc/metabolism , Proto-Oncogene Proteins c-myc/antagonists & inhibitors , Cell Line, Tumor , Oxidoreductases Acting on CH-CH Group Donors/antagonists & inhibitors , Oxidoreductases Acting on CH-CH Group Donors/genetics , Apoptosis/drug effects , Lymphoma, B-Cell/drug therapy , Lymphoma, B-Cell/genetics , Lymphoma, B-Cell/pathology , Lymphoma, B-Cell/metabolism , Gene Rearrangement , Cell Proliferation/drug effects , Biphenyl Compounds , QuinaldinesABSTRACT
BACKGROUND: The Global Diet Quality Score (GDQS) is a simple and practical dietary metric associated with a number of chronic diseases. The GDQS included various foods related to blood pressure, especially diverse plant-based foods that have shown to lower blood pressure. However, studies on the role of the GDQS in reducing the risk of new-onset hypertension and whether its performance differs from that of other dietary metrics are lacking. OBJECTIVE: We aimed to examine the association between the GDQS and new-onset hypertension and to compare its performance with that of other dietary patterns, including the Plant-based Diet Index (PDI), alternate Mediterranean diet (aMED) score, Alternative Healthy Eating Index-2010, and Dietary Approaches to Stop Hypertension (DASH) score in Chinese adults. METHODS: We included a total of 12,002 participants (5644 males and 6358 females) aged >18 y from the China Health and Nutrition Survey (1997-2015). Dietary intake was estimated using average food intakes from 3 consecutive 24-h dietary recalls. Multivariable relative risks (RRs) were computed for hypertension using modified Poisson regression models. RESULTS: With ≤18 y of follow-up (mean 8.7± 5.4 y), we ascertained 4232 incident cases of hypertension. Compared with participants with a low GDQS score (<15), the multivariable-adjusted RR of hypertension was 0.72 [95% confidence interval (CI): 0.62, 0.83] among participants with a high score (≥23). A 25% increment in the GDQS was associated with a 30% (RR, 0.70; 95% CI: 0.64, 0.76) lower risk of new-onset hypertension, which was comparable with the RRs of new-onset hypertension associated with every 25% increment in the PDI (RR, 0.84; 95% CI: 0.76, 0.93), DASH score (RR, 0.84; 95% CI: 0.78, 0.91), and aMED score (RR, 0.89; 95% CI: 0.84, 0.93). CONCLUSION: A higher GDQS was associated with a lower risk of new-onset hypertension, with comparable associations of new-onset hypertension with PDI, DASH, and aMED scores in Chinese adults.