p110CUX1 promotes acute myeloid leukemia progression via regulating pyridoxal phosphatase expression and activating PI3K/AKT/mTOR signaling pathway.

As an evolutionarily conserved transcription factor, Cut-like homeobox 1 (CUX1) plays crucial roles in embryonic and nervous system development, cell differentiation, and DNA damage repair. One of its major isoforms, p110CUX1, exhibits stable DNA binding capabilities and contributes to the regulation of cell cycle progression, proliferation, migration, and invasion. While p110CUX1 has been implicated in the progression of various malignant tumors, its involvement in acute myeloid leukemia (AML) remains uncertain. This study aims to elucidate the role of p110CUX1 in AML. Our findings reveal heightened expression levels of both p110CUX1 and pyridoxal phosphatase (PDXP) in AML cell lines. Overexpression of p110CUX1 promotes AML cell proliferation while inhibiting apoptosis and differentiation, whereas knockdown of PDXP yields contrasting effects. Mechanistically, p110CUX1 appears to facilitate AML development by upregulating PDXP expression and activating the PI3K/AKT/mTOR signaling pathway. Animal experimental corroborate the pro-AML effect of p110CUX1. These results provide experimental evidence supporting the involvement of the p110CUX1-PDXP-PI3K/AKT/mTOR axis in AML progression. Hence, targeting p110CUX1 may hold promise as a therapeutic strategy for AML.

[Construction and Evaluation of a Prognostic Risk Prediction Model of Pancreatic Ductal Adenocarcinoma Based on Immune-Related Genes].

Objective To construct a risk prediction model by integrating the molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) and immune-related genes.Methods With GSE71729 data set (n=145) as the training set,the differentially expressed genes and differential immune-related genes between the squamous and non-squamous subtypes of PDAC were integrated to construct a regulatory network,on the basis of which five immune marker genes regulating the squamous subtype were screened out.An integrated immune score (IIS) model was constructed based on patient survival information and immune marker genes to predict the clinical prognosis of PDAC patients,and its predictive performance was tested with 5 validation sets (n=758).Results PDAC patients were assigned into high risk and low risk groups according to the IIS.In both training and validation sets,the overall survival of patients in the high risk group was shorter than that in the low risk group (both P<0.001).The multivariable Cox regression showed that IIS was an independent prognostic factor for PDAC (HR=2.16,95%CI=1.50-3.10,P<0.001).Conclusion IIS can be used for risk stratification of PDAC patients and may become a potential prognostic marker for PDAC.

Immunogenicity, Safety, and Immune Persistence of One Dose of SARS-CoV-2 Recombinant Adenovirus Type-5 Vectored Vaccine in Children and Adolescents Aged 6-17 Years: An Immunobridging Trial.

BACKGROUND: Though children infected by SARS-CoV-2 generally experience milder symptoms compared to adults, severe cases can occur. Additionally, children can transmit the virus to others. Therefore, the availability of safe and effective COVID-19 vaccines for children and adolescents is crucial. METHOD: A single-center, randomized, double-blind clinical trial was conducted in Funing County, Yancheng City, Jiangsu Province, China. Healthy children and adolescents were divided into two subgroups (6-12 years old or 13-17 years old) and randomly assigned to one of three groups to receive one dose of Ad5-nCoV (3 × 1010 vp/dose). Another group, aged 18-59, received one dose of Ad5-nCoV (5 × 1010 vp/dose) as the control group. At 28, 90, 180, and 360 days post-vaccination, we measured the geometric mean titer (GMT)/concentration (GMC) of neutralizing and binding antibodies against the prototype SARS-CoV-2 strain, as well as serum antibody levels against the BA.4/5 variant. We also evaluated the incidence of adverse events within 28 days post-vaccination. RESULTS: A total of 2413 individuals were screened from 3 June 2021 to 25 July 2021, of whom 2021 eligible participants were enrolled, including 1009 aged 6~17 years in the children and adolescent group and 1012 aged 18-59 years in the adults group. The GMT of anti-wild SARS-CoV-2 neutralizing antibodies was 18.6 (95% CI, 16.6-20.9) in children and adolescents and 13.2 (95% CI, 11.6-15.0) in adults on day 28. The incidence of solicited adverse reactions between the adult group (49.4% [124/251]) and the children and adolescent group (46.3% [156/337]) was not statistically significant. The neutralizing antibody levels decreased by a factor of 3.29 from day 28 to day 360 post-vaccination. CONCLUSIONS: A single dose of Ad5-nCoV at 3 × 1010 virus particles/dose is safe in children and adolescents, and it elicited significant immune response, which was not only non-inferior but also superior to that in adults aged 18-59 years.

Pt-O-Ce interaction enhanced by Al substitution to promote the acetone degradation through accelerating the breaking of CC bond in acetic acid intermediate.

The reaction rate of volatile organic compounds (VOCs) oxidation is controlled by the rate-limiting step in the total reaction process. This study proposes a novel strategy, by which the rate-limiting step of acetone oxidation is accelerated by enhanced chemical bond interaction with more electrons transfer through Al-substituted CeO2 loaded Pt (Pt/Al-CeO2). Results indicate that the rate-limiting step in the process of acetone oxidation is the decomposition of acetic acid. Al substitution enhances the Pt-O-Ce interaction that transfers more electrons from Pt/Al-CeO2 to acetic acid, promoting the breaking of its CC bond with a lower free energy barrier. Attributing to these, the reaction rate of Pt/Al-CeO2 is 13 times as high as that of Pt/CeO2 and its TOFPt value is 11 times as high as that of Pt/CeO2 at 150 °C. Moreover, the CO2 selectivity of Pt/Al-CeO2 also increases by 22 %. This work establishes the relationship between Pt-O-Ce interaction and acetone oxidation that provides novel perspectives on the development of efficient materials for VOCs oxidation.

p200CUX1-regulated BMP8B inhibits the progression of acute myeloid leukemia via the MAPK signaling pathway.

The full-length p200CUX1 protein encoded by the homology frame CUT-like protein (CUX1) plays an important role in tumors as a pro-oncogene or oncogene. However, its role and mechanism in acute myeloid leukemia remain unknown. p200CUX1 regulates several pathways, including the MAPK signaling pathway. Our data showed that p200CUX1 is lowly expressed in THP1 and U937 AML cell lines. Lentiviral overexpression of p200CUX1 reduced proliferation and promoted apoptosis and G0/G1 phase blockade, correlating with MAPK pathway suppression. Additionally, p200CUX1 regulated the expression of bone morphogenetic protein 8B (BMP8B), which is overexpressed in AML. Overexpression of p200CUX1 downregulated BMP8B expression and inhibited the MAPK pathway. Furthermore, BMP8B knockdown inhibited AML cell proliferation, enhanced apoptosis and the sensitivity of ATRA-induced cell differentiation, and blocked G0/G1 transition. Our findings demonstrate the pivotal function of the p200CUX1-BMP8B-MAPK axis in maintaining the viability of AML cells. Consequently, targeting p200CUX1 could represent a viable strategy in AML therapy.

Lysosome-related genes predict acute myeloid leukemia prognosis and response to immunotherapy.

Background: Acute myeloid leukemia (AML) is a highly aggressive and pathogenic hematologic malignancy with consistently high mortality. Lysosomes are organelles involved in cell growth and metabolism that fuse to form specialized Auer rods in AML, and their role in AML has not been elucidated. This study aimed to identify AML subtypes centered on lysosome-related genes and to construct a prognostic model to guide individualized treatment of AML. Methods: Gene expression data and clinical data from AML patients were downloaded from two high-throughput sequencing platforms. The 191 lysosomal signature genes were obtained from the database MsigDB. Lysosomal clusters were identified by unsupervised consensus clustering. The differences in molecular expression, biological processes, and the immune microenvironment among lysosomal clusters were subsequently analyzed. Based on the molecular expression differences between lysosomal clusters, lysosomal-related genes affecting AML prognosis were screened by univariate cox regression and multivariate cox regression analyses. Algorithms for LASSO regression analyses were employed to construct prognostic models. The risk factor distribution, KM survival curve, was applied to evaluate the survival distribution of the model. Time-dependent ROC curves, nomograms and calibration curves were used to evaluate the predictive performance of the prognostic models. TIDE scores and drug sensitivity analyses were used to explore the implication of the model for AML treatment. Results: Our study identified two lysosomal clusters, cluster1 has longer survival time and stronger immune infiltration compared to cluster2. The differences in biological processes between the two lysosomal clusters are mainly manifested in the lysosomes, vesicles, immune cell function, and apoptosis. The prognostic model consisting of six prognosis-related genes was constructed. The prognostic model showed good predictive performance in all three data sets. Patients in the low-risk group survived significantly longer than those in the high-risk group and had higher immune infiltration and stronger response to immunotherapy. Patients in the high-risk group showed greater sensitivity to cytarabine, imatinib, and bortezomib, but lower sensitivity to ATRA compared to low -risk patients. Conclusion: Our prognostic model based on lysosome-related genes can effectively predict the prognosis of AML patients and provide reference evidence for individualized immunotherapy and pharmacological chemotherapy for AML.

Do as Sonographers Think: Contrast-enhanced Ultrasound for Thyroid Nodules Diagnosis via Microvascular Infiltrative Awareness.

Dynamic contrast-enhanced ultrasound (CEUS) imaging can reflect the microvascular distribution and blood flow perfusion, thereby holding clinical significance in distinguishing between malignant and benign thyroid nodules. Notably, CEUS offers a meticulous visualization of the microvascular distribution surrounding the nodule, leading to an apparent increase in tumor size compared to gray-scale ultrasound (US). In the dual-image obtained, the lesion size enlarged from gray-scale US to CEUS, as the microvascular appeared to be continuously infiltrating the surrounding tissue. Although the infiltrative dilatation of microvasculature remains ambiguous, sonographers believe it may promote the diagnosis of thyroid nodules. We propose a deep learning model designed to emulate the diagnostic reasoning process employed by sonographers. This model integrates the observation of microvascular infiltration on dynamic CEUS, leveraging the additional insights provided by gray-scale US for enhanced diagnostic support. Specifically, temporal projection attention is implemented on time dimension of dynamic CEUS to represent the microvascular perfusion. Additionally, we employ a group of confidence maps with flexible Sigmoid Alpha Functions to aware and describe the infiltrative dilatation process. Moreover, a self-adaptive integration mechanism is introduced to dynamically integrate the assisted gray-scale US and the confidence maps of CEUS for individual patients, ensuring a trustworthy diagnosis of thyroid nodules. In this retrospective study, we collected a thyroid nodule dataset of 282 CEUS videos. The method achieves a superior diagnostic accuracy and sensitivity of 89.52% and 93.75%, respectively. These results suggest that imitating the diagnostic thinking of sonographers, encompassing dynamic microvascular perfusion and infiltrative expansion, proves beneficial for CEUS-based thyroid nodule diagnosis.

Prescribed-Time Network-Based Deployment of Nonlinear Multiagent Systems: A Discrete-Space PDE Method.

This article attempts to design the prescribed-time time-varying deployment schemes for first-order and second-order nonlinear multiagent systems (MASs). We assume that all agents can obtain the information of their current and final relative positions with their neighbors, and the final absolute velocities (as well as their current and final relative velocities, the final absolute accelerations for the second-order MASs) through a communication network, whereas two boundary agents are able to obtain their current and final absolute positions (as well as their current and final absolute velocities for the second-order MASs). The neighbor relationship of all agents is described by a spatial variable and two static-feedback controllers are introduced, which can be expressed as a second-order space difference of the spatial variable. Then, the deployment of MASs can be transformed into the stabilization of discrete-space partial differential equation (PDE) systems. Three virtual agents are introduced to constitute the Dirchlet and Neumann boundary conditions. Several algebraic inequality criteria are derived to guarantee that the prescribed-time time-varying deployment can be achieved within a prescribed time under the Dirchlet and mixed boundary conditions. Unlike the published results, our results are derived based on the discrete-space PDE systems instead of continuous-space PDE systems, which is consistent with the discrete spatial distribution of agents. Finally, two numerical examples are given to illustrate the effectiveness of our results.

Integration of metal organic framework nanoparticles into sodium alginate biopolymer-based three-dimensional membrane capsules for the efficient removal of toxic metal cations from water and real sewage.

Sodium alginate (SA) biopolymer has been recognized as an efficient adsorbent material owing to their unique characteristics, including biodegradability, non-toxic nature, and presence of abundant hydrophilic functional groups. Accordingly, in the current research work, UiO-66-OH and UiO-66-(OH)2 metal organic framework (MOF) nanoparticles (NPs) have been integrated into SA biopolymer-based three-dimensional (3-D) membrane capsules (MCs) via a simple and facile approach to remove toxic metal cations (Cu2+ and Cd2+) from water and real sewage. The newly configured capsules were characterized by FTIR, SEM, XRD, EDX and XPS analyses techniques. Exceptional sorption properties of the as-developed capsules were ensured by evaluation of the pertinent operational parameters, i.e., contents of MOF-NPs (1-100 wt%), adsorbent dosage (0.001-0.05 g), content time (0-360 h), pH (1-8), initial concentration of metal cations (5-1000 mg/L) and reaction temperature (298.15-333.15 K) on the eradication of Cu2+ and Cd2+ metal cations. It was found that hydrophilic functional groups (-OH and -COOH) have performed an imperative role in the smooth loading of MOF-NPs into 3-D membrane capsules via intra/inter-molecular hydrogen bonding and van der waals potencies. The maximum monolayer uptake capacities (as calculated by the Langmuir isotherm model) of Cd2+ and Cu2+ by 3-D SGMMCs-OH were 940 and 1150 mg/g, respectively, and by 3-D SGMMCs-(OH)2 were 1375 and 1575 mg/g, respectively, under optimum conditions. The as-developed capsules have demonstrated superior selectivity against targeted metal cations under designated pH and maintained >80 % removal efficiency up to six consecutive treatment cycles. Removal mechanisms of metal cations by the 3-D SGMMCs-OH/(OH)2 was proposed, and electrostatic interaction, ion-exchange, inner-sphere coordination bonds/interactions, and aromatic ligands exchange were observed to be the key removal mechanisms. Notably, FTIR and XPS analysis indicated that hydroxyl groups of Zr-OH and BDC-OH/(OH)2 aromatic linkers played vital roles in Cu2+ and Cd2+ adsorption by participating in inner-sphere coordination interactions and aromatic ligands exchange mechanisms. The as-prepared capsules indicated >70 % removal efficiency of Cu2+ from real electroplating wastewater in the manifestation of other competitive metal ions and pollutants under selected experimental conditions. Thus, it was observed that newly configured 3-D SGMMCs-OH/(OH)2 have offered a valuable discernment into the development of MOFs-based water decontamination 3-D capsules for industrial applications.

Use of egg yolk phospholipids to improve the thermal-oxidative stability of fatty acids, capsaicinoids and carotenoids in chili oil.

Phospholipids can act as antioxidants in food. In this study, egg yolk phospholipids (EPL) and sunflower oil were utilized in making chili oil, and proton nuclear magnetic resonance spectroscopy was employed to quantify the concentrations of fatty acyl groups, carotenoids, capsaicinoids in chili oil according to their specific signals in the spectra. The results showed that the changes in the concentrations of fatty acyl groups in the control samples were greater than those in the EPL-treated samples at the same frying temperature, while the contents of carotenoids and capsaicinoids were significantly lower than those of the EPL-treated samples when fried at 150 °C (p < 0.05). Two-way ANOVA indicated that frying temperature and EPL treatment, as well as their interaction had significant impacts on the thermal-oxidative stability of chili oil (p < 0.05). The results suggest that EPL may act as antioxidants during frying, and EPL can improve the thermal-oxidative stability of chili oil.

Association of epicardial fat volume with subclinical myocardial damage in patients with type 2 diabetes mellitus.

Background: In type 2 diabetes mellitus (T2DM) patients, left ventricular systolic dyssynchrony (LVSD) with normal left ventricular ejection fraction (LVEF) and normal myocardial perfusion could referred to as subclinical myocardial damage, which is difficult to diagnose at an early stage. Epicardial adipose tissue, a distinctive heart-specific visceral fat, is closely related to various cardiovascular diseases. The objective of this study was to investigate the correlation between epicardial fat volume (EFV) and subclinical myocardial damage in T2DM patients. Methods: This retrospective cross-sectional study included 117 T2DM patients with normal myocardial perfusion by single photon emission computed tomography-computed tomography (SPECT-CT) and normal LVEF by echocardiography. The study was conducted from January 2018 to December 2022. Patient data were collected through electronic medical records including basic patient information, medical history, laboratory tests, and medication data. The EFV was quantified through a non-contrast CT scan. Quantitative indicators of LVSD including phase standard deviation (PSD) and phase histogram bandwidth (PBW) were obtained through phase analysis of the gated rest myocardial perfusion imaging (MPI). Additionally, 83 healthy individuals at the same time were selected to gain the reference threshold of LVSD indicators (13.1° for PSD and 37.6° for PBW). Univariate and multivariable logistic regression models were performed to analyze factors influencing LVSD. A generalized additive model (GAM) was applied to explore the relationship between EFV and LVSD. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of EFV for LVSD. Results: Among all patients, 32 (27.4%) patients had LVSD. Compared with the non-LVSD group, the body mass index (BMI) and EFV were higher in the LVSD group (25.83±2.66 vs. 23.94±3.13 kg/m2; 142.41±44.17 vs. 108.01±38.24 cm3, respectively, both P<0.05). Multivariate regression analysis revealed that EFV was independently associated with LVSD [odds ratio (OR) =1.19; 95% confidence interval (CI): 1.06-1.34; P=0.003]. Age, BMI, incidence of hypertension, and LVSD were increased with tertiles of EFV (all P<0.05). The GAM indicated a linear association between EFV and LVSD. The ROC curve analysis concluded that the area under the curve (AUC) of EFV for predicting subclinical myocardial damage in T2DM patients was 0.732 (95% CI: 0.633-0.831, P<0.001), with the optimal threshold of 122.26 cm3, sensitivity of 71.9%, and specificity of 69.4%. Conclusions: EFV is an independent risk factor for LVSD in T2DM patients with normal LVEF and normal MPI, which could potentially serve as a novel imaging marker and a potential therapeutic target for subclinical myocardial damage.

Deep learning radiomics based prediction of axillary lymph node metastasis in breast cancer.

This study aimed to develop and validate a deep learning radiomics nomogram (DLRN) for the preoperative evaluation of axillary lymph node (ALN) metastasis status in patients with a newly diagnosed unifocal breast cancer. A total of 883 eligible patients with breast cancer who underwent preoperative breast and axillary ultrasound were retrospectively enrolled between April 1, 2016, and June 30, 2022. The training cohort comprised 621 patients from Hospital I; the external validation cohorts comprised 112, 87, and 63 patients from Hospitals II, III, and IV, respectively. A DLR signature was created based on the deep learning and handcrafted features, and the DLRN was then developed based on the signature and four independent clinical parameters. The DLRN exhibited good performance, yielding areas under the receiver operating characteristic curve (AUC) of 0.914, 0.929, and 0.952 in the three external validation cohorts, respectively. Decision curve and calibration curve analyses demonstrated the favorable clinical value and calibration of the nomogram. In addition, the DLRN outperformed five experienced radiologists in all cohorts. This has the potential to guide appropriate management of the axilla in patients with breast cancer, including avoiding overtreatment.

Platelet Exosome-Derived miR-223-3p Regulates Pyroptosis in the Cell Model of Sepsis-Induced Acute Renal Injury by Targeting Mediates NLRP3.

BACKGROUND: The present study investigated the roles and mechanisms of platelet-derived exosomes in sepsis-induced acute renal injury. METHODS: The blood samples of septic patients and healthy controls were collected for clinical examination. The plasma levels of miR-223-3p and NLRP3 mRNA were analyzed by qRT-PCR and the serum IL-1ß and creatinine levels were quantified by enzyme-linked immunosorbent assay (ELISA). C57BL/6 mice injected with LPS (lipopolysaccharide) were employed as the animal model for sepsis-induced acute renal injury. Human coronary artery endothelial cells (HCAECs) were treated with TNF-α as a cellular model for sepsis-induced endothelial damages. RESULTS: The number of PMP (platelet-derived microparticles) in patients with sepsis was increased. The level of miR-223-3p in the platelet exosomes isolated from the serum sample in patients with sepsis was significantly lower than that of the healthy controls. The level of miR-223-3p was also decreased in the platelet exosomes of mouse model with sepsis-induced acute renal injury. Downregulating miR-223-3p promoted sepsis-induced acute renal injury in mice model, while the administration of miR-223-3p reduced the inflammation in endothelial cells of sepsis-induced acute renal injury. NLRP3 (NLR Family Pyrin Domain Containing 3) was identified as one target of miR-223-3p in the platelet exosomes of sepsis-induced acute kidney injury. miR-223-3p attenuated NLRP3-induced pyroptosis in endothelial cell model of sepsis-induced acute kidney injury. CONCLUSION: Our data suggest that platelet exosome-derived miR-223-3p negatively regulates NLRP3-dependent inflammasome to suppress pyroptosis in endothelial cells. Decreased miR-223-3p expression promotes the inflammation in sepsis-induced acute renal injury. Targeting miR-223-3p may be developed into a therapeutic approach for sepsis-induced acute renal injury.

The relationship between right atrial wall inflammation and poor prognosis of atrial fibrillation based on 18F-FDG positron emission tomography/computed tomography.

Background: Atrial fibrillation (AF) has been identified to increase stroke risk, even after oral anticoagulants (OACs), and the recurrence rate is high after radiofrequency catheter ablation (RFCA). Inflammation is an essential factor in the occurrence and persistence of AF. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) is an established molecular imaging modality to detect local inflammation. We aimed to investigate the relationship between atrial inflammatory activity and poor prognosis of AF based on 18F-FDG PET/CT. Methods: A total of 204 AF patients including 75 with paroxysmal AF (ParAF) and 129 with persistent AF (PerAF) who underwent PET/CT before treatment were enrolled in this prospective cohort study. Clinical data, electrocardiograph (ECG), echocardiography, and cardiac 18F-FDG uptake were collected. Follow-up information was obtained from patient clinical case notes or telephone reviews, with the starting point being the time of PET/CT scan. The follow-up deadline was either the date of AF recurrence after RFCA, new-onset stroke, or May 2023. Cox proportional hazards regression models were used to identify predictors of poor prognosis and hazard ratios (HRs) with 95% confidence intervals (CIs) was calculated. Results: Median follow-up time was 29 months [interquartile range (IQR), 22-36 months]. Poor prognosis occurred in 52 patients (25.5%), including 34 new-onset stroke patients and 18 recrudescence after RFCA. The poor prognosis group had higher congestive heart failure, hypertension, age ≥75 years (doubled), diabetes mellitus, prior stroke or transient ischemic attack (TIA) or thromboembolism (doubled), vascular disease, age 65-74 years, sex category (female) (CHA2DS2-VASc) score [3.0 (IQR, 1.0-3.75) vs. 2.0 (IQR, 1.0-3.0), P=0.01], right atrial (RA) wall maximum standardized uptake value (SUVmax) (4.13±1.82 vs. 3.74±1.58, P=0.04), higher percentage of PerAF [39 (75.0%) vs. 90 (59.2%), P=0.04], left atrial (LA) enlargement [45 (86.5%) vs. 104 (68.4%), P=0.01], and RA wall positive FDG uptake [40 (76.9%) vs. 79 (52.0%), P=0.002] compared with the non-poor prognosis group. Univariate and multivariate Cox proportional hazard regression analysis concluded that only CHA2DS2-VASc score (HR, 1.29; 95% CI: 1.06-1.57; P=0.01) and RA wall positive FDG uptake (HR, 2.68; 95% CI: 1.10-6.50; P=0.03) were significantly associated with poor prognosis. Conclusions: RA wall FDG positive uptake based on PET/CT is tightly related to AF recurrence after RFCA or new-onset stroke after antiarrhythmic and anticoagulation treatment.

Mutation in PgABCC2 confers low-level resistance to Cry1Ac in pink bollworm.

BACKGROUND: With the increasing incidence of pest resistance to transgenic crops producing Bacillus thuringiensis (Bt) proteins in the field, elucidating the molecular basis of resistance is important for monitoring, delaying and countering pest resistance. Previous work revealed that mutation or down-regulated expression of the cadherin gene (PgCad1) is associated with pink bollworm (Pectinophora gossypiella) resistance to Cry1Ac, and 20 mutant PgCad1 alleles (r1-r20) were characterized. Here, we tested the hypothesis that the ABC transporter PgABCC2 is a functional receptor for the Bt toxin Cry1Ac and that a mutation is associated with resistance. RESULTS: We identified and characterized the first resistance allele (rC2) of PgABCC2 in the laboratory-selected Cry1Ac-resistant strain AQ-C2 of pink bollworm. The rC2 allele had a one-base deletion in exon20, resulting in a frameshift and the introduction of a premature stop codon. This resulting PgABCC2 protein had a truncated C-terminus, including the loss of the NBD2 domain. AQ-C2 exhibited 20.2-fold greater resistance to Cry1Ac than the susceptible strain, and its inheritance of Cry1Ac resistance was recessive and genetically linked to PgABCC2. When produced in cultured insect cells, recombinant wild-type and rC2 mutant PgABCC2 proteins localized within the cell plasma membrane, although substantial cytoplasmic retention was also observed for the mutant protein, while the mutant PgABCC2 caused a 13.9-fold decrease in Cry1Ac toxicity versus the wild-type PgABCC2. CONCLUSIONS: PgABCC2 is a functional receptor of Cry1Ac and the loss of its carboxyl terminus (including its NBD2 domain) confers low-level resistance to Cry1Ac in both larvae and in cultured cells. © 2024 Society of Chemical Industry.

Netrin-1 mitigates acute lung injury by preventing the activation of the Toll-like receptor 4/nuclear factor-κB (TLR4/NF-κB) signaling.

Acute lung injury (ALI) is one of the most common high-risk diseases associated with a high mortality rate and is still a challenge to treat effectively. Netrin-1 (NT-1) is a novel peptide with a wide range of biological functions, however, its effects on ALI have not been reported before. In this study, an ALI model was constructed using lipopolysaccharide (LPS) and treated with NT-1. Pulmonary function and lung wet to dry weight ratio (W/D) were detected. The expressions of pro-inflammatory cytokines and chemokines interleukin-8 (IL-8), interleukin-1ß (IL-1ß), and chemokine (C-X-C motif) ligand 2 (CXCL2) were measured using real-time polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA). We found that the levels of NT-1 were reduced in the LPS-induced ALI mice model. Administration of NT-1 improved histopathological changes of lung tissues and lung function in LPS-challenged ALI mice. We also report that NT-1 decreased Myeloperoxidase (MPO) activity and ameliorated pulmonary edema. Additionally, treatment with NT-1 reduced the levels of pro-inflammatory cytokines and chemokines such as IL-8, IL-1ß, and CXCL2 in lung tissues of LPS-challenged ALI mice. Importantly, NT-1 reduced cell count in BALF and mitigated oxidative stress (OS) by reducing the levels of MDA and increasing the levels of GSH. Mechanistically, it is shown that NT-1 reduced the levels of Toll-like receptor 4 (TLR4) and prevented nuclear translocation of nuclear factor-κB (NF-κB) p65. Our findings indicate that NT-1 is a promising agent for the treatment of ALI through inhibiting TLR4/NF-κB signaling.

Multi-Instance Multi-Task Learning for Joint Clinical Outcome and Genomic Profile Predictions From the Histopathological Images.

With the remarkable success of digital histopathology and the deep learning technology, many whole-slide pathological images (WSIs) based deep learning models are designed to help pathologists diagnose human cancers. Recently, rather than predicting categorical variables as in cancer diagnosis, several deep learning studies are also proposed to estimate the continuous variables such as the patients' survival or their transcriptional profile. However, most of the existing studies focus on conducting these predicting tasks separately, which overlooks the useful intrinsic correlation among them that can boost the prediction performance of each individual task. In addition, it is sill challenge to design the WSI-based deep learning models, since a WSI is with huge size but annotated with coarse label. In this study, we propose a general multi-instance multi-task learning framework (HistMIMT) for multi-purpose prediction from WSIs. Specifically, we firstly propose a novel multi-instance learning module (TMICS) considering both common and specific task information across different tasks to generate bag representation for each individual task. Then, a soft-mask based fusion module with channel attention (SFCA) is developed to leverage useful information from the related tasks to help improve the prediction performance on target task. We evaluate our method on three cancer cohorts derived from the Cancer Genome Atlas (TCGA). For each cohort, our multi-purpose prediction tasks range from cancer diagnosis, survival prediction and estimating the transcriptional profile of gene TP53. The experimental results demonstrated that HistMIMT can yield better outcome on all clinical prediction tasks than its competitors.

Heteropolyacid-Catalyzed Phosphorylation of Secondary Aromatic Alcohols with H-Phosphine Oxides in DMC: A Simple Protocol for C-P Bond Formation.

We successfully achieved the phosphorylation of secondary aromatic alcohols with H-phosphine oxides (less developed system) using phosphotungstic acid as a catalyst in dimethyl carbonate. The system was simple and environmentally friendly and showed better activity than traditional Lewis or Brønsted acids such as FeCl3, p-TsOH·H2O, etc., generating up to a 97% isolated yield. Control experiments indicated that the reaction did not occur through the radical pathway, and ethers and carbocation were the key intermediates in the pathway.

Convergence-Rate-Based Event-Triggered Mechanisms for Quasi-Synchronization of Delayed Nonlinear Systems on Time Scales.

Most of the existing event-triggered mechanisms (ETMs) were designed according to the difference between the quadratic form of measurement errors and the quadratic form of sampling states (or real-time states). In order to reduce the amount of data transmission and develop ETMs for continuous-time and discrete-time delayed nonlinear systems (NSs) simultaneously, this article investigates quasi-synchronization (QS) of NSs on time scales based on a novel ETM, which is designed according to the convergence rate instead of measurement errors of the addressed systems. First, a novel ETM is designed under known nonlinear dynamics, and it is demonstrated that QS with given convergence rate and error level can be achieved under matrix inequality criteria. Second, if the nonlinear functions are unknown, we adapt our ETM to handle this special case. Not only QS but also complete synchronization with given convergence rate can be achieved under the ETMs. If the constructed Lyapunov functions passes through 0, the designed ETM will keep it at the origin. In this case, finite-time synchronization is achieved. Third, under the designed ETMs, it is proved that Zeno behavior can be excluded. At last, four numerical simulations are presented to demonstrate the feasibility and the advantage of the designed ETMs in this article.

A novel sphingolipid metabolism-related long noncoding RNA signature predicts the prognosis, immune landscape and therapeutic response in pancreatic adenocarcinoma.

Sphingolipid metabolism affects prognosis and resistance to immunotherapy in patients with cancer and is an emerging target in cancer therapy with promising diagnostic and prognostic value. Long noncoding ribonucleic acids (lncRNAs) broadly regulate tumour-associated metabolic reprogramming. However, the potential of sphingolipid metabolism-related lncRNAs in pancreatic adenocarcinoma (PAAD) is poorly understood. In this study, coexpression algorithms were employed to identify sphingolipid metabolism-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a sphingolipid metabolism-related lncRNA signature (SMLs). The prognostic predictive stability of the SMLs was validated using Kaplan-Meier. Univariate and multivariate Cox, receiver operating characteristic (ROC) and clinical stratification analyses were used to comprehensively assess the SMLs. Gene set variation analysis (GSVE), gene ontology (GO) and tumor mutation burden (TMB) analysis explored the potential mechanisms. Additionally, single sample gene set enrichment analysis (ssGSEA), ESTIMATE, immune checkpoints and drug sensitivity analysis were used to investigate the potential predictive function of the SMLs. Finally, an SMLs-based consensus clustering algorithm was utilized to differentiate patients and determine the suitable population for immunotherapy. The results showed that the SMLs consists of seven sphingolipid metabolism-related lncRNAs, which can well determine the clinical outcome of individuals with PAAD, with high stability and general applicability. In addition, the SMLs-based consensus clustering algorithm divided the TCGA-PAAD cohort into two clusters, with Cluster 1 showing better survival than Cluster 2. Additionally, Cluster 1 had a higher level of immune cell infiltration than Cluster 2, which combined with the higher levels of immune checkpoints in Cluster 1 suggests that Cluster 1 is more consistent with an immune 'hot tumor' profile and may respond better to immune checkpoint inhibitors (ICIs). This study offers new insights regarding the potential role of sphingolipid metabolism-related lncRNAs as biomarkers in PAAD. The constructed SMLs and the SMLs-based clustering are valuable tools for predicting clinical outcomes in PAAD and provide a basis for clinical selection of individualized treatments.