Histone demethylase KDM4A mediating macrophage polarization: A potential mechanism of trichloroethylene induced liver injury.

Trichloroethylene (TCE) is a commonly used organic solvent in industry. Our previous studies have found that TCE can cause liver injury accompanied by macrophage polarization, but the specific mechanism is unclear. The epigenetic regulation of macrophage polarization is mainly focused on histone modification. Histone lysine demethylase 4A (KDM4A) is involved in the activation of macrophages. In this study, we used a mouse model we investigated the role of KDM4A in the livers of TCE-drinking mice and found that the expression of KDM4A, M1-type polarization indicators, and related inflammatory factors in the livers of TCE-drinking mice. In the study, BALB/c mice were randomly divided into four groups: 2.5 mg/mL TCE dose group and 5.0 mg/mL TCE dose group, the vehicle control group, and the blank control group. We found that TCE triggered M1 polarization of mouse macrophages, characterized by the expression of CD11c and robust production of inflammatory cytokines. Notably, exposure to TCE resulted in markedly increased expression of KDM4A in macrophages. Functionally, the increased expression of KDM4A significantly impaired the expression of H3K9me3 and H3K9me2 and increased the expression of H3K9me1. In addition, KDM4A potentially represents a novel epigenetic modulator, with its upregulation connected to ß-catenin activation, a signal critical for the pro-inflammatory activation of macrophages. Furthermore, KDM4A inhibitor JIB-04 treatment resulted in a decrease in ß-catenin expression and prevented TCE-induced M1 polarization and the expression of the pro-inflammatory cytokines TNF-α and IL-1ß. These results suggest that the association of KDM4A and Wnt/ß-catenin cooperatively establishes the activation and polarization of macrophages and global changes in H3K9me3/me2/me1. Our findings identify KDM4A as an essential regulator of the polarization of macrophages and the expression of inflammatory cytokines, which might serve as a potential target for preventing and treating liver injury caused by TCE.

Population pharmacokinetics and pharmacodynamics of nasal glucagon in patients with type 1 or 2 diabetes.

The objective was to characterize the pharmacokinetics (PK) and pharmacodynamics (PD) of glucagon after injectable or nasal administration and confirm the appropriate therapeutic dose of nasal glucagon (NG) for adult patients. Six clinical studies with PK and five clinical studies with PD (glucose) data were included in the analysis. Doses ranging from 0.5 to 6 mg NG, and 0.5 to 1 mg injectable glucagon were studied. A total of 6284 glucagon and 7130 glucose concentrations from 265 individuals (patients and healthy participants) were available. Population PK/PD modeling was performed using NONMEM. Glucagon exposure and glucose response were simulated for patients administered various doses of NG to confirm the optimal dose. Glucagon PK was well-described with a single compartment disposition with first-order absorption and elimination processes. Bioavailability of NG relative to injectable glucagon was 16%. Exposure-response modeling revealed that lower baseline glucose was associated with higher maximum drug effect. The carry-over effect from prior insulin administration was incorporated into the model through a time-dependent increase in elimination rate of glucose. Simulations showed that more than 99% of hypoglycemic adult patients would experience treatment success, defined as an increase in blood glucose to ≥70 mg/dL or an increase of ≥20 mg/dL from nadir within 30 min after administration of NG 3 mg. The population PK/PD model adequately described the PK and PD profiles of glucagon after nasal administration. Modeling and simulations confirmed that NG 3 mg is the most appropriate dose for rescue treatment during hypoglycemia emergencies.

Waist-to-height ratio is a better predictor of hypertension in women during recovery from anesthesia compared to BMI, waist-to-hip ratio, and waist circumference.

This was an observational study of patients with benign breast tumors intended to investigate and compare the predictive value of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) for hypertension in the recovery room. Logistic regression analysis was used to determine the association between these body fat anthropometric indices and hypertension. Receiver operating characteristic curve (ROC) analysis was performed to assess the comparative predictive ability. A total of 689 women were evaluated. Patients with BMI ≥28 (kg/m2), WC > 85 cm, WHR ≥0.82, and WHtR ≥0.5 had a significantly higher probability of increased systolic blood pressure (SBP) and diastolic blood pressure (DBP) than patients with less than threshold values (all P < 0.05). The areas under the ROC curve (AUC) of BMI, WC, and WHtR where all modestly significant (all AUC ≥0.65) and nearly identical at 0.6592, 0.65, and 0.6724, respectively. Conclusion: body fat anthropometric indices are useful predicting hypertension during recovery from general anesthesia in patients with benign breast tumors undergoing day surgery; WHtR outperformed the other indices and nearly identical.

Prognostic Significance of Plasma VEGFA and VEGFR2 in Acute Ischemic Stroke-a Prospective Cohort Study.

Enhancement of vascular remodeling in affected brain tissue is a novel therapy for acute ischemic stroke (AIS). However, conclusions regarding angiogenesis after AIS remain ambiguous. Vascular endothelial growth factor A (VEGFA) and VEGF receptor 2 (VEGFR2) are potent regulators of angiogenesis and vascular permeability. We aimed to investigate the association between VEGFA/VEGFR2 expression in the acute stage of stroke and prognosis of patients with AIS. We enrolled 120 patients with AIS within 24 h of stroke onset and 26 healthy controls. Plasma levels of VEGFA and VEGFR2 were measured by enzyme-linked immunosorbent assay (ELISA). The primary endpoint was an unfavorable outcome defined as a modified Rankin Scale (mRS) score > 2 at 3 months after AIS. Univariate and multivariate logistic regression analyses were used to identify risk factors affecting prognosis. Plasma VEGFA and VEGFR2 were significantly higher in patients with AIS than in health controls, and also significantly higher in patients with unfavorable than those with favorable outcomes. Moreover, both VEGFA and VEGFR2 showed a significantly positive correlation with mRS at 3 months. Univariate and multivariate analyses showed VEGFA and VEGFR2 remained associated with unfavorable outcomes, and adding VEGFA and VEGFR2 to the clinical model significantly improved risk reclassification (continuous net reclassification improvement, 105.71%; integrated discrimination improvement, 23.45%). The new risk model curve exhibited a good fit with an area under the receiver operating characteristic curve (ROC) curve of 0.9166 (0.8658-0.9674). Plasma VEGFA and VEGFR2 are potential markers for predicting prognosis; thus these two plasma biomarkers may improve risk stratification in patients with AIS.

Interfacial interactions of polyethylene terephthalate microplastics and malachite green, tetracycline in aqueous environments.

Polyethylene terephthalate microplastics (PET-MPs) are one of pivotal nondegradable emerging pollutant. Here the variation of the surface physicochemical characteristics of PET-MPs with UV irradiation aging and the adsorption behaviors of PET-MPs in malachite green (MG), tetracycline (TC) solution and the effect of coexisting Cu(II) were comparatively investigated. The yellowing, weakened hydrophobicity, and increased surface negative charge, crystallinity degree and oxygen-containing functional groups were manifested specifically by the aged PET-MPs. Different from the single system, the hydrophobic interaction and metal ion bridging complexation dominated the adsorption of MG and TC, respectively, in the binary solution. While in the ternary solution, cationic ion competition of Cu(II) with MG decreased its capture, and the formation of PET-Cu(II)-TC ternary complexes promoted TC adsorption. Moreover, PET-MPs could serve as an efficient vector for MG and TC in MG/TC/Cu(II) ternary system, indicating PET-MPs tend to carry more varieties in the complex environment, that may increase the environmental risk of PET-MPs.

metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics.

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a "primary" feature list is used as a template for matching compounds in "target" feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution's in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.

High-frequency rTMS over bilateral primary motor cortex improves freezing of gait and emotion regulation in patients with Parkinson's disease: a randomized controlled trial.

Background: Freezing of gait (FOG) is a common and disabling phenomenon in patients with Parkinson's disease (PD), but effective treatment approach remains inconclusive. Dysfunctional emotional factors play a key role in FOG. Since primary motor cortex (M1) connects with prefrontal areas via the frontal longitudinal system, where are responsible for emotional regulation, we hypothesized M1 may be a potential neuromodulation target for FOG therapy. The purpose of this study is to explore whether high-frequency rTMS over bilateral M1 could relieve FOG and emotional dysregulation in patients with PD. Methods: This study is a single-center, randomized double-blind clinical trial. Forty-eight patients with PD and FOG from the Affiliated Hospital of Xuzhou Medical University were randomly assigned to receive 10 sessions of either active (N = 24) or sham (N = 24) 10 Hz rTMS over the bilateral M1. Patients were evaluated at baseline (T0), after the last session of treatment (T1) and 30 days after the last session (T2). The primary outcomes were Freezing of Gait Questionnaire (FOGQ) scores, with Timed Up and Go Test (TUG) time, Standing-Start 180° Turn (SS-180) time, SS-180 steps, United Parkinson Disease Rating Scales (UPDRS) III, Hamilton Depression scale (HAMD)-24 and Hamilton Anxiety scale (HAMA)-14 as secondary outcomes. Results: Two patients in each group dropped out at T2 and no serious adverse events were reported by any subject. Two-way repeated ANOVAs revealed significant group × time interactions in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14. Post-hoc analyses showed that compared to T0, the active group exhibited remarkable improvements in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14 at T1 and T2. No significant improvement was found in the sham group. The Spearman correlation analysis revealed a significantly positive association between the changes in HAMD-24 and HAMA-14 scores and FOGQ scores at T1. Conclusion: High-frequency rTMS over bilateral M1 can improve FOG and reduce depression and anxiety in patients with PD.

The Plastic Deformation Mechanism in Nano-Polycrystalline Al/Mg Layered Composites: A Molecular Dynamics Study.

Understanding plastic deformation behaviour is key to optimising the mechanical properties of nano-polycrystalline layered composites. This study employs the molecular dynamics (MD) simulation to comprehensively investigate the effects of various factors, such as grain sizes, strain rates, and the interlayer thicknesses of the intermetallic compounds (IMCs), on the plastic deformation behaviour of nano-polycrystalline Al/Mg layered composites. Our findings reveal that the influence of grain size on deformation behaviour is governed by the strain rate, and an increase in grain size is inversely proportional to yield stress at low strain rates, whereas it is positively proportional to tensile stress at high strain rates. Moreover, an optimal thickness of the intermediate layer contributes to enhanced composite strength, whereas an excessive thickness leads to reduced tensile strength due to the fewer grain boundaries (GBs) available for accommodating dislocations. The reinforcing impact of the intermediate IMCs layer diminishes at excessive strain rates, as the grains struggle to accommodate substantial large strains within a limited timeframe encountered at high strain rates. The insights into grain sizes, strain rates, and interlayer thicknesses obtained from this study enable the tailored development of nanocomposites with optimal mechanical characteristics.

Targeting Erbin-mitochondria axis in platelets/megakaryocytes promotes B cell-mediated antitumor immunity.

The roles of platelets/megakaryocytes (MKs), the key components in the blood system, in the tumor microenvironment and antitumor immunity are unclear. In patients with colorectal cancer, the number of platelets was significantly increased in patients with metastasis, and Erbin expression was highly expressed in platelets from patients with metastases. Moreover, Erbin knockout in platelets/MKs suppressed lung metastasis in mice and promoted aggregations of platelets. Mechanistically, Erbin-deficient platelets have increasing mitochondrial oxidative phosphorylation and secrete lipid metabolites like acyl-carnitine (Acar) by abolishing interaction with prothrombotic protein ESAM. Notably, Acar enhanced the activity of mitochondrial electron transport chain complex and mitochondrial oxidative phosphorylation in B cells by acetylation of H3K27 epigenetically. Targeting Erbin in platelets/MKs by a nanovesicle system dramatically attenuated lung metastasis in mice in vivo. Our study identifies an Erbin-mitochondria axis in platelets/MKs, which suppresses B cell-mediated antitumor immunity, suggesting a new way for the treatment of metastasis.

Sulfated Chitosan Nanofibrous Scaffolds Seeded With Adipose Stem Cells Promote Ischemic Wound Healing in a Proangiogenic Strategy.

Ischemic wounds are chronic wounds with poor blood supply that delays wound reconstruction. To accelerate wound healing and promote angiogenesis, adipose-derived stem cells (ADSCs) are ideal seed cells for stem cell-based therapies. Nevertheless, providing a favorable environment for cell proliferation and metabolism poses a substantial challenge. A highly sulfated heparin-like polysaccharide 2-N, 6-O-sulfated chitosan (26SCS)-doped poly(lactic-co-glycolic acid) scaffold (S-PLGA) can be used due to their biocompatibility, mechanical properties, and coagent 26SCS high affinity for growth factors. In this study, a nano-scaffold system, constructed from ADSCs seeded on electrospun fibers of modified PLGA, was designed to promote ischemic wound healing. The S-PLGA nanofiber membrane loaded with adipose stem cells ADSCs@S-PLGA was prepared by a co-culture in vitro, and the adhesion and compatibility of cells on the nano-scaffolds were explored. Scanning electron microscopy was used to observe the growth state and morphological changes of ADSCs after co-culture with PLGA electrospun fibers. The proliferation and apoptosis after co-culture were detected using a Cell Counting Kit-8 kit and flow cytometry, respectively. An ischemic wound model was then established, and we further studied the ability of ADSCs@S-PLGA to promote wound healing and angiogenesis. We successfully established ischemic wounds on the backs of rats and demonstrated that electrospun fibers combined with the biological effects of adipose stem cells effectively promoted wound healing and the growth of microvessels around the ischemic wounds. Phased research results can provide a theoretical and experimental basis for a new method for promoting clinical ischemic wound healing.

A novel model for predicting prognosis in patients with idiopathic pulmonary fibrosis based on endoplasmic reticulum stress-related genes.

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic disease of unknown pathogenic origin. Endoplasmic reticulum (ER) stress refers to the process by which cells take measures to ER function when the morphology and function of the reticulum are changed. Recent studies have demonstrated that the ER was involved in the evolution and progression of IPF. In this study, we obtained transcriptome data and relevant clinical information from the Gene Expression Omnibus database and conducted bioinformatics analysis. Among the 544 ER stress-related genes (ERSRGs), 78 were identified as differentially expressed genes (DEGs). These DEGs were primarily enriched in response to ER stress, protein binding, and protein processing. Two genes (HTRA2 and KTN1) were included for constructing an accurate molecular signature. The overall survival of patients was remarkably worse in the high-risk group than in the low-risk group. We further analyzed the difference in immune cells between high-risk and low-risk groups. M0 and M2 macrophages were significantly increased in the high-risk group. Our results suggested that ERSRGs might play a critical role in the development of IPF by regulating the immune microenvironment in the lungs, which provide new insights on predicting the prognosis of patients with IPF.

Construction of 3D network aluminum sludge-based hydrogel beads: combination of macroization, amino functionalization, and resource utilization.

An aluminum sludge-based composite material was constructed against the problems of phosphorus pollution and the waste of aluminum sludge resources. Utilizing metal Ce doping and hydrogel microbeads with pore preparation, the adsorption performance of the original sludge was improved. Meanwhile, the macroscopic body was constructed, and on this basis, polyethyleneimine (PEI) was introduced to complete the amino functionalization further to enhance the adsorption of phosphorus by the adsorbent, and NH-CeAIS-10 microbeads were successfully prepared. In adsorption, microbeads with larger specific surface area and richer functional groups are better choice compared to original sludge. The results of SEM, BET, FT-IR, and XPS analyses indicate that the adsorption of phosphorus by the microbeads is mainly achieved through electrostatic interactions, ligand exchange, and the formation of inner-sphere complexes. According to the Langmuir model, the maximum phosphorus adsorption capacity of NH-CeAIS-10 was 29.56 mg g-1, which was four times higher compared to native aluminum sludge. This also confirms the significant enhancement of phosphorus adsorption through the modification of aluminum sludge. Besides, in dynamic adsorption column experiments, the material exhibited up to 99% removal in simulated wastewater for up to 30 days, demonstrating the great adsorption potential of NH-CeAIS-10 in engineering applications.

Development and Temporal Validation of a Machine Learning Model to Predict Clinical Deterioration.

OBJECTIVES: Early warning scores detecting clinical deterioration in pediatric inpatients have wide-ranging performance and use a limited number of clinical features. This study developed a machine learning model leveraging multiple static and dynamic clinical features from the electronic health record to predict the composite outcome of unplanned transfer to the ICU within 24 hours and inpatient mortality within 48 hours in hospitalized children. METHODS: Using a retrospective development cohort of 17 630 encounters across 10 388 patients, 2 machine learning models (light gradient boosting machine [LGBM] and random forest) were trained on 542 features and compared with our institutional Pediatric Early Warning Score (I-PEWS). RESULTS: The LGBM model significantly outperformed I-PEWS based on receiver operating characteristic curve (AUROC) for the composite outcome of ICU transfer or mortality for both internal validation and temporal validation cohorts (AUROC 0.785 95% confidence interval [0.780-0.791] vs 0.708 [0.701-0.715] for temporal validation) as well as lead-time before deterioration events (median 11 hours vs 3 hours; P = .004). However, LGBM performance as evaluated by precision recall curve was lesser in the temporal validation cohort with associated decreased positive predictive value (6% vs 29%) and increased number needed to evaluate (17 vs 3) compared with I-PEWS. CONCLUSIONS: Our electronic health record based machine learning model demonstrated improved AUROC and lead-time in predicting clinical deterioration in pediatric inpatients 24 to 48 hours in advance compared with I-PEWS. Further work is needed to optimize model positive predictive value to allow for integration into clinical practice.

Kernel Transcriptome Profiles of Susceptible Wheat Genotypes in Response to Wheat Dwarf Bunt.

Wheat dwarf bunt is caused by Tilletia controversa J. G. Kühn (TCK), which is a serious fungal diseases affecting kernels of wheat. In order to identify candidate genes involved in the abnormal development of kernels in wheat, we used RNA sequencing technology to analyze the transcriptome of the abnormal and healthy kernels of a susceptible variety (Yili053) at the mid-filling stage, late-filling stage, and maturity stage, respectively. The differentially expressed genes (DEGs) were analyzed, and there were 3930 DEGs, 28,422 DEGs, and 20,874 DEGs found at the mid-filling stage, late-filling stage, and maturity stage in Yili053, respectively. A total of 1592 DEGs (506 DEGs up-regulated) showed continuously differential expression in the three stages. Gene ontology analysis showed that these DEGs were related to biological regulation, metabolic processes, and the response to stimulus. Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that these DEGs play major roles in pathways including photosynthesis, carbon metabolism, carbon fixation in photosynthetic organisms, and glyoxylate and dicarboxylate metabolism. Moreover, we predicted that 13 MADS-MIKC transcription factors, which were continuously up-regulated, were crucial for regulating the maturation and senescence of eukaryotes. Some 21 genes related to the plant hormone signaling transduction pathway and 61 genes related to the response to stimulus were analyzed. A total of 26 of them were successful validated with a qPCR analysis. These genes were thought to be involved in the abnormal development of kernels infected by TCK. A transcriptomics analysis of wheat kernels in response to TCK will contribute to understanding the interaction of TCK and wheat, and may provide a basis for knowledge of molecular events in the abnormal development of kernels, which will be helpful for more efficient TCK management.

Combining Transcriptome and Whole Genome Re-Sequencing to Screen Disease Resistance Genes for Wheat Dwarf Bunt.

Wheat dwarf bunt is a damaging disease caused by Tilletia controversa Kühn (TCK). Once the disease infects wheat, it is difficult to control and will significantly reduce wheat output and quality. RNA sequencing and whole genome re-sequencing were used to search for potential TCK resistance genes in Yili 053 (sensitive variety) and Zhongmai 175 (moderately resistant variety) in the mid-filling, late-filling, and maturity stages. The transcriptomic analysis revealed 11 potential disease resistance genes. An association analysis of the findings from re-sequencing found nine genes with single nucleotide polymorphism mutations. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that three up-regulated genes were involved in the synthesis of benzoxazinone and tryptophan metabolism. Additionally, quantitative real-time polymerase chain reaction confirmed the RNA sequencing results. The results revealed novel TCK resistance genes and provide a theoretical basis for researching the function of resistance genes and molecular breeding.

A novel ensemble approach for estimating the competency of bank telemarketing.

Having a reliable understanding of bank telemarketing performance is of great importance in the modern world of economy. Recently, machine learning models have obtained high attention for this purpose. In order to introduce and evaluate cutting-edge models, this study develops sophisticated hybrid models for estimating the success rate of bank telemarketing. A large free dataset is used which lists the clients' information of a Portuguese bank. The data are analyzed by four artificial neural networks (ANNs) trained by metaheuristic algorithms, namely electromagnetic field optimization (EFO), future search algorithm (FSA), harmony search algorithm (HSA), and social ski-driver (SSD). The models predict the subscription of clients for a long-term deposit by evaluating nineteen conditioning parameters. The results first indicated the high potential of all four models in analyzing and predicting the subscription pattern, thereby, revealing the competency of neuro-metaheuristic hybrids. However, comparatively speaking, the EFO yielded the most reliable approximation with an area under the curve (AUC) around 0.80. FSA-ANN emerged as the second-accurate model followed by the SSD and HSA with respective AUCs of 0.7714, 0.7663, and 0.7160. Moreover, the superiority of the EFO-ANN is confirmed against several conventional models from the previous literature, and finally, it is introduced as an effective model to be practically used by banking institutions for predicting the likelihood of deposit subscriptions.

LibGen: Generating High Quality Spectral Libraries of Natural Products for EAD-, UVPD-, and HCD-High Resolution Mass Spectrometers.

Compound annotation using spectral-matching algorithms is vital for (MS/MS)-based metabolomics research, but is hindered by the lack of high-quality reference MS/MS library spectra. Finding and removing errors from libraries, including noise ions, is mostly done manually. This process is both error-prone and time-consuming. To address these challenges, we have developed an automated library curation pipeline, LibGen, to universally build novel spectral libraries. This pipeline corrects mass errors, denoises spectra by subformula assignments, and performs quality control of the reference spectra by calculating explained intensity and spectral entropy. We employed LibGen to generate three high-quality libraries with chemical standards of 2241 natural products. To this end, we used an IQ-X orbital ion trap mass spectrometer to generate 1947 classic high-energy collision dissociation spectra (HCD) as well as 1093 ultraviolet-photodissociation (UVPD) mass spectra. The third library was generated by an electron-activated collision dissociation (EAD) 7600 ZenoTOF mass spectrometer yielding 3244 MS/MS spectra. The natural compounds covered 140 chemical classes from prenol lipids to benzypyrans with >97% of the compounds showing <0.2 Tanimoto-similarity, demonstrating a very high structural variance. Mass spectra showed much higher information content for both UVPD- and EAD-mass spectra compared to classic HCD spectra when using spectral entropy calculations. We validated the denoising algorithm by acquiring MS/MS spectra at high concentration and at 13-fold diluted chemical standards. At low concentrations, a higher proportion of spectra showed apparent fragment ions that could not be explained by subformula losses of the parent molecule. When more than 10% of the total intensity of MS/MS fragments was regarded as noise ions, spectra were considered as low quality and were not included in the libraries. As the overall process is fully automated, LibGen can be utilized by all researchers who create or curate mass spectral libraries. The libraries we created here are publicly available at MassBank.us.

Bis-peri-dinaphtho-rylenes: Facile Synthesis via Radical-Mediated Coupling Reactions and their Distinctive Electronic Structures.

Polycyclic aromatic hydrocarbons (PAHs) with a one-dimensional (1D), ribbon-like structure have the potential to serve as both model compounds for corresponding graphene nanoribbons (GNRs) and as materials for optoelectronics applications. However, synthesizing molecules of this type with extended π-conjugation presents a significant challenge. In this study, we present a straightforward synthetic method for a series of bis-peri-dinaphtho-rylene molecules, wherein the peri-positions of perylene, quaterrylene, and hexarylene are fused with naphtho-units. These molecules were efficiently synthesized primarily through intramolecular or intermolecular radical coupling of in situ generated organic radical species. Their structures were confirmed using X-ray crystallographic analysis, which also revealed a slightly bent geometry due to the incorporation of a cyclopentadiene ring at the bay regions of the rylene backbones. Bond lengh analysis and theoretical calculations indicate that their electronic structures resemble pyrenacenes more than quinoidal rylenes. That is, the aromatic sextets are predominantly localized along the long axis of the skeletones. As the chain length increases, these molecules exhibit enhanced electronic absorption with a bathochromic shift, and multiple amphoteric redox waves. This study introduces a novel synthetic approach for generating 1D extended PAHs and GNRs, along with their structure-dependent electronic properties.

Prediction of early neurological deterioration in acute ischemic stroke patients treated with intravenous thrombolysis.

A proportion of acute ischemic stroke (AIS) patients suffer from early neurological deterioration (END) within 24 hours following intravenous thrombolysis (IVT), which greatly increases the risk of poor prognosis of these patients. Therefore, we aimed to explore the predictors of early neurological deterioration of ischemic origin (ENDi) in AIS patients after IVT and develop a nomogram prediction model. This study collected 244 AIS patients with post-thrombolysis ENDi as the derivation cohort and 155 patients as the validation cohort. To establish a nomogram prediction model, risk factors were identified by multivariate logistic regression analysis. The results showed that neutrophil to lymphocyte ratio (NLR) (OR 2.616, 95% CI 1.640-4.175, P < 0.001), mean platelet volume (MPV) (OR 3.334, 95% CI 1.351-8.299, P = 0.009), body mass index (BMI) (OR 1.979, 95% CI 1.285-3.048, P = 0.002) and atrial fibrillation (AF) (OR 8.012, 95% CI 1.341-47.873, P = 0.023) were significantly associated with ENDi. The area under the curve of the prediction model constructed from the above four factors was 0.981 (95% CI 0.961-1.000) and the calibration curve was close to the ideal diagonal line. Therefore, this nomogram prediction model exhibited good discrimination and calibration power and might be a reliable and easy-to-use tool to predict post-thrombolysis ENDi in AIS patients.