Insufficient Plasma Melatonin and Its Association With Neuropsychiatric Impairments in Patients With T2DM.

Purpose: Type 2 diabetes mellitus (T2DM) is associated with multiple neuropsychiatric impairments, including cognitive dysfunction, and melatonin (MLT) plays a crucial role in maintaining normal neuropsychiatric functions. This study is aimed at investigating the change in plasma MLT levels and its association with neuropsychiatric impairments in T2DM patients. Methods: One hundred twenty-six T2DM patients were recruited, and their demographics and clinical data were collected. Apart from the plasma glycated hemoglobin (HbA1c) levels and other routine metabolic indicators, the plasma concentrations of MLT, C-reactive protein (CRP), Interleukin 6 (IL-6), soluble myeloid triggered receptor 1 (sTREM 1), and receptor 2 (sTREM 2) were measured. Moreover, the executive function and depressive tendency were evaluated via the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) and the Epidemiological Research Center Depression Scale (CES-D), respectively. Result: Compared with the low HbA1c group, the T2DM patients in the high HbA1c group presented lower plasma MLT levels but higher plasma concentrations of inflammatory biomarker levels, together with higher scores in the BRIEF-A and CES-D scales. Moreover, results of the Pearson correlation test showed that the plasma MLT levels were negatively correlated with the BRIEF-A and CES-D scores, as well as plasma concentrations of HbA1c and inflammatory indications, indicating that MLT may mediate their neuroinflammation and neuropsychiatric impairments. Furthermore, the ROC curve results indicated that plasma MLT levels have a predictive effect on executive impairment and depressive status in T2DM patients. Conclusion: MLT levels decreased in patients with T2DM and were associated with neuropsychiatric impairments and inflammatory status, and MLT might be developed as a therapeutic agent and predictive indicator for T2DM-associated executive impairment and depression status.

Differential toxic and antiepileptic features of Vigabatrin raceme and its enantiomers.

BACKGROUND: The study aimed to investigate the potential pharmacological and toxicological differences between Vigabatrin (VGB) and its enantiomers S-VGB and R-VGB. The researchers focused on the toxic effects and antiepileptic activity of these compounds in a rat model. METHODS: The epileptic rat model was established by intraperitoneal injection of kainic acid, and the antiepileptic activity of VGB, S-VGB, and VGB was observed, focusing on the improvements in seizure latency, seizure frequency and sensory, motor, learning and memory deficits in epileptic rats, as well as the hippocampal expression of key molecular associated with synaptic plasticity and the Wnt/ß-catenin/GSK 3ß signaling pathway. The acute toxic test was carried out and the LD50 was calculated, and tretinal damages in epileptic rats were also evaluated. RESULT: The results showed that S-VGB exhibited stronger antiepileptic and neuroprotective effects with lower toxicity compared to VGB raceme. These findings suggest that S-VGB and VGB may modulate neuronal damage, glial cell activation, and synaptic plasticity related to epilepsy through the Wnt/ß-catenin/GSK 3ß signaling pathway. The study provides valuable insights into the potential differential effects of VGB enantiomers, highlighting the potential of S-VGB as an antiepileptic drug with reduced side effects. CONCLUSION: S-VGB has the highest antiepileptic effect and lowest toxicity compared to VGB and R-VGB.

Exploration of beauvericin's toxic effects and mechanisms in human astrocytes and N-acetylcysteine's protective role.

Beauvericin (BEA) is a newly identified mycotoxin produced by various Fusarium species, and its contamination in food and animal feed is widespread globally. This mycotoxin demonstrates cytotoxic effects by inducing oxidative stress in multiple models. Furthermore, evidence indicates that BEA possesses diverse toxic activities, making it a promising candidate for toxicological research. Recent studies have highlighted the ability of BEA to traverse the blood-brain barrier, suggesting its potential neurotoxicity. However, limited information is available regarding the neurotoxic effects of BEA on human astrocytes. Therefore, this study aimed to assess the neurotoxic effects of BEA on the Gibco® Human Astrocyte (GHA) cell line and elucidate the underlying mechanisms. Additionally, the study aimed to investigate the protective effects of the antioxidant N-acetylcysteine (NAC) against BEA-induced toxicity. The data show that exposure to BEA within the 2.5-15 µM concentration range resulted in concentration-dependent cytotoxicity. BEA-treated cells exhibited significantly increased levels of reactive oxygen species (ROS), while intracellular glutathione (GSH) content was significantly reduced. Western blot analysis of cells treated with BEA revealed altered protein levels of Bax, cleaved caspase-9, and caspase-3, along with an increased Bax/Bcl-2 ratio, indicating the induction of apoptosis. Additionally, BEA exposure triggered antioxidant responses, as evidenced by increased protein expression of Nrf2, HO-1, and NQO1. Significantly, pretreatment with NAC partially attenuated the significant toxic effects of BEA. In conclusion, our findings suggest that BEA-induced cytotoxicity in GHA cells involves oxidative stress-associated apoptosis. Furthermore, NAC demonstrates potential as a protective agent against BEA-induced oxidative damage.

Insight into the fate of nitrogen during char thermal conversion and the influence mechanism of potassium: A theoretical research.

Nitrogen oxides (NOₓ) are primary pollutants produced during biomass combustion. During the devolatilization stage, char nitrogen (char(N)) is formed. In the subsequent char combustion stage, char(N) can decompose directly into NOx precursors or engage in heterogeneous reactions with O2 or NO to form NO and N2. Nonetheless, a comprehensive understanding of the reaction mechanisms and competitiveness of char(N) migration, especially the influence of the alkali metal potassium (K) present in biomass, remains incomplete. Building on the Zigzag char(N) models, the present study delves into the migration reactions of char(N), assessing their competitive dynamics through the integration of density functional theory, electronic structure analysis, and conventional transition state theory. Furthermore, it examines the impact of K on char(N) conversion. The competitiveness of the heterogeneous reactions follows the sequence: heterogeneous reduction of NO to N2 > heterogeneous oxidation of char(N) to NO > decomposition of char(N) to NOx precursors. Moreover, the formation of HCN is more favorable than NH3 production. The successive conversion from char(N) to NO and then to N2 is the predominant migration route for char(N), with NO generation as the pivotal step. The less preferred char(N) migration route involves decomposition to NH3/HCN, followed by oxidation to NOx within the main combustion zone, which cannot be mitigated by char. K can accelerate NO generation and sustain the primacy of the heterogeneous NO reduction, consequently enhancing the oxidation-reduction process of char(N). As a result, K plays a constructive role in managing NOx emissions during the thermal conversion of char.

Efficient Exploration of Chemical Compound Space Using Active Learning for Prediction of Thermodynamic Properties of Alkane Molecules.

We introduce an exploratory active learning (AL) algorithm using Gaussian process regression and marginalized graph kernel (GPR-MGK) to sample chemical compound space (CCS) at minimal cost. Targeting 251,728 enumerated alkane molecules with 4-19 carbon atoms, we applied the AL algorithm to select a diverse and representative set of molecules and then conducted high-throughput molecular simulations on these selected molecules. To demonstrate the power of the AL algorithm, we built directed message-passing neural networks (D-MPNN) using simulation data as the training set to predict liquid densities, heat capacities, and vaporization enthalpies of the CCS. Validations show that D-MPNN models built on the smallest training set considered in this work, which consists of 313 molecules or 0.124% of the original CCS, predict the properties with R2 > 0.99 against the computational data and R2 > 0.94 against the experimental data. The advantage of the presented AL algorithm is that the predicted uncertainty of GPR depends on only the molecular structures, which renders it compatible with high-throughput data generation.

The day-night differences in cognitive and anxiety-like behaviors of mice after chronic sleep restriction.

Animal behavioral tests are often conducted during the day. However, rodents are nocturnal animals and are primarily active at night. The aim of this study was to determine whether there are diurnal changes in cognitive and anxiety-like performance of mice following chronic sleep restriction (SR). We also investigated whether this phenotypic difference is related to the diurnal variation of glymphatic clearance of metabolic wastes. Mice received 9-day SR by the use of the modified rotating rod method, followed by the open field, elevated plus maze, and Y-maze tests conducted during the day and at night, respectively. Brain ß-amyloid (Aß) and tau protein levels, the polarity of aquaporin4 (AQP4), a functional marker of the glymphatic system, and glymphatic transport ability were also analyzed. SR mice exhibited cognitive impairment and anxiety-like behaviors during the day, but not at night. AQP4 polarity and glymphatic transport ability were higher during the day, with lower Aß1-42 , Aß1-40 , and P-Tau levels in the frontal cortex. These day-night differences were totally disrupted after SR. These results reveal the diurnal changes in behavioral performance after chronic SR, which may be related to circadian control of AQP4-mediated glymphatic clearance of toxic macromolecules from the brain.

Atroposelective Synthesis of Heterobiaryls through Ring Formation.

Atropisomeric heterobiaryls play a vital role in natural products, chiral ligands, organocatalysts, and other research fields, which have aroused great interest from chemists in recent years. Until now, a growing number of optically active heterobiaryls based on indole, quinoline, isoquinoline, pyridine, pyrrole, azole, and benzofuran skeletons have been successfully synthesized through metal or organic catalytic cross-coupling, functionalization of prochiral or racemic heterobiaryls, and ring formation. Among different strategies for the atroposelective synthesis of heterobiaryls, the strategy of ring formation has become a vital tool toward this goal. In this review, we summarize the enantioselective synthesis of axially chiral heterobiaryls through ring formation approaches, such as cycloaddition, cyclization, and chirality conversion. Meanwhile, the reaction mechanism and the corresponding applications of the chiral heterobiaryls are also discussed.

Potential Energy Surfaces Sampled in Cremer-Pople Coordinates and Represented by Common Force Field Functionals for Small Cyclic Molecules.

The complex conformations of the cyclic moieties impact the physical and chemical properties of molecules. In this work, we chose 22 molecules of four-, five-, and six-membered rings and performed a thorough conformational sampling using Cremer-Pople coordinates. With consideration of symmetries, we obtained a total of 1504 conformational structures for four-membered, 5576 for five-membered, and 13509 for six-membered rings. All well-known and many less well-known conformers for each molecule were identified. We represented the potential energy surfaces (PESs) by fitting the data to common analytical force field (FF) functional forms. We found that the general features of PESs can be described by the essential FF functional forms; however, the accuracy of representation can be improved remarkably by including the torsion-bond and torsion-angle coupling terms. The best fit yields R-squared (R2) values close to 1.0 and mean absolute errors in energy less than 0.3 kcal/mol.

Modular Construction of Heterobiaryl Atropisomers and Axially Chiral Styrenes via All-Carbon Tetrasubstituted VQMs.

Here we report a new type of chiral all-carbon tetrasubstituted VQMs generated via chiral phosphoric acids catalyzed nucleophilic addition of 2-alkynylnaphthols to o-quinone methides or imines, which can be captured intramolecularly as a result of cycloaddition reaction. A new class of naphthyl-2H-chromenes bearing axially and centrally chiral elements and axially chiral quinone-naphthols were prepared efficiently with good to excellent yields, diastereoselectivities and enantioselectivities. Noteworthy, the enantioselective cycloaddition of alkynylnaphthols with o-quinone methides proceeded via a [2+2] cycloaddition, followed by a retro-4π-electrocyclization and a 6π re-cyclization. While the cycloaddition of alkynylnaphthols with imines proceeded via a sequential [2+4] cycloaddition and an auto oxidation reaction. Moreover, the obtained axially chiral naphthols can be converted into valuable phosphine ligands and other functional molecules.

A Dehydrogenative Inverse Electron Demand Diels-Alder Reaction for the Synthesis of Functionalized Pyranones.

An efficient dehydrogenative inverse electron demand Diels-Alder reaction of isopropyl and prenyl benzene derivatives with electron-deficient dienes followed by decarboxylation has been reported for the first time. The much broader substrate scope of dienophiles and electron-deficient dienes led to biologically valuable pyranones in good to excellent yields.

Organocatalytic cycloaddition of alkynylindoles with azonaphthalenes for atroposelective construction of indole-based biaryls.

The axially chiral indole-aryl motifs are present in natural products and biologically active compounds as well as in chiral ligands. Atroposelective indole formation is an efficient method to construct indole-based biaryls. We report herein the result of a chiral phosphoric acid catalyzed asymmetric cycloaddition of 3-alkynylindoles with azonaphthalenes. A class of indole-based biaryls were prepared efficiently with excellent yields and enantioselectivities (up to 98% yield, 99% ee). Control experiment and DFT calculations illustrate a possible mechanism in which the reaction proceeds via a dearomatization of indole to generate an allene-iminium intermediate, followed by an intramolecular aza-Michael addition. This approach provides a convergent synthetic strategy for enantioselective construction of axially chiral heterobiaryl backbones.

Scandium Triflate Catalyzed Tandem Transfer Hydrogenation and Cyclization Reaction of o-Aminobenzaldehydes and o-Aminoacetophenone with Alcohols.

An effective Sc-catalyzed transfer hydrogenation and cyclization tandem reaction has been achieved. This process showed excellent functional group compatibility and good yields. A variety of benzoxazines were produced with primary or secondary alcohols as a hydrogen source. Furthermore, the utility of this newly developed protocol is demonstrated through scaled-up experiment, late-stage modification, and preliminary exploration of enantioselective synthesis.

A Comparative Study of Marginalized Graph Kernel and Message-Passing Neural Network.

This work proposes a state-of-the-art hybrid kernel to calculate molecular similarity. Combined with Gaussian process models, the performance of the hybrid kernel in predicting molecular properties is comparable to that of the directed message-passing neural network (D-MPNN). The hybrid kernel consists of a marginalized graph kernel (MGK) and a radial basis function (RBF) kernel that operate on molecular graphs and global molecular features, respectively. Bayesian optimization was used to obtain the optimal hyperparameters for both models. The comparisons are performed on 11 publicly available data sets. Our results show that their performances are similar, their prediction errors are correlated, and the ensemble predictions of the two models perform better than either of them. Through principal component analysis, we found that the molecular embeddings of the hybrid kernel and the D-MPNN are also similar. The advantage of D-MPNN lies in the computational efficiency and scalability of large-scale data, while the advantage of the graph kernel models lies in the accurate uncertainty quantification.

Pros and cons of the time-dependent hybrid density functional approach for calculating the optical spectra of solids: a case study of CeO2.

The prediction of optical spectra of complex solids remains a great challenge for first-principles calculations due to the huge computational cost of the state-of-the-art many-body perturbation theory based GW-Bethe Salpeter equation (BSE) approach. An alternative method is the time-dependent density-functional theory (TDDFT) based on hybrid exchange-correlation functionals, which involves the essential ingredients of electron-hole interactions in its formalism in contrast to its local/semi-local functional counterparts. In this work, we investigate the optical absorption spectra of ceria (CeO2), a prototypical lanthanide oxide with a 4f0 configuration, utilizing TDDFT based on four well-established hybrid functionals for ground state DFT calculations. All four functionals reproduce well the excitonic features of the experimental optical spectra, in spite of the significant differences in their band structures arising from different hybridization parameters (i.e. the fraction of the Hartree-Fock exchange and the screening parameter). It is demonstrated that the apparently weak dependence of the resulting optical spectra on the employed functionals is quite universal and applies to simple semiconductors such as Si and GaAs and insulator LiF as well. This study highlights the feasibility of TDDFT based on existing hybrids to describe optical spectra of solids, and also, points out the difficulty of obtaining accurate exciton binding energies using these hybrid functionals due to the strong functional dependence of quasi-particle band structures.

Predicting Single-Substance Phase Diagrams: A Kernel Approach on Graph Representations of Molecules.

This work presents a Gaussian process regression (GPR) model on top of a novel graph representation of chemical molecules that predicts thermodynamic properties of pure substances in single, double, and triple phases. A transferable molecular graph representation is proposed as the input for a marginalized graph kernel, which is the major component of the covariance function in our GPR models. Radial basis function kernels of temperature and pressure are also incorporated into the covariance function when necessary. We predicted three types of representative properties of pure substances in single, double, and triple phases, i.e., critical temperature, vapor-liquid equilibrium (VLE) density, and pressure-temperature density. The accuracy of the models is nearly identical to the precision of the experimental measurements. Moreover, the reliability of our predictions can be quantified on a per-sample basis using the posterior uncertainty of the GPR model. We compare our model against Morgan fingerprints and a graph neural network to further demonstrate the advantage of the proposed method.

[A Preliminary Study of Applying Geometric Deep Learning in Brain Morphometry for Diagnosis of Alzheimer's Disease].

OBJECTIVE: A predictive model of Alzheimer's disease (AD) was established based on brain surface meshes and geometric deep learning, and its performance was evaluated. METHODS: Seventy-six clinically diagnosed AD patients and 83 healthy older adults were enrolled and randomly assigned to the training set and the test set according to a 4-to-1 ratio. Brain surface mesh was constructed from 3-D T1-weighted high-resolution structural MR volumes of each participant. After applying a series of simplification to the surface meshes, the training set was fed into the geometric deep neural network for training. The performance of the prediction model was evaluated with the test set, and the evaluation metrics included accuracy, sensitivity and specificity. RESULTS: The prediction model trained on the right brain surface meshes with 6 000 faces achieved the best performance, with accuracy reaching 93.8%, sensitivity, 91.7%, and specificity, 94.1%. The evolution of the brain surface meshes during convolution and pooling revealed that AD patients had diffuse brain tissue loss compared with healthy older adults. CONCLUSION: Morphological brain analysis based on mesh data and geometric deep learning has great potential in the differential diagnosis of AD.

Selectfluor-Mediated Stereoselective [1 + 1 + 4 + 4] Dimerization of Styrylnaphthols.

Stereoselective [1 + 1 + 4 + 4] dimerization of 1-styrylnaphthols has been developed by using Selectfluor as the oxidant for the first time. The reaction was compatible with various functional groups, giving a class of ethanodinaphtho[b,f][1,5]dioxocines with novel 3D skeletons. DFT calculations indicate that this method merges an intriguing stereoselective intermolecular 1 + 1 radical coupling to construct a bridged C-C bond and then an intramolecular [4 + 4] formal cycloaddition of the in situ generated o-quinone methide intermediate.

Manipulation of cholesteric liquid crystal phase behavior and molecular assembly by molecular chirality.

Molecular simulation is used to study the effect of molecular chirality on liquid crystalline phase transition and molecular assembly behavior. Based on a flexible chain (FCh) model with helical arrangement of side beads, the phase behavior of FCh models with various molecular chiralities are studied as functions of pressure (or density). By modifying the molecular chirality of FCh, we can manipulate the relative stability of the nematic and cholesteric phases continuously; and we found that increasing molecular chirality may destabilize cholesteric order due to the effective reduction of chiral interactions. A semismectic phase is identified in the high-density region, in which the two-dimensional fluid layers overlap due to shift alignment formed by FCh particles. The global phase diagram of the FCh model is constructed and the potential energy surface is calculated to elucidate the formation of cholesteric phase in terms of two-body interactions.

[Myocardial Magnetic Resonance Texture Characteristics of Healthy Volunteers].

OBJECTIVE: To determine the myocardial texture features of cardiac magnetic resonance (CMR) in healthy adult Han populations. METHODS: 59 healthy Han volunteers were recruited for this study from May 2016 to November 2017. CMR examinations were performed on the participants with a 3.0T scanner (Tim Trio, Siemens Medical Solution) to estimate the functional parameters, Native T1 value and ECV. Texture analysis (TA) was performed on the region of interest (ROI) in the left ventricle myocardium on T1 mapping images, with 40 myocardial texture features being extracted. Differences in the myocardial texture features across gender and age groups were analyzed through Student's t-tests or Wilcoxon signed-rank tests. Spearman correlations were analyzed between the myocardial texture features and age, native T1 value and extracellular volume (ECV). RESULTS: Of the 59 participants, 28 were women and 29 were in the younger age group (< 45 years old). The male participants had higher left ventricular mass index (Lvmassi) and lower native T1 than their female counterparts (P < 0.01). No gender differences in blood pressure, heart rate, left ventricular ejection fraction (LVEF) and ECV values were found. Ten of the forty myocardial texture features showed gender differences, including two first order features and eight Grey-level co-occurrence matrix (GLCM) features. Gender differences appeared in five first order features and eight GLCM features in the younger group (< 45 years old), but not in the older group (≥45 years old). Eight myocardial texture features were correlated with age, including five first order features and three GLCM features (all P < 0.01). Six first-order texture features were correlated with Native T1 values of the left ventricle middle myocardium. Three first-order texture features were correlated with ECV. CONCLUSION: Myocardial texture features in T1 mapping images vary by gender and age in healthy Han populations.

Large carotid body tumor successfully resected in hybrid operating theatre: A case report.

BACKGROUND: Surgical treatment for large carotid body tumor (CBT), particularly the Shamblin III type, is challenging and rarely reported. CASE SUMMARY: In July 2014, a 63-year-old woman presented to our hospital with a large CBT (130 mm × 60 mm × 70 mm). The lesion was hypervascular, spanned from the first to the seventh cervical vertebra, and adhered to the right common carotid artery (CCA), internal carotid artery (ICA) and external carotid artery (ECA). The resection was carried out in a hybrid operating theatre. First, we used Onyx gel to embolize the feeding artery. An ICA balloon was used to prevent gel entry into the ICA. After shrinkage and hardening of the CBT, we quickly resected the CBT as well as a part of the ECA that adhered to the CBT. A vascular shunt was inserted between CCA and ICA, and the part where the ICA was cut off from the CCA was directly sutured. A follow-up at four years later showed no neurological damage. CONCLUSION: For large hypervascular CBT, embolization of the feeding artery prior to resection is helpful. The hybrid operating theatre is the ideal platform to carry out such operations.