Novel inflammatory and insulin resistance indices provide a clue in cerebral amyloid angiopathy.

This study investigated the correlation of newly identified inflammatory and insulin resistance indices with cerebral amyloid angiopathy (CAA), and explored their potential to differentiate CAA from hypertensive arteriopathy (HA). We retrospectively analyzed 514 consecutive patients with cerebral small vessel disease (CSVD)-related haemorrhage, comparing the differences in novel inflammatory and insulin resistance indices between patients with CAA and HA. Univariate regression, LASSO and multivariate regression were used to screen variables and construct a classification diagnosis nomogram. Additionally, these biomarkers were explored in patients with mixed haemorrhagic CSVD. Inflammatory indices were higher in CAA patients, whereas insulin resistance indices were higher in HA patients. Further analysis identified neutrophil-to-lymphocyte ratio (NLR, OR 1.17, 95% CI 1.07-1.30, P < 0.001), and triglyceride-glucose index (TyG, OR = 0.56, 95% CI 0.36-0.83, P = 0.005) as independent factors for CAA. Therefore, we constructed a CAA prediction nomogram without haemorrhagic imaging markers. The nomogram yielded an area under the curve (AUC) of 0.811 (95% CI 0.764-0.865) in the training set and 0.830 (95% CI 0.718-0.887) in the test set, indicating an ability to identify high-risk CAA patients. These results show that CSVD patients can be phenotyped using novel inflammatory and insulin resistance indices, potentially allowing identification of high-risk CAA patients without haemorrhagic imaging markers.

Causal Effects of Blood Metabolites and Obstructive Sleep Apnea: A Mendelian Randomization Study.

BACKGROUND: Obstructive sleep apnea (OSA) is one of the most common forms of sleep-disordered breathing. Studies have shown that certain changes in metabolism play an important role in the pathophysiology of OSA. However, the causal relationship between these metabolites and OSA remains unclear. AIMS: We use a mendelian randomization (MR) approach to investigate the causal associations between the genetic liability to metabolites and OSA. METHODS: We performed a 2-sample inverse-variance weighted mendelian randomization analysis to evaluate the causal effects of genetically determined 486 metabolites on OSA. Multiple sensitivity analyses were performed to assess pleiotropy. We used multivariate mendelian randomization analyses to assess confounding factors and mendelian randomization Bayesian model averaging to rank the significant biomarkers by their genetic evidence. We also conducted a metabolic pathway analysis to identify potential metabolic pathways. RESULTS: We identified 14 known serum metabolites (8 risk factors and 6 protective factors) and 12 unknown serum metabolites associated with OSA. These 14 known metabolites included 8 lipids( 1-arachidonoylglycerophosphoethanolamine, Tetradecanedioate, Epiandrosteronesulfate, Acetylca Glycerol3-phosphate, 3-dehydrocarnitine, Margarate17:0, Docosapentaenoaten3;22:5n3), 3 Aminoacids (Isovalerylcarnitine,3-methyl-2-oxobutyrate,Methionine), 2 Cofactors and vitamins [Bilirubin(E,ZorZ,E),X-11593--O-methylascorbate], 1Carbohydrate(1,6-anhydroglucose). We also identified several metabolic pathways that involved in the pathogenesis of OSA. CONCLUSION: MR (mendelian randomization) approach was performed to identify 6 protective factors and 12 risk factors for OSA in the present study. 3-Dehydrocarnitine was the most significant risk factors for OSA. Our study also confirmed several significant metabolic pathways that were involved in the pathogenesis of OSA. Valine, leucine and isoleucine biosynthesis metabolic pathways were the most significant metabolic pathways that were involved in the pathogenesis of OSA.

Rhodium-Catalyzed Intramolecular Nitrogen Atom Insertion into Arene Rings.

In this study, we describe the direct insertion of an intramolecular nitrogen atom into an aromatic C-C bond. In this transformation, carbamoyl azides are activated by a Rh catalyst and subsequently directly inserted into the C-C bond of an arene ring to access fused azepine products. This transformation is challenging, owing to the existence of a competitive C-H amination pathway. The use of a paddlewheel dirhodium complex Rh2(esp)2 effectively inhibited the undesired C-H insertion. Density functional theory calculations were performed to reveal the reaction mechanism and origin of the chemoselectivity of the Rh-catalyzed reactions. The novel fused azepine products are highly robust and allow for downstream diversification.

Correlation between neutrophil gelatinase phase lipocalin and cerebral small vessel disease.

Background: Cerebral small vessel disease (CSVD) is common in the elderly population. Neutrophil gelatinase-associated lipocalin (NGAL) is closely related to cardiovascular and cerebrovascular diseases. NGAL causes pathological changes, such as damage to the vascular endothelium, by causing inflammation, which results in other related diseases. The purpose of this study was to investigate whether serum NGAL levels could predict disease severity in patients with CSVD. Methods: The patients with CSVD who visited the Department of Neurology at the First Affiliated Hospital of Zhengzhou University between January 2018 and June 2022 were prospectively included. The total CSVD burden score was calculated using whole-brain magnetic resonance imaging (MRI), and the patients were divided into a mild group (total CSVD burden score < 2 points) and a severe group (total CSVD burden score ≥ 2 points). Age, sex, height, smoking and alcohol consumption history, medical history, and serological results of patients were collected to perform the univariate analysis. Multivariate logistic regression was used to analyze the risk factors that affect CSVD severity. The multiple linear regression method was used to analyze which individual CSVD markers (periventricular white matter hyperintensities, deep white matter hyperintensities, lacune, and cerebral microbleed) play a role in the association between total CSVD burden score and NGAL. Results: A total of 427 patients with CSVD (140 in the mild group and 287 in the severe group) were included in the study. A multivariate logistic regression analysis showed that the following factors were significantly associated with CSVD severity: male sex [odds ratio(OR), 1.912; 95% confidence interval (CI), 1.150-3.179], age (OR, 1.046; 95% CI, 1.022-1.070), history of cerebrovascular disease (OR, 3.050; 95% CI, 1.764-5.274), serum NGAL level (OR, 1.005; 95% CI, 1.002-1.008), and diabetes (OR, 2.593; 95% CI, 1.424-4.722). A multivariate linear regression shows that periventricular white matter hyperintensities and cerebral microbleed are associated with serum NGAL concentrations (P < 0.05). Conclusion: Serum NGAL level is closely related to CSVD severity and is a risk factor for the burden of CSVD brain damage. Serum NGAL has high specificity in reflecting the severity of CSVD.

Smoking, Coffee Consumption, Alcohol Intake, and Obstructive Sleep Apnea: A Mendelian Randomization Study.

BACKGROUND: Previous studies revealed that obstructive sleep apnea (OSA) and smoking, alcohol consumption, and coffee intake are closely related. This study aimed to evaluate the causal effect between these factors and OSA. METHODS: The published genome-wide association study data (GWAS) provided genetic tools. We conducted a univariable two-sample Mendelian Randomization (MR) to estimate the causal effect between smoking initiation, never smoking, alcohol consumption, coffee intake, and coffee consumption with the risk of incidence OSA. Inverse variance weighting (IVW) was used as the main method for effect evaluation, and other MR methods were used for sensitivity analysis. After adjusting for body mass index (BMI), hypertension, and diabetes respectively by multivariable MR (MVMR), we further evaluate the causal effect of these factors on OSA. RESULTS: Under univariable MR analysis, we observed that smoking initiation was associated with an increased risk of incidence OSA (OR 1.326, 95% CI 1.001-1.757, p =0.049). Never smoking was associated with decreased risk of OSA (OR 0.872, 95% CI 0.807-0.942, p <0.001). Coffee intake and coffee consumption was associated with an increased incidence of OSA (OR 1.405, 95% CI 1.065-1.854, p =0.016) and (OR 1.330, 95% CI 1.013-1.746, p =0.040). Further multivariate MR showed that the causal relationship between never smoking and OSA existed but not coffee consumption, after adjusting for diabetes and hypertension. However, the all results did not support causality after adjusting for BMI. CONCLUSION: This two-sample MR study showed that genetically predicted smoking and higher coffee intake are causally associated with an increased risk of OSA.

Association of Blood Lipid Profile Components with White Matter Hyperintensity Burden in Cerebral Small Vessel Disease.

BACKGROUND: Cerebral small vessel disease (CSVD) refers to a common cerebrovascular disease and white matter hyperintensities (WMHs) constitute a typical feature of CSVD. However, there has not been a large number of studies investigating the relationship between lipid profile components and WMHs. METHODS: Altogether, 1019 patients with CSVD were enrolled at the First Affiliated Hospital of Zhengzhou University between April 2016 to December 2021. Baseline data were collected for all patients, including demographic characteristics and clinical data. WMH volumes were evaluated by two experienced neurologists using the MRIcro software. Multivariate regression analysis was used to investigate the relationship among the severity of WMHs, blood lipids and common risk factors. RESULTS: Altogether, 1019 patients with CSVD were enrolled, including 255 in the severe WMH group and 764 in the mild WMH group. After including age, sex and blood lipids to construct a multivariate logistic regression equation, we observed that the severity of WMHs was independently predicted by low-density lipoprotein (LDL), homocysteine level and history of cerebral infarction. CONCLUSION: We used WMH volume, a highly accurate measure, to assess its relationship with lipid profiles. The WMH volume increased with a decrease in LDL. This relationship was more significant, especially among the subgroups of patients aged <70 years and men. Patients with cerebral infarction and higher homocysteine levels were more likely to have higher WMH volumes. Our study has provided a reference for clinical diagnosis and therapy, especially for discussing the role of blood lipid profiles in the pathophysiology of CSVD.

Mechanism and Practice of Multifracturing Using Dynamic Loads in a Low-Permeability Coal Reservoir.

The geological conditions of coal reservoirs in China are complex, and the reservoir permeability is generally lower. Multifracturing is an effective method of improving reservoir permeability and coalbed methane (CBM) production. In this study, two types of dynamic loads, CO2 blasting and a pulse fracturing gun (PF-GUN), were used to conduct multifracturing engineering tests in nine surface CBM wells in the Lu'an mining area in the central and eastern parts of the Qinshui Basin. The curves of pressure versus time of the two dynamic loads were obtained in the laboratory. The prepeak pressurization time of the PF-GUN was 200 ms, and that of the CO2 blasting was 2.05 ms, which just falls in the optimum pressurization time of multifracturing. The microseismic monitoring results revealed that, in terms of the fracture morphology, both the CO2 blasting and PF-GUN loads produced multiple sets of fractures in the near-well zone. In the six wells used for the CO2 blasting tests, an average of three branch fractures were produced outside of the main fracture, and the average angle between the main fracture and the branch fractures exceeded 60°. In the three wells stimulated by PF-GUN, an average of two branch fractures were produced outside of the main fracture, and the average angle between the main fracture and the branch fractures was 25-35°. The multifracture characteristics of the fractures formed via CO2 blasting were more obvious. However, a coal seam is a multifracture reservoir with a large filtration coefficient; the fracture will not extend after reaching the maximum scale under a certain gas displacement condition. Compared with the traditional hydraulic fracturing technique, the nine wells used in the multifracturing tests exhibited an obvious stimulation effect with an average increase of 51.4% in daily production. The results of this study provide an important technical reference for the efficient development of CBM in low- and ultralow-permeability reservoirs.

A Multicomponent Nucleic Acid Enzyme-Cleavable Quantum Dot Nanobeacon for Highly Sensitive Diagnosis of Tuberculosis with the Naked Eye.

Clinical tuberculosis (TB) screening and diagnosis are crucial for controlling the spread of this life-threatening infectious disease. In this work, a novel, rapid, and simple colorimetric detection platform for TB was developed based on a quantum dot-based nanobeacon (QD-NB) and multicomponent nucleic acid enzyme (MNAzyme). In the presence of target DNA (IS1081 gene fragment), the recombinase polymerase amplification (RPA) was performed and the amplicons were chemically DNA-denatured and then subjected to MNAzyme reaction. RNA-cleaving MNAzyme assembly included the recognition of target DNA and hybridization with a QD-NB fluorescence probe. Under the addition of Mg2+, the RNA-containing QD-NB as a cleavable substrate could be broken into two DNA fragments, leading to green fluorescence release due to their departure from a black hole quencher (BHQ2). The TB detection could be achieved with the naked eye under a portable and inexpensive UV flashlight. Our results demonstrated that QD-NB-based MNAzyme colorimetric assays improved the detection sensitivity by 1 order of magnitude compared with the detection using RPA. The limit of detection (LOD) of the visual reading was as low as 2 copies/µL (3.3 amol/L). Excellent specificity and reproducibility could also be achieved. Furthermore, the practical application of the colorimetric method for TB diagnosis was verified by 36 clinical TB patients and 20 healthy individuals. The developed QD-NB-based MNAzyme colorimetric assays provided a rapid, convenient, sensitive, and accurate alternative for clinical TB screening and diagnosis.

Enzyme Activity Prediction of Sequence Variants on Novel Substrates using Improved Substrate Encodings and Convolutional Pooling.

Protein engineering is currently being revolutionized by deep learning applications, especially through natural language processing (NLP) techniques. It has been shown that state-of-the-art self-supervised language models trained on entire protein databases capture hidden contextual and structural information in amino acid sequences and are capable of improving sequence-to-function predictions. Yet, recent studies have reported that current compound-protein modeling approaches perform poorly on learning interactions between enzymes and substrates of interest within one protein family. We attribute this to low-grade substrate encoding methods and over-compressed sequence representations received by downstream predictive models. In this study, we propose a new substrate-encoding based on Extended Connectivity Fingerprints (ECFPs) and a convolutional-pooling of the sequence embeddings. Through testing on an activity profiling dataset of haloalkanoate dehalogenase superfamily that measures activities of 218 phosphatases against 168 substrates, we show substantial improvements in predictive performances of compound-protein interaction modeling. In addition, we also test the workflow on three other datasets from the halogenase, kinase and aminotransferase families and show that our pipeline achieves good performance on these datasets as well. We further demonstrate the utility of this downstream model architecture by showing that it achieves good performance with six different protein embeddings, including ESM-1b (Rives et al., 2021), TAPE (Rao et al., 2019), ProtBert, ProtAlbert, ProtT5, and ProtXLNet (Elnaggar et al., 2021). This study provides a new workflow for activity prediction on novel substrates that can be used to engineer new enzymes for sustainability applications.

Ultra-Broadband, Omnidirectional, High-Efficiency Metamaterial Absorber for Capturing Solar Energy.

In this study, we investigated an absorber based on a center-aligned tandem nanopillar array for ultra-broadband solar energy harvesting theoretically. A high-efficiency, omnidirectional absorber was obtained by introducing the center-aligned tandem nanopillar array embedded in an Al2O3 dielectric layer. The multi-coupling modes at different wavelengths were interpreted. The strong absorption can be adjusted by changing the radii and heights of nanopillars. According to the simulation results, the average absorptance of the absorber exceeded 94% in the wavelength range from 300 nm to 2000 nm. In addition, the high-efficiency absorption was insensitive to the incident angle and polarization state. The research not only proposed an absorber which possesses a huge potential value for application areas, such as thermal photovoltaic systems, infrared detection, and isotropic absorption sensors, but also pointed out a new way to design an absorber with high efficiency in an ultrabroad wavelength range.

Rapid syntheses of N-fused heterocycles via acyl-transfer in heteroaryl ketones.

The wide-ranging potencies of bioactive N-fused heterocycles inspire the development of synthetic transformations that simplify preparation of their complex, diverse structural motifs. Heteroaryl ketones are ubiquitous, readily available, and inexpensive molecular scaffolds, and are thus synthetically appealing as precursors in preparing N-fused heterocycles via intramolecular acyl-transfer. To best of our knowledge, acyl-transfer of unstrained heteroaryl ketones remains to be demonstrated. Here, we show an acyl transfer-annulation to convert heteroaryl ketones to N-fused heterocycles. Driven via aromatisation, the acyl of a heteroaryl ketone can be transferred from the carbon to the nitrogen of the corresponding heterocycle. The reaction commences with the spiroannulation of a heteroaryl ketone and an alkyl bromide, with the resulting spirocyclic intermediate undergoing aromatisation-driven intramolecular acyl transfer. The reaction conditions are optimised, with the reaction exhibiting a broad substrate scope in terms of the ketone and alkyl bromide. The utility of this protocol is further demonstrated via application to complex natural products and drug derivatives to yield heavily functionalised N-fused heterocycles.

Coulometric back titration based on all-solid-state electrodes for phenylephrine hydrochloride determination.

Existing coulometric titration generally used liquid reference electrodes, with limitations of frequent maintenance and liquid leakage risk and requiring vertical working position. Herein, we proposed an all-solid coulometric titration based on the glassy carbon electrode (GCE) and preliminarily utilized it in phenylephrine hydrochloride (PHE) analysis with a universal back titration program. Subsequently, the long-term stability of the GCE in bromine and iodine solution was evaluated comprehensively by electrochemical characterization and titration measurement. The results presented an excellent linear relationship between electrolysis time and PHE concentration from 0.3 to 20 mM, with a limit of detection of 0.07 mM (3 S0/S). It also showed an excellent standard recovery rate and a short testing time within 10 min. Compared with bromometry in the pharmacopoeia, the all-solid coulometric titration exhibited higher accuracy and precision in formulation detection with simpler operation. The long-term stability experiments indicated that the potential difference mutation was unaffected by the electrochemical property of the GCE. Conclusively, this enabling work provided an all-solid coulometric titration for drug determination without maintenance in the long term and contributed to its further integration and industrialization.

Ultra-Broadband, Polarization-Irrelevant Near-Perfect Absorber Based on Composite Structure.

This paper proposes a near-perfect absorption device based on a cross-shaped titanium nanostructure and a multilayered structure. The multilayered bottom structure consists of alternately SiO2 and Ti. The whole device is put on a TiN substrate. The coupling between cross-shaped titanium nanostructures, and that between the cross-shaped titanium nanostructure and bottom multilayer, can further enhance the absorption at some wavelength where most of the energy is reflected or passes through in the device with a single structure. According to the simulation results, the device presents a nearly perfect absorption in a wavelength range from 300 nm to 2000 nm. The average absorptance in the wavelength range from 500 nm to 1400 nm exceeds 96%. This paper also provides a new idea for realizing perfect absorption, which is extensively used in sensing, controllable thermal emission, solar energy harvesting solar thermo-photovoltaic devices, and optoelectronic metrology.

Determination of tuberculosis-related volatile organic biomarker methyl nicotinate in vapor using fluorescent assay based on quantum dots and cobalt-containing porphyrin nanosheets.

Methyl nicotinate (MN) is a representative and typical volatile organic marker of Mycobacterium tuberculosis, and the specific detection of MN in human breath facilitates non-invasive, rapid, and accurate epidemic screening of tuberculosis infection. Herein, we constructed a fluorescent assay consisted of CdTe quantum dots (QD) and cobalt-metalized tetrakis(4-carboxyphenyl) porphyrin (CoTCPP) nanosheets to determine methyl nicotinate (MN) in vapor samples. Red-emission QD (λex=370 nm, λem=658 nm) acts as signal switches whose fluorescence signals can be effectively quenched by CoTCPP nanosheets but restored in the presence of MN. The strategy relied on the distinct binding affinity of cobalt ion and MN. MN restored the fluorescence of QD quenched by CoTCPP in a concentration-dependent manner, which exhibited a well-linear relationship in the range 1-100 µM, and a limit of detection of 0.59 µM. The proposed platform showed sensitivity and selectivity to detect MN in vapor samples with satisfactory RSD below 3.33%. The method is cheap, simple, and relatively rapid (detected within 4 min), which suggests a potential in tuberculosis diagnosis in resource- and professional-lacked areas.

FOXO4 Inhibits the Migration and Metastasis of Colorectal Cancer by Regulating the APC2/ß-Catenin Axis.

Objective: Adenomatous polyposis coli 2 (APC2) is a colorectal cancer (CRC) tumor-suppressor gene. The progression of several kinds of cancer is closely associated with Forkhead box O4 (FOXO4). However, the function of FOXO4 in CRC is unclear. This study focused on the role of FOXO4 and the relationship between FOXO4 and APC2 in CRC migration and metastasis. Methods: The expressions of FOXO4, APC2, and p(S37)-ß-catenin were detected in CRC tissues by immunohistochemistry, and their correlation was analyzed using the Spearman coefficient. Chromatin immunoprecipitation was used to test whether FOXO4 binds and regulates APC2 as a transcription factor. Either FOXO4 overexpression or APC2 knockdown was performed in CRC cell lines. The roles of FOXO4 and APC2 were investigated in CRC migration and metastasis. Results: FOXO4 was downregulated in CRC tissues compared with normal tissues and positively correlated with APC2 and p(S37)-ß-catenin. FOXO4 could combine the promoter region of APC2 to upregulate its expression and increase the phosphorylated degradation of ß-catenin. Stemness genes (CD133, ABCG1, and SOX2) were inhibited by FOXO4 overexpression in SW620 and HCT116 cell lines. Overexpressed FOXO4 suppressed epithelial-mesenchymal transition and the migration of CRC cell lines and metastasis of HCT116 in both the spleen and liver of nude mice, which was reversed by APC2 knockdown. Conclusion: This research demonstrates that overexpressed FOXO4 inhibits the migration and metastasis of CRC cells by enhancing the APC2/ß-catenin axis, suggesting that FOXO4 is a potential therapeutic target of CRC.

Machine learning enabled self-calibration single fiber endoscopic imaging.

Single fiber scanners (SFSs), with the advantages of compact size, versatility, large field of view, and high resolution, have been applied in many areas. However, image distortions persistently impair the imaging quality of the SFS, although many efforts have been made to address the problem. In this Letter, we propose a simple and complete solution by combining the piezoelectric (PZT) self-induction sensor and machine learning algorithms. The PZT tube was utilized as both the actuator and the fiber position sensor. Additionally, the feedback sensor signal was interrogated by a convolution neural network to eliminate the noise. The experimental results show that the predicted fiber trajectory error was below 0.1%. Moreover, this self-calibration SFS has an excellent robustness to temperature changes (20-50°C). It is believed that the proposed solution has removed the biggest barrier for the SFS and greatly improved its performance and stability in complex environments.