Abnormal EEG microstates in Alzheimer's disease: predictors of ß-amyloid deposition degree and disease classification.

Electroencephalography (EEG) microstates are used to study cognitive processes and brain disease-related changes. However, dysfunctional patterns of microstate dynamics in Alzheimer's disease (AD) remain uncertain. To investigate microstate changes in AD using EEG and assess their association with cognitive function and pathological changes in cerebrospinal fluid (CSF). We enrolled 56 patients with AD and 38 age- and sex-matched healthy controls (HC). All participants underwent various neuropsychological assessments and resting-state EEG recordings. Patients with AD also underwent CSF examinations to assess biomarkers related to the disease. Stepwise regression was used to analyze the relationship between changes in microstate patterns and CSF biomarkers. Receiver operating characteristics analysis was used to assess the potential of these microstate patterns as diagnostic predictors for AD. Compared with HC, patients with AD exhibited longer durations of microstates C and D, along with a decreased occurrence of microstate B. These microstate pattern changes were associated with Stroop Color Word Test and Activities of Daily Living scale scores (all P < 0.05). Mean duration, occurrences of microstate B, and mean occurrence were correlated with CSF Aß 1-42 levels, while duration of microstate C was correlated with CSF Aß 1-40 levels in AD (all P < 0.05). EEG microstates are used to predict AD classification with moderate accuracy. Changes in EEG microstate patterns in patients with AD correlate with cognition and disease severity, relate to Aß deposition, and may be useful predictors for disease classification.

DDLA: a double deep latent autoencoder for diabetic retinopathy diagnose based on continuous glucose sensors.

The current diagnosis of diabetic retinopathy is based on fundus images and clinical experience. However, considering the ineffectiveness and non-portability of medical devices, we aimed to develop a diagnostic model for diabetic retinopathy based on glucose series data from the wearable continuous glucose monitoring system. Therefore, this study developed a novel method, i.e., double deep latent autoencoder, for exploring glycemic variability influence from multi-day glucose data for diabetic retinopathy. Specifically, the model proposed in this research could encode continuous glucose sensor data with non-continuous and variable length via the integration of a data reorganization module and a novel encoding module with fragmented-missing-wise objective function. Additionally, the model implements a double deep autoencoder, which integrated convolutional neural network, long short-term memory, to jointly capturing the inter-day and intra-day glucose latent features from glucose series. The effectiveness of the proposed model is evaluated through a cross-validation method to clinical datasets of 765 type 2 diabetes patients. The proposed method achieves the highest accuracy value (0.89), precision value (0.88), and F1 score (0.73). The results suggest that our model can be used to remotely diagnose and screen for diabetic retinopathy by learning potential features of glucose series data collected by wearable continuous glucose monitoring systems.

Hydroformylation of Olefins with CO2/H2 and Hydrosilane by Copper/Cobalt Tandem Catalysis.

A Cu/Co tandem catalysis protocol was developed to conduct the hydroformylation of olefins using CO2/H2 and PMHS (polymethylhydrosiloxane) as a readily available and environmentally friendly hydride source. This methodology was performed via a two-step approach consisting of the copper-catalyzed reduction of CO2 by hydrosilane and subsequent cobalt-promoted hydroformylation with H2 and the in situ formed CO. The optimized triphos oxide ligand, which presumably facilitates the migratory insertion of CO gives moderate to excellent yields for both terminal and internal alkenes. This earth-abundant metal catalysis provides a reliable and efficient way to afford useful aldehydes in industry using silicon by-product PMHS as hydrogen source and renewable CO2 as carbonyl source.

Clinical application value of metagenome next-generation sequencing in pulmonary diffuse exudative lesions: a retrospective study.

Objective: This study aims to investigate the clinical application value of Metagenome Next-Generation Sequencing (mNGS) for pulmonary diffuse exudative lesions. Methods: From January 1, 2014, to November 31, 2021, 136 cases with chest radiologic presentations of pulmonary diffuse exudative lesions admitted to Fujian Provincial Hospital were included in the study; of those, 77 patients underwent mNGS pathogen detection. Based on the pathogen detection outcomes and clinical diagnoses, patients were categorized into an infection group (IG) and a non-infection group (NIG). A comparison was made between the diagnostic efficacy of the mNGS technique and traditional culture methods. Meanwhile, 59 patients clinically identified as having infectious pulmonary diffuse exudative lesions but who did not receive mNGS testing were designated as the non-NGS infection group (non-IG). A retrospective cohort study was conducted on patients in both the IG and non-IG, with a 30-day all-cause mortality endpoint used for follow-up. Outcomes: When compared to conventional culture methods, mNGS demonstrated an approximate 35% increase in sensitivity (80.0% vs 45.5%, P<0.001), without significant disparity in specificity (77.3% vs 95.5%, P=0.185). Under antibiotic exposure, the positivity rate detected by mNGS was notably higher than that by traditional culture methods, indicating that mNGS is less affected by exposure to antibiotics (P<0.05). Within 30 days, the all-cause mortality rate for patients in the IG versus the non-IG was 14.55% and 37.29%, respectively (P<0.05). Following a COX regression analysis to adjust for confounding factors, the analysis revealed that a CURB-65 score ≥3 points (HR=3.348, P=0.001) and existing cardiovascular disease (HR=2.473, P=0.026) were independent risk factors for these patients. Conversely, mNGS testing (HR=0.368, P=0.017) proved to be an independent protective factor. Conclusion: mNGS technology makes it easier to pinpoint the cause of pulmonary diffuse infectious exudative lesions without much interference from antibiotics, helping doctors spot and diagnose these issues early on, thereby playing a key role in helping them decide the best treatment approach for patients. Such conclusions may have a bias, as the performance of traditional methods might be underestimated due to the absence of complete results from other conventional diagnostic techniques like serological testing and PCR.

Electrochemical E-Selective Semireductive Dicarboxylation of Aryl Alkynes with CO2.

Herein, we report an electrochemical protocol for the dicarboxylation of aryl alkynes using CO2. With a graphite rod as the cathode and Al as the sacrificial anode, a series of valuable butenedioic acids are obtained in moderate to excellent yields with an E/Z ratio up to 50:1. This method features high E-selectivity, high step and atom economy, easy scalability, and a nice substrate scope, which renders it appealing for promising applications in organic synthesis and materials chemistry.

TRIM38 Induced in Respiratory Syncytial Virus-infected Cells Downregulates Type I Interferon Expression by Competing with TRIM25 to Bind RIG-I.

Innate immune response is the first line of defense for the host against virus invasion. One important response is the synthesis and secretion of type I interferon (IFN-I) in the virus-infected host cells. Here, we found that respiratory syncytial virus (RSV) infection induced high expression of TRIM25, which belongs to the tripartite motif-containing (TRIM) family of proteins. TRIM25 bound and activated retinoic acid-inducible gene I (RIG-I) by K63-linked ubiquitination. Accordingly, RIG-I mediated the production of IFN-I mainly through the nuclear factor kappa-B (NF-κB) pathway in respiratory epithelial cells. Interestingly, IFN-I, in turn, promoted a high expression of TRIM38 which downregulated the expression of IFN-I by reducing the protein level of RIG-I by K48-linked ubiquitination. More importantly, the binding site of TRIM25 to RIG-I was found in the narrow 25th-43rd amino acid (aa) region of RIG-I N-terminus. In contrast, the binding sites of TRIM38 to RIG-I were found in a much wider amino acid region, which included the binding site of TRIM25 on RIG-I. As a result, TRIM38 inhibits the production of IFN-I by competing with TRIM25 for RIG-I binding. Thus, TRIM38 negatively regulates RIG-I activation to, in turn, downregulate IFN-I expression, thus interfering with host immune response. A negative feedback loop effectively "puts the brakes" on the reaction once host immune response is overactivated and homeostasis is unbalanced. We also discovered that TRIM25 bound RIG-I by a new K63-linked ubiquitination located at K-45 of the first caspase recruitment domain (CARD). Collectively, these results confirm an antagonism between TRIM38 and TRIM25 in regulating IFN-I production by affecting RIG-I activity following RNA virus infection.

An integrated electrode material based on corn straw cellulose biochar with three-dimensional network porous structure for boosting electrochemical performance of lithium batteries.

In this work an integrated electrode material based on the VS4 nanoparticles grow on three-dimensional network porous biochar is put forward, forming a heterostructure that significantly boost the rate and cycle performance in lithium batteries. Biochar derives from two-steps treatment removing partial cellulose and hemicellulose, possessing three-dimensional network porous structure and naturally nitrogenous. The integrated electrode material constructs the continuous electrons transfer network, accommodates the volume expansion and traps the polar polysulfides efficiently. After 100 cycles at 1C, the integrated electrode with biochar shows the highest specific discharge capacity. Even at 2C, the three-dimensional electrode can display a high specific discharge capacity of 798.6 mAh·g-1. Thus, our study has pointed the innovations approach of constructing integrated electrode materials with porous structure biochar to enhance the electrochemical performance of lithium batteries.

A cross-trait study of lung cancer and its related respiratory diseases based on large-scale exome sequencing population.

Background: Genome-wide association studies (GWASs) explain the genetic susceptibility between diseases and common variants. Nevertheless, with the appearance of large-scale sequencing profiles, we could explore the rare coding variants in disease pathogenesis. Methods: We estimated the genetic correlation of nine respiratory diseases and lung cancer in the UK Biobank (UKB) by linkage disequilibrium score regression (LDSC). Then, we performed exome-wide association studies at single-variant level and gene-level for lung cancer and lung cancer-related respiratory diseases using the whole-exome sequencing (WES) data of 427,934 European participants. Cross-trait meta-analysis was conducted by association analysis based on subsets (ASSET) to identify the pleiotropic variants, while in-silico functional analysis was performed to explore their function. Causal mediation analysis was used to explore whether these pleiotropic variants lead to lung cancer is mediated by affecting the chronic respiratory diseases. Results: Five respiratory diseases [emphysema, pneumonia, asthma, chronic obstructive pulmonary disease (COPD), and fibrosis] were genetically correlated with lung cancer. We identified 102 significant independent variants at single-variant levels for lung cancer and five lung cancer-related diseases. 15:78590583:G>A (missense variant in CHRNA5) was shared in lung cancer, emphysema, and COPD. Meanwhile, 14 significant genes and 87 suggestive genes were identified in gene-based association tests, including HSD3B7 (lung cancer), SRSF2 (pneumonia), TNXB (asthma), TERT (fibrosis), MOSPD3 (emphysema). Based on the cross-trait meta-analysis, we detected 145 independent pleiotropic variants. We further identified abundant pathways with significant enrichment effects, demonstrating that these pleiotropic genes were functional. Meanwhile, the proportion of mediation effects of these variants ranged from 6 to 23 (emphysema: 23%; COPD: 20%; pneumonia: 20%; fibrosis: 7%; asthma: 6%) through these five respiratory diseases to the incidence of lung cancer. Conclusions: The identified shared genetic variants, genes, biological pathways, and potential intermediate causal pathways provide a basis for further exploration of the relationship between lung cancer and respiratory diseases.

Synthesis of Dimethyl Carbonate via Transesterification of Ethylene Carbonate and Methanol over Mesoporous KF-loaded Mg-Fe Oxides.

A series of KF/Mg-Fe oxides were fabricated via the solid-state reaction between KF and Mg-Fe oxides. Especially, when 20 wt % KF was supported on the Mg-Fe bi-metal oxides and calcined at 400-600 °C, the solid material with more basic sites than the support itself was obtained. When applied as catalyst to dimethyl carbonate (DMC) synthesis through transesterification of ethylene carbonate (EC) and methanol, this material can afforded up to 88 % yield and 97 % selectivity toward DMC in 2 h under reflux conditions with the molar ratio of methanol to ethylene carbonate set at 8. It is worth noting that the catalyst was easily separated and reused, retaining at least 89 % catalytic activity during the first four recycles. Although an attenuated activity was still observed due to the inevitable filtration loss and dissolution, this solid base can still provide clues to the development recyclable catalyst in green synthesis of DMC.

Mononuclear Iron Pyridinethiolate Complex Promoted CO2 Photoreduction via Rapid Intramolecular Electron Transfer.

Designing earth-abundant metal complexes as efficient molecular photocatalysts for visible light-driven CO2 reduction is a key challenge in artificial photosynthesis. Here, we demonstrated the first example of a mononuclear iron pyridine-thiolate complex that functions both as a photosensitizer and catalyst for CO2 reduction. This single-component bifunctional molecular photocatalyst efficiently reduced CO2 to formate and CO with a total turnover number (TON) of 46 and turnover frequency (TOF) of 11.5 h-1 in 4 h under visible light irradiation. Notably, the quantum yield was determined to be 8.4 % for the generation of formate and CO at 400 nm. Quenching experiments indicate that high photocatalytic activity is mainly attributed to the rapid intramolecular quenching protocol. The mechanism investigation by DFT calculation and electrochemical studies revealed that the protonation of Febpy(pyS)2 is indispensable step for photocatalytic CO2 reduction.

Clinically relevant stratification of patients with type 2 diabetes by using continuous glucose monitoring data.

AIM: The wealth of data generated by continuous glucose monitoring (CGM) provides new opportunities for revealing heterogeneities in patients with type 2 diabetes mellitus (T2DM). We aimed to develop a method using CGM data to discover T2DM subtypes and investigate their relationship with clinical phenotypes and microvascular complications. METHODS: The data from 3119 patients with T2DM who wore blinded CGM at an academic medical centre was collected, and a glucose symbolic pattern (GSP) metric was created that combined knowledge-based temporal abstraction with numerical vectorization. The k-means clustering was applied to GSP to obtain subgroups of patients with T2DM. Clinical characteristics and the presence of diabetic retinopathy and albuminuria were compared among the subgroups. The findings were validated in an independent population comprising 773 patients with T2DM. RESULTS: By using GSP, four subgroups were identified with distinct features in CGM profiles and parameters. Moreover, the clustered subgroups differed significantly in clinical phenotypes, including indices of pancreatic ß-cell function and insulin resistance (all p < .001). After adjusting for confounders, group C (the most insulin resistant) had a significantly higher risk of albuminuria (odds ratio = 1.24, 95% confidence interval: 1.03-1.39) relative to group D, which had the best glucose control. These findings were confirmed in the validation set. CONCLUSION: Subtyping patients with T2DM using CGM data may help identify high-risk patients for microvascular complications and provide insights into the underlying pathophysiology. This method may help refine clinically meaningful stratification of patients with T2DM and inform personalized diabetes care.

Proteome-wide Mendelian randomization identifies causal plasma proteins in lung cancer.

Plasma proteins are promising biomarkers and potential drug targets in lung cancer. To evaluate the causal association between plasma proteins and lung cancer, we performed proteome-wide Mendelian randomization meta-analysis (PW-MR-meta) based on lung cancer genome-wide association studies (GWASs), protein quantitative trait loci (pQTLs) of 4,719 plasma proteins in deCODE and 4,775 in Fenland. Further, causal-protein risk score (CPRS) was developed based on causal proteins and validated in the UK Biobank. 270 plasma proteins were identified using PW-MR meta-analysis, including 39 robust causal proteins (both FDR-q < 0.05) and 78 moderate causal proteins (FDR-q < 0.05 in one and p < 0.05 in another). The CPRS had satisfactory performance in risk stratification for lung cancer (top 10% CPRS:Hazard ratio (HR) (95%CI):4.33(2.65-7.06)). The CPRS [AUC (95%CI): 65.93 (62.91-68.78)] outperformed the traditional polygenic risk score (PRS) [AUC (95%CI): 55.71(52.67-58.59)]. Our findings offer further insight into the genetic architecture of plasma proteins for lung cancer susceptibility.

Study on unconfined compressive strength and deformation characteristics of chlorine saline soil.

The distribution of saline soil is wide and the area is large in China. The saline soil in different regions shows their own characteristics. The saline soil of single salt is configured by adding different contents of NaCl to the loess in Xi'an. The effects of chlorine content and water content on soil strength and volume change in a large water content range was studied, and the change mechanism was analyzed by scanning electron microscopy. The results show that the strength of chloride saline soil increases with the decrease of water content. The moisture content of 12% is the critical point of strength change of chloride saline soil. When the moisture content is greater than 12%, the strength of soil decreases with the increase of salt content. When the water content is less than 12%, the strength of saline soil is 3% NaCl content > 1% NaCl content > 5% NaCl content > 0% NaCl content. The volume change of the sample consists of three parts: elastic deformation during sample pressing, volume shrinkage during water loss and salt expansion. In the absence of NaCl and 1% NaCl content, the sample was in the state of shrinkage during the loading process, in which with the decrease of moisture content shrinkage rate slowed down. The volume change rate of 3% and 5% NaCl showed an inflection point from negative to positive when the water content was 15%. When the water content is less than 12%, the saline soil with 3% NaCl content has the characteristics of high strength and unobvious salt expansion. The method of adding 3% NaCl to loess in Xi 'an area can be used to simulate the cement between soil particles, which provides a reference for artificially preparing structural soil. According to the microstructure analysis, the higher the salt content of saline soil, the smaller the soil pores, and the contact form of soil particles gradually develops from the point contact between soil particles to the salt-wrapped structure.

RPTOR blockade suppresses brain metastases of NSCLC by interfering the ceramide metabolism via hijacking YY1 binding.

BACKGROUND: Ceramide metabolism is crucial in the progress of brain metastasis (BM). However, it remains unexplored whether targeting ceramide metabolism may arrest BM. METHODS: RNA sequencing was applied to screen different genes in primary and metastatic foci and whole-exome sequencing (WES) to seek crucial abnormal pathway in BM + and BM-patients. Cellular arrays were applied to analyze the permeability of blood-brain barrier (BBB) and the activation or inhibition of pathway. Database and Co-Immunoprecipitation (Co-IP) assay were adopted to verify the protein-protein interaction. Xenograft and zebrafish model were further employed to verify the cellular results. RESULTS: RNA sequencing and WES reported the involvement of RPTOR and ceramide metabolism in BM progress. RPTOR was significantly upregulated in BM foci and increased the permeability of BBB, while RPTOR deficiency attenuated the cell invasiveness and protected extracellular matrix. Exogenous RPTOR boosted the SPHK2/S1P/STAT3 cascades by binding YY1, in which YY1 bound to the regions of SPHK2 promoter (at -353 ~ -365 nt), further promoting the expression of SPHK2. The latter was rescued by YY1 RNAi. Xenograft and zebrafish model showed that RPTOR blockade suppressed BM of non-small cell lung cancer (NSCLC) and impaired the SPHK2/S1P/STAT3 pathway. CONCLUSION: RPTOR is a key driver gene in the brain metastasis of lung cancer, which signifies that RPTOR blockade may serve as a promising therapeutic candidate for clinical application.

Systematic characterization of m6A proteomics across 12 cancer types: a multi-omics integration study.

The modification patterns of N6-methyladenosine (m6A) regulators and interacting genes are deeply involved in tumors. However, the effect of m6A modification patterns on human proteomics remains largely unknown. We evaluated the molecular characteristics and clinical relevance of m6A modification proteomics patterns among 1013 pan-cancer samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). More than half of the m6A proteins were expressed at higher levels in tumor tissues and presented oncogenic characteristics. Furthermore, we performed multi-omics analyses integrating with transcriptomics data of m6A regulators and interactive coding and non-coding RNAs and developed a m6A multi-omics signature to identify potential m6A modification target proteins across global proteomics. It was significantly associated with overall survival in nine cancer types, tumor mutation burden (P = 0.01), and immune checkpoints including PD-L1 (P = 4.9 × 10-8) and PD-1 (P < 0.01). We identified 51 novel proteins associated with the multi-omics signature (PFDR < 0.05). These proteins were functional through pathway enrichment analyses. The protein with the highest hit frequency was CHORDC1, which was significantly up-regulated in tumor tissues in nine cancer types. Its higher abundance was significantly associated with a poorer prognosis in seven cancer types. The identified m6A target proteins might provide infomation for the study of molecular mechanism of cancer.

Study of efficient catalytic electrode for hydrogen evolution reaction from seawater based on low tortuosity corn straw cellulose biochar/Mo2C with porous channels.

Porosity and channel structure has important effects on the performance of hydrogen evolution reaction (HER) of nanostructured electrocatalysts in acid solution and seawater. Mesopore usually helps to enhance the reaction kinetics and mass transfer, while the macroporous channel structure also affects the electrocatalyst. Traditional graphene materials do not have such structure. Therefore, this paper designs a method to synthesize Mo2C composite nanomaterial in situ on corn straw biochar, inspires by the natural channel structure of conducting water, salt and organic matter in plants. Characteristic characterization shows that the material also has a large number of mesoporous and vertical distribution of large porous channel structure, through the decrease of tortuosity and porosity, ensure the catalyst surface electrolyte transport and hydrogen timely escape, alleviate the process of metal ion precipitation blocking pore channel, so as to improve the rate of hydrogen evolution reaction. The results shows that the overpotential of the catalyst was 48 mV and 251 mV under 10 mA cm-2 acidic electrolyte and simulated seawater electrolyte, respectively. This method provides new ideas for the design of efficient electrocatalysts for seawater decomposition, then the HER performance in alkaline and neutral environments needs to be further explored.

Successful treatment of severe lung cancer caused by third-generation EGFR-TKI resistance due to EGFR genotype conversion with afatinib plus anlotinib.

Third-generation EGFR-TKIs can be used to treat advanced non-small cell lung cancer patients with T790M resistance mutation induced by first- or second-generation EGFR-TKIs. However, it will also result in drug resistance, and the resistance mechanisms of third-generation EGFR-TKIs are complex. Here we reported a patient diagnosed with advanced lung adenocarcinoma and EGFR positive in September 2016. Following first-line targeted therapy with gefitinib, genetic testing showed EGFR T790M positive, which resulted in a change to osimertinib targeted therapy. In May 2021, troponin and creatinine levels were elevated, and the tumor hyperprogressed to severe lung cancer. Repeated genetic testing revealed that EGFR genotype converted to a non-classical mutation and EGFR T790M turned negative, which caused third-generation EGFR-TKI resistance. As a result, afatinib combined with anlotinib was selected to stabilize the patient's condition. We were inspired by the case that it reflects the significance and necessity of exploring the resistance mechanism and dynamically detecting genetic status throughout the course of treatment, which may help realize individualized precision therapy, and maximize the potential of patient.

Enhanced ultraviolet-B radiation alleviates structural damages on rice leaf caused by Magnaporthe oryzae infection.

Enhanced ultraviolet-B (UV-B) radiation can change the interaction between crops and pathogens. The effects of single and compound stresses of enhanced UV-B radiation (5.0 kJ·m-2) and Magnaporthe oryzae on the morphology, anatomy, and ultrastructure of rice leaves were investigated. M. oryzae infection decreased the leaf area and thickness, reduced the stomatal area and density, and caused damages to the leaf ultrastructure, such as cytoplasm-cell wall separation, atrophy and sinking of fan-shaped bulliform cells, and chloroplast deformation. The enhanced UV-B radiation supplied before or during M. oryzae infection remarkably decreased the mycelia number of M. oryzae in leaf epidermis, increased the leaf area, leaf thickness, stomatal density, and mastoid number; and alleviated the ultrastructural damages induced by M. oryzae to keep an integral chloroplast. While the UV-B radiation was supplied after M. oryzae infection, its alleviation effects on the damages induced by M. oryzae infection on the morphology and structure of rice leaf were attenuated. Thus, the alleviation of enhanced UV-B radiation on damages induced by M. oryzae infection on rice leaves was related to its application period. The enhanced UV-B radiation supplied before or during M. oryzae infection allowed the rice leaf to resist M. oryzae infection.

A novel hypoglycemia alarm framework for type 2 diabetes with high glycemic variability.

In patients with type 2 diabetes (T2D), accurate prediction of hypoglycemic events is crucial for maintaining glycemic control and reducing their frequency. However, individuals with high blood glucose variability experience significant fluctuations over time, posing a challenge for early warning models that rely on static features. This article proposes a novel hypoglycemia early alarm framework based on dynamic feature selection. The framework incorporates domain knowledge and introduces multi-scale blood glucose features, including predicted values, essential for early warnings. To address the complexity of the feature matrix, a dynamic feature selection mechanism (Relief-SVM-RFE) is designed to effectively eliminate redundancy. Furthermore, the framework employs online updates for the random forest model, enhancing the learning of more relevant features. The effectiveness of the framework was evaluated using a clinical dataset. For T2D patients with a high coefficient of variation (CV), the framework achieved a sensitivity of 81.15% and specificity of 98.14%, accurately predicting most hypoglycemic events. Notably, the proposed method outperformed other existing approaches. These results indicate the feasibility of anticipating hypoglycemic events in T2D patients with high CV using this innovative framework.