Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we propose an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.

VThunter: a database for single-cell screening of virus target cells in the animal kingdom.

Viral infectious diseases are a devastating and continuing threat to human and animal health. Receptor binding is the key step for viral entry into host cells. Therefore, recognizing viral receptors is fundamental for understanding the potential tissue tropism or host range of these pathogens. The rapid advancement of single-cell RNA sequencing (scRNA-seq) technology has paved the way for studying the expression of viral receptors in different tissues of animal species at single-cell resolution, resulting in huge scRNA-seq datasets. However, effectively integrating or sharing these datasets among the research community is challenging, especially for laboratory scientists. In this study, we manually curated up-to-date datasets generated in animal scRNA-seq studies, analyzed them using a unified processing pipeline, and comprehensively annotated 107 viral receptors in 142 viruses and obtained accurate expression signatures in 2 100 962 cells from 47 animal species. Thus, the VThunter database provides a user-friendly interface for the research community to explore the expression signatures of viral receptors. VThunter offers an informative and convenient resource for scientists to better understand the interactions between viral receptors and animal viruses and to assess viral pathogenesis and transmission in species. Database URL: https://db.cngb.org/VThunter/.

Identification of a Branch Number Locus in Soybean Using BSA-Seq and GWAS Approaches.

The determination of the soybean branch number plays a pivotal role in plant morphogenesis and yield components. This polygenic trait is subject to environmental influences, and despite its significance, the genetic mechanisms governing the soybean branching number remain incompletely understood. To unravel these mechanisms, we conducted a comprehensive investigation employing a genome-wide association study (GWAS) and bulked sample analysis (BSA). The GWAS revealed 18 SNPs associated with the soybean branch number, among which qGBN3 on chromosome 2 emerged as a consistently detected locus across two years, utilizing different models. In parallel, a BSA was executed using an F2 population derived from contrasting cultivars, Wandou35 (low branching number) and Ruidou1 (high branching number). The BSA results pinpointed a significant quantitative trait locus (QTL), designated as qBBN1, located on chromosome 2 by four distinct methods. Importantly, both the GWAS and BSA methods concurred in co-locating qGBN3 and qBBN1. In the co-located region, 15 candidate genes were identified. Through gene annotation and RT-qPCR analysis, we predicted that Glyma.02G125200 and Glyma.02G125600 are candidate genes regulating the soybean branch number. These findings significantly enhance our comprehension of the genetic intricacies regulating the branch number in soybeans, offering promising candidate genes and materials for subsequent investigations aimed at augmenting the soybean yield. This research represents a crucial step toward unlocking the full potential of soybean cultivation through targeted genetic interventions.

CRISPR/CasΦ2-mediated gene editing in wheat and rye.

The compact CRISPR/CasΦ2 system provides a complementary genome engineering tool for efficient gene editing including cytosine and adenosine base editing in wheat and rye with high specificity, efficient use of the protospacer-adjacent motif TTN, and an alternative base-editing window.

Achieving a Deeper Understanding of Drug Metabolism and Responses Using Single-Cell Technologies.

Recent advancements in single-cell technologies have enabled detection of RNA, proteins, metabolites, and xenobiotics in individual cells, and the application of these technologies has the potential to transform pharmacological research. Single-cell data has already resulted in the development of human and model species cell atlases, identifying different cell types within a tissue, further facilitating the characterization of tumor heterogeneity, and providing insight into treatment resistance. Research discussed in this review demonstrates that distinct cell populations express drug metabolizing enzymes to different extents, indicating there may be variability in drug metabolism not only between organs, but within tissue types. Additionally, we put forth the concept that single-cell analyses can be used to expose underlying variability in cellular response to drugs, providing a unique examination of drug efficacy, toxicity, and metabolism. We will outline several of these techniques: single-cell RNA-sequencing and mass cytometry to characterize and distinguish different cell types, single-cell proteomics to quantify drug metabolizing enzymes and characterize cellular responses to drug, capillary electrophoresis-ultrasensitive laser-induced fluorescence detection and single-probe single-cell mass spectrometry for detection of drugs, and others. Emerging single-cell technologies such as these can comprehensively characterize heterogeneity in both cell-type-specific drug metabolism and response to treatment, enhancing progress toward personalized and precision medicine. SIGNIFICANCE STATEMENT: Recent technological advances have enabled the analysis of gene expression and protein levels in single cells. These types of analyses are important to investigating mechanisms that cannot be elucidated on a bulk level, primarily due to the variability of cell populations within biological systems. Here, we summarize cell-type-specific drug metabolism and how pharmacologists can utilize single-cell approaches to obtain a comprehensive understanding of drug metabolism and cellular heterogeneity in response to drugs.

Prognostic factors of sepsis in children with acute leukemia admitted to the pediatric intensive care unit.

OBJECTIVE: To analyze the prognostic factors of sepsis in children with acute leukemia admitted to the pediatric intensive care unit (PICU) and to compare the efficacy of different scoring systems for predicting the outcome of children. METHODS: Patients with an acute leukemia diagnosis admitted to a tertiary care university hospital PICU due to sepsis during chemotherapy between May 2015 and August 2022 were retrospectively analyzed through an electronic medical record system. RESULTS: During this period, 693 children with acute leukemia initially diagnosed were admitted to the center, and 155 (22.3%) of them were transferred to PICU due to deterioration of the disease during treatment. Total 109 (70.3%) patients were transferred to PICU due to sepsis. Here, 17 patients was excluded (prior treatment from another hospital; referring from other hospitals; discontinued treatment; incomplete medical record). Of the 92 patients studied, the mortality rate was 35.9%. Multivariate analysis revealed that remission status, lactate level, invasive mechanical ventilation (IMV), and inotropic support within 48 hours after PICU transfer were independent risk factors for PICU mortality. The pediatric sequential organ failure assessment (PSOFA) score had the greatest predictive validity for hospital mortality (area under the receiver operating characteristic curve [AUROC]: 0.83, 95% confidence intervals [CI]: 0.74-0.92), followed by the pediatric early warning score (PEWS) (0.82, 0.73-0.91) and pediatric critical illness score (PCIS) (0.79, 0.69-0.88). CONCLUSION: The mortality rate among children with acute leukemia complicated with sepsis is high after being transferred to the PICU. Various scoring systems can be used to monitor the clinical status of patients, identify sepsis early, detect critical illness, and determine the optimal time for transfer to the PICU for supportive treatment, thereby improving the prognosis of these patients.

Effect of Hydrophobic Chain Length in Amphiphilic Chitosan Conjugates on Intracellular Drug Delivery and Smart Drug Release of Redox-Responsive Micelle.

Three redox-sensitive nanocarriers were rationally designed based on amphiphilic low molecular weight chitosan-cystamine-octylamine/dodecylamin/cetylamine (LC-Cys-OA, LC-Cys-DA, LC-Cys-CA) conjugates containing disulfide linkage for maximizing therapeutic effect by regulating hydrophobic interaction. The resultant spherical micelles had the characteristics of low CMC, suitable size, excellent biosafety and desired stability. The drug-loaded micelles were fabricated by embedding doxorubicin (Dox) into the hydrophobic cores. The effect of hydrophobic chain lengths of amphiphilic conjugates on encapsulation capacity, redox sensitivity, trigger-release behavior, cellular uptake efficacy, antitumor effect and antimigratory activity of Dox-loaded micelles was systematically investigated. Studies found that Dox-loaded LC-Cys-CA micelle had superior loading capacity and enhanced redox sensitivity compared with the other two micelles. Release assay indicated that the three Dox-loaded micelles maintained sufficiently stability in normal blood circulation but rapidly disintegrated in tumor cells. More importantly, the LC-Cys-CA micelle with a longer hydrophobic chain length exhibited a higher accumulative Dox release percentage than the other two micelles. Additionally, an increase in hydrophobic chain lengths of amphiphilic conjugates improved cellular uptake efficiency, antitumor effect and antimigration activity of Dox-loaded micelles, which could be explained by enhanced loading ability and redox sensitivity. Our research was expected to provide a viable platform for achieving a desired therapeutic efficacy via the alteration of hydrophobic interaction.

Ru and Se Co-Doped Cobalt Hydroxide Electrocatalyst for Efficient Hydrogen Evolution Reactions.

The development of efficient electrocatalysts for hydrogen evolution reactions is an extremely important area for the development of green and clean energy. In this work, a precursor material was successfully prepared via electrodeposition of two doping elements to construct a co-doped cobalt hydroxide electrocatalyst (Ru-Co(OH)2-Se). This approach was demonstrated to be an effective way to improve the performance of the hydrogen evolution reaction (HER). The experimental results show that the material exhibited a smaller impedance value and a larger electrochemically active surface area. In the HER process, the overpotential was only 109 mV at a current density of 10 mA/cm2. In addition, the doping of selenium and ruthenium effectively prevented the corrosion of the catalysts, with the (Ru-Co(OH)2-Se) material showing no significant reduction in the catalytic performance after 50 h. This synergistic approach through elemental co-doping demonstrated good results in the HER process.

Synthesis of Multifluoromethylated γ-Sultines by a Photoinduced Radical Addition-Polar Cyclization.

Despite the significance of sultines in synthesis, medicine, and materials science, the chemistry of sultines has remained unexplored due to their inaccessibility. Herein, we demonstrate the development of a photoredox-catalyzed multifluoromethyl radical addition/SO2 incorporation/polar cyclization cascade approach to multifluoromethylated γ-sultines. The reactions proceed by single electron transfer induced multifluoromethyl radical addition to an alkene followed by SO2 incorporation, and single-electron reduction for polar 5-exo-tet cyclization. Key to the success of the protocol is the use of easily oxidizable multifluoroalkanesulfinates as bifunctional reagents. The reactions proceed with excellent functional-group tolerance to deliver γ-sultines in moderate to excellent yields.

Analysis of Ozonation Processes Using Coupled Modeling of Fluid Dynamics, Mass Transfer, and Chemical Reaction Kinetics.

The efficacy of oxidation of recalcitrant organic contaminants in municipal and industrial wastewaters by ozonation is influenced by chemical reaction kinetics and hydrodynamics within a reactor. A 3D computational fluid dynamics (CFD) model incorporating both multiphase flow and reaction kinetics describing ozone decay, hydroxyl radical (•OH) generation, and organic oxidation was developed to simulate the performance of continuous flow ozonation reactors. Formate was selected as the target organic in this study due to its well-understood oxidation pathway. Simulation results revealed that the dissolved ozone concentration in the reactor is controlled by rates of O3(g) interphase transfer and ozone self-decay. Simulations of the effect of various operating conditions showed that the reaction stoichiometric constraints between formate and ozone were reached; however, complete utilization of gas phase ozone was hard to achieve due to the low ozone interphase mass transfer rate. Increasing the O3(g) concentration leads to an increase in the formate removal rate by ∼5% due to an enhancement in the rate of O3(g) interphase mass transfer. The CFD model adequately describes the mass transfer occurring in the two-phase flow system and confirms that O3(g) interphase mass transfer is the rate-limiting step in contaminant degradation. The model can be used to optimize the ozone reactor design for improved contaminant degradation and ozonation efficiency.

Kinetic Modeling-Assisted Mechanistic Understanding of the Catalytic Ozonation Process Using Cu-Al Layered Double Hydroxides and Copper Oxide Catalysts.

In this study, copper aluminum layered hydroxides (Cu-Al LDHs) and copper oxide (CuO) were utilized as catalysts for heterogeneous catalytic ozonation (HCO). Target compounds oxalate and formate were used with removal by adsorption and oxidation quantified to elucidate the role of the catalyst in contaminant removal. Oxidation of oxalate mostly occurred on the catalyst surface via interaction of surface oxalate complexes with surface-located oxidants. In contrast, the oxidation of formate occurred in the bulk solution as well as on the surface of the catalyst. Measurement of O3 decay kinetics coupled with fluorescence microscopy image analysis corresponding to 7-hydroxycoumarin formation indicates that while surface hydroxyl groups in Cu-Al LDHs facilitate slow decay of O3 resulting in the formation of hydroxyl radicals on the surface, CuO rapidly transforms O3 into surface-located hydroxyl radicals and/or other oxidants. Futile consumption of surface-located oxidants via interaction with the catalyst surface was minimal for Cu-Al-LDHs; however, it becomes significant in the presence of higher CuO dosages. A mechanistic kinetic model has been developed which adequately describes the experimental results obtained and can be used to optimize the process conditions for the application of HCO.

Comparative Effectiveness of Varenicline and Nicotine Replacement Therapy for Smoking Cessation in Older and Younger Smokers: A Prospective Cohort in Taiwan.

Introduction: The effectiveness of varenicline compared with nicotine replacement therapy (NRT) in achieving smoking cessation in older smokers has not been investigated. This study prospectively compared the effectiveness of varenicline relative to NRT in smokers aged 25-54 years and separately in smokers aged 55 years or older. Methods: Among 13 397 smokers participating in the Smoking Cessation Program in Taiwan, 2012-2015, 6336 (19.2%, aged ≥55) received varenicline and 7061 received NRT patch or gum (23.2%, aged ≥55). Participants self-reported smoking behaviors by phone interview after 6 months. Logistic regression models estimated odds ratios (ORs) and 95% confidence intervals (CIs) for 7-day, 1-month, and 6-month point-prevalence abstinence. Age-specific models adjusted for sex, education, marital status, smoke-years, nicotine dependence, medical institution, clinic visit number, and duration of medication received. Results: Among smokers aged 25-54 years, varenicline users had a greater point-prevalence abstinence than NRT users (e.g., 7-day point-prevalence: 34.0% vs. 23.5%), with adjusted OR ranging from 1.23 (CI: 1.09-1.39; 6-month point-prevalence) to 1.37 (CI: 1.24-1.50; 1-month point-prevalence). Among smokers aged 55 years or older, point-prevalence was similar for varenicline and NRT users (e.g., 7-day point-prevalence: 32.3% vs. 33.1%), and ORs did not suggest that varenicline has greater effectiveness than NRT. Sex and level of nicotine dependence did not modify the age-specific effectiveness of varenicline relative to NRT. Conclusions: Varenicline did not offer greater effectiveness in achieving abstinence than NRT for smokers 55 years or older, whereas it was more effective than NRT in smokers aged 25-54 years. These findings highlighted the need for age-specific approaches for effective tobacco control. Implications: In this prospective investigation of a national cohort, older smokers (aged ≥55 years) who received varenicline did not have a greater point-prevalence abstinence after 6 months compared with those who used NRT patch or gum. Younger smokers (aged 25-54 years) who received varenicline had a greater likelihood of abstinence than NRT users. Sex and nicotine dependence did not modify the age-specific effectiveness of varenicline relative to NRT patch or gum. Age-appropriate approaches for effective tobacco control are needed.

Effects of six types of aspirin combination medications for treatment of acute cerebral infarction in China: A network meta-analysis.

WHAT IS KNOWN AND OBJECTIVE: Previous studies have shown that various aspirin combinations might be beneficial for the treatment of acute cerebral infarction (ACI). The aim of this study was to evaluate the efficacy of six aspirin combinations in the treatment of ACI using network meta-analysis (NMA). The performance of these combinations is then ranked according to results of this analysis. METHODS: Multiple databases were consulted to find randomized controlled trials (RCT) of six different aspirin combinations for the treatment of ACI. NMA was conducted on the data using stata (13.0) software. The odds ratio (OR) was calculated. The studies included in this paper were divided into a control group (aspirin alone) and an observation group (one of six aspirin combinations). RESULTS: A total of 103 eligible RCTs were identified. A total of 13 317 cases were included in the study, and the results showed that the six types of aspirin combinations (aspirin with atorvastatin, ozagrel sodium, low molecular weight heparin [LMWH], clopidogrel, cilostazol and ginkgo damo) were all significantly superior (P < 0.05) to aspirin alone. The combination of aspirin with LMWH had the highest probability of being the most clinically efficacious intervention, with a surface under the cumulative ranking (SUCRA) curve of 79.1. The combination of aspirin with ozagrel sodium was the worst, with a SUCRA value of 29.7. WHAT IS NEW AND CONCLUSION: A combination of aspirin with LMWH is the best option among the six aspirin combinations considered for the treatment of ACI. The combination of aspirin with ozagrel sodium was ranked the last.

A drug-delivering-drug strategy for combined treatment of metastatic breast cancer.

Treatment of metastatic cancer continues to be a huge challenge worldwide. Notably, drug nanocrystals (Ns) in nanosuspensions clearly belong to a type of nanoparticle. Therefore, a question arose as to whether these drug particles can also be applied as carriers for drug delivery. Here, we design a novel paclitaxel (PTX) nanocrystal stabilized with complexes of matrix metalloproteinase (MMP)-sensitive ß-casein/marimastat (MATT) for co-delivering MATT and PTX and combined therapy of metastatic breast cancer. The prepared Ns (200 nm) with a drug-loading of >50% were potent in treatment of metastatic cancer, which markedly inhibited MMP expression and activity and greatly blocked the lung metastasis and angiogenesis. In conclusion, employing protein-drug complexes as stabilizers, Ns with dual payloads are developed and are a promising strategy for co-delivery. Furthermore, the developed Ns can target the tumor microenvironment and cancer cells and, as a result, enable efficient treatment for breast metastatic cancer.

Optimization of QuEChERS cleanup for quantification of γ-oryzanol in vegetable oils by UHPLC-MS/MS.

This study was based on QuEChERS cleanup coupled with UHPLC-MS/MS for the determination of γ-oryzanol compounds in vegetable oils. Several parameters of QuEChERS and UHPLC-MS/MS were studied for purification and detection of γ-oryzanol compounds in oil samples. Under the optimized conditions, the whole pretreatment procedure could be accomplished within 10 min without tedious procedure, larger volume of organic solvent and complicated apparatus. The limit of detections and the limit of quantifications for γ-oryzanol compounds were ranging from 0.1-0.3 µg kg-1 and 0.4-1.0 µg kg-1, respectively. Satisfactory recoveries of all analyts were ranging from 72.2 % to 101.3 %, and the intra-day and inter-day precision were less than 10.6 %. The validation indicated that rice band oil and corn oil were rich in 24-mCAF, CAF, ß-SIF, CMF and STF. The QuEChERS-UHPLC-MS/MS simultaneously quantified five γ-oryzanol compounds in lipid matrices and assessed the nutritional and functional substances of vegetable oils.

Performance evaluation and optimization of a suspension-type reactor for use in heterogeneous catalytic ozonation.

Packed fixed-bed reactors are traditionally used for heterogeneous catalytic ozonation. However, a high solid-to-liquid requirement, poor ozone dissolution, ineffective utilization of catalyst surface area, and production of large amounts of catalyst waste impede application of such reactors. In this study, we designed a suspension catalytic ozonation reactor and compared the performance of this reactor with that of a traditional fixed-bed catalytic ozonation reactor employing oxalic acid (OA) as the target contaminant. Our results showed that total O3 dissolved into the suspension reactor (117-134 mg.L-1) was much higher compared to that measured in the fixed-bed reactor (53 mg.L-1) due to a higher O3(g) interphase mass transfer rate in the suspension reactor. In accordance with the higher O3(g) interphase mass transfer, we observed a much higher proportional OA removal (32 %) compared to that achieved in the fixed-bed reactor (10%) employing an Fe-oxide catalyst supported on Al2O3 (Fe-oxide@Al2O3) in both reactors. Use of a double-layered Cu-Al hydroxide (Cu-Al LDHs) catalyst in the suspension reactor further enhanced the performance with nearly 90 % OA removal observed. Given the superior performance of the suspension reactor, we investigated the impact of operating conditions (catalyst dosage, hydraulic retention time and ozone dosage) employing Cu-Al LDHs as the catalyst. We also developed a mathematical kinetic model to describe the performance of the suspension reactor and, through use of the kinetic model, showed that O3(g) interphase transfer rate was the rate-limiting step in OA removal. Thus, improvement in ozone gas diffuser design is required to improve the performance of the suspension reactor. Overall, the present study demonstrated that suspension reactors were more effective than fixed-bed reactors for oxidation of surface-active organic compounds such as OA due to the higher ozone interphase mass transfer rate and effective utilization of the catalyst surface area that can be achieved. As such, further research on suspension reactor design and development of catalysts suitable for use in suspension reactors should facilitate large-scale application of catalytic ozonation processes by the wastewater treatment industry.

Low molecular weight chitosan based GSH-responsive self-assembled cationic micelle with enhanced anti-tumor effect by combining oxidative damage and chemotherapy.

A novel cationic lipoic acid grafted low molecular weight chitosan (LCNE-LA) conjugate was constructed and further self-assembled into GSH-responsive cationic nanocarrier to achieve better antitumor effect by combining encapsulated chemotherapy and oxidative damage induced by ROS. The resultant LCNE-LA cationic micelle exhibited favorable physicochemical properties (low CMC, small size, positively zeta potential and good stability), excellent biosafety and desired redox sensitivity. Next, doxorubicin (Dox) was embedded into hydrophobic core to form stable Dox/LCNE-LA micelle that had superior loading capacity. The GSH-induced release behavior, cellular uptake ability, ROS generation and GSH consumption capacity and in vitro antitumor activity of Dox/LCNE-LA micelle were systematically evaluated. Consequently, Dox/LCNE-LA cationic micelle with positively charged could efficiently enter into cancer cell and redox-sensitive release Dox via disulfide-thiol exchange reaction, which usually expend abundant GSH and disrupt redox homeostasis. Studies further confirmed that Dox/LCNE-LA micelle could increase ROS and reduced GSH content which might cause oxidative damage to tumor cell. Antitumor activity indicated that Dox/LCNE-LA micelle achieved an excellent cancer-killing effect, which might be attributed to combination treatment of Dox and ROS induce oxidative damage. Overall, this research was expected to provide a platform for antitumor treatment by triggering Dox release and promoting ROS generation.

Effects of DPP4 Inhibitors as Neuroprotective Drug on Cognitive Impairment in Patients with Type 2 Diabetes Mellitus: A Meta-Analysis and Systematic Review.

Purpose: Type 2 diabetes mellitus is considered as one of the risk factors for cognitive impairment. DPP4 inhibitors are effective drugs for the treatment of type 2 diabetes mellitus. However, the relationship between DPP4 inhibitors and cognitive dysfunction remains unclear. Therefore, we used a meta-analysis to determine the association between DPP4 inhibitors and cognitive impairment in type 2 diabetes mellitus. Methods: We systematically searched PubMed, CNKI, and the Cochrane Library at the time of establishment, 2022, and then made inclusion criteria and screened strategies to identify studies with more precise correlations. Results: We included 10 studies with 5,583 participants. The data showed that DPP4 inhibitors significantly reduced the incidence rate of cognitive impairment in type 2 diabetes mellitus (SMD: 0.99; 95% CI [0.59, 1.38]). Furthermore, there was a linear correlation found between cognitive impairment in type 2 diabetes mellitus and fasting blood glucose, 2-hour postprandial blood glucose, and glycosylated hemoglobin. DPP4 inhibitors decreased fasting blood glucose (FPG) (SMD: 0.52; 95% CI [-0.68, -0.37]), blood glucose (2hPPG) at 2 hours after the meal (SMD: 0.82; 95% CI, [-1.2, -0.43]), and HbA1c (SMD: 0.34; 95% CI [-0.48, -0.21]). All data were statistically significant (P < 0.0001). Furthermore, we conducted subgroup analyses of the following measures at various treatment durations and ages: cognitive scores, fasting blood glucose, glycosylated hemoglobin, and two-hour postprandial blood glucose. Conclusion: DPP4 inhibitors significantly improved type 2 diabetic mellitus individuals' cognitive impairment and reduced fasting blood glucose, 2-hour postprandial blood glucose, and glycosylated hemoglobin. Subgroup analysis showed that people aged 60 to 70 years had better treatment effects at 0-180 days. This trial is registered with CRD42023399473.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis.

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

Association of autoantibodies against the M2-muscarinic receptor with perinatal outcomes in women with severe preeclampsia.

BACKGROUND: The goal of this study was to test the hypothesis that autoantibodies against M2-muscarinic acetylcholine receptor (M2-AAB) are associated with severe preeclampsia and increased risk of adverse perinatal outcomes. METHODS: We conducted a case-control study comparing 60 women with severe preeclampsia to 60 women with normal pregnancy and 60 non-pregnant controls. A peptide, corresponding to amino acid sequences of the second extracellular loops of the M2 receptor, was synthesized as antigen to test for the presence of autoantibodies, using an enzyme-linked immunosorbent assay. The frequency and titer of M2-AAB were compared in the 3 groups. The risk of adverse perinatal outcomes among women with severe preeclampsia in the presence of M2-AAB was estimated. RESULTS: M2-AAB were positive in 31.7% (19/60) of patients with severe preeclampsia, in 10.0% (6/60) (p=0.006) of normal pregnant women and in 8.3% (5/60) (p=0.002) of non-pregnant controls. The presence of M2-AAB was associated with increased risk of adverse pregnancy complications (OR, 3.6; 95%CI, 1.0-12.6; p=0.048), fetal growth restriction (OR, 6.8; 95% CI, 2.0-23.0; p=0.002), fetal distress (OR, 6.7; 95% CI, 1.7-26.6; p=0.007), low Apgar score (OR, 5.3; 95% CI, 1.4-20.7; p=0.017), and perinatal death (OR, 4.3; 95% CI, 1.0-17.6; p=0.044) among women with severe preeclampsia. CONCLUSIONS: This study demonstrates, for the first time, an increase in M2-AAB in patients with severe preeclampsia. Women with severe preeclampsia who are M2-AAB positive are at increased risk for neonatal mortality and morbidity. We posit that M2-AAB may be involved in the pathogenesis of severe preeclampsia.