Effectiveness and Safety of Direct Oral Anticoagulants Versus Warfarin in Patients with Atrial Fibrillation and Cancer: A Target Trial Emulation from SEER-Medicare Database.

BACKGROUND: Direct oral anticoagulants (DOACs) are preferred over warfarin in patients with atrial fibrillation (AFib). However, their safety and effectiveness in patients with AFib and cancer are inconclusive. METHODS: We conducted a retrospective cohort study by emulating a target trial. Patients with a record of cancer (breast, prostate, or lung), newly diagnosed with AFib initiated DOACs or warfarin within 3 months after AFib diagnosis from the 2012-2019 Surveillance, Epidemiology, and End Results (SEER)-Medicare database were included. We compared the risk of ischemic stroke, major bleeding, and secondary outcomes (venous thromboembolism, intracranial bleeding, gastrointestinal bleeding, and non-critical site bleeding) between patients who initiated DOACs and warfarin. Inverse probability treatment weights and inverse probability censoring weights were used to adjust imbalanced patient and disease characteristics and loss to follow-up between the two groups. Weighted pooled logistic regression were used to estimate treatment effect with hazard ratios (HRs) with 95% confidence interval (95% CIs). RESULTS: The incidence rates of stroke and major bleeding between DOAC and warfarin initiators were 9.97 vs. 9.91 and 7.74 vs. 9.24 cases per 1000 person-years, respectively. In adjusted intention-to-treat analysis, patients initiated DOACs had no statistically significant difference in risk of ischemic stroke (HR = 0.87, 95% CI 0.52-1.44) and major bleeding (HR = 1.14, 95% CI 0.77-1.68) compared to those initiated warfarin. In adjusted per-protocol analysis, there was no statistical difference in risk of ischemic stroke (HR = 1.81, 95% CI 0.75-4.36) and lower risk for major bleeding, but the 95% CI was wide (HR = 0.35, 95% CI 0.12-0.99) among DOAC initiators compared to warfarin initiators. The benefits in secondary outcomes were in favor of DOACs. The findings remained consistent across subgroups and sensitivity analyses. CONCLUSION: DOACs are safe and effective alternatives to warfarin in the management of patients with AFib and cancer.

Benefit and risk of oral anticoagulant initiation strategies in patients with atrial fibrillation and cancer: a target trial emulation using the SEER-Medicare database.

Oral anticoagulants (OACs) are recommended for patients with atrial fibrillation (AFib) having CHA2DS2-VASc score ≥ 2. However, the benefits of OAC initiation in patients with AFib and cancer at different levels of CHA2DS2-VASc is unknown. We included patients with new AFib diagnosis and a record of cancer (breast, prostate, or lung) from the 2012-2019 Surveillance, Epidemiology, and End Results (SEER)-Medicare database (n = 39,915). Risks of stroke and bleeding were compared between 5 treatment strategies: (1) initiated OAC when CHA2DS2-VASc ≥ 1 (n = 6008), (2) CHA2DS2-VASc ≥ 2 (n = 8694), (3) CHA2DS2-VASc ≥ 4 (n = 20,286), (4) CHA2DS2-VASc ≥ 6 (n = 30,944), and (5) never initiated OAC (reference group, n = 33,907). Confounders were adjusted using inverse probability weighting through cloning-censoring-weighting approach. Weighted pooled logistic regressions were used to estimate treatment effect [hazard ratios (HRs) and 95% confidence interval (95% CIs)]. We found that only patients who initiated OACs at CHA2DS2-VASc ≥ 6 had lower risk of stroke compared without OAC initiation (HR 0.64, 95% CI 0.54-0.75). All 4 active treatment strategies had reduced risk of bleeding compared to non-initiators, with OAC initiation at CHA2DS2-VASc ≥ 6 being the most beneficial strategy (HR = 0.49, 95% CI 0.44-0.55). In patients with lung cancer or regional/metastatic cancer, OAC initiation at any CHA2DS2-VASc level increased risk of stroke and did not reduce risk of bleeding (except for Regimen 4). In conclusion, among cancer patients with new AFib diagnosis, OAC initiation at higher risk of stroke (CHA2DS2-VASc score ≥ 6) is more beneficial in preventing ischemic stroke and bleeding. Patients with advanced cancer or low life-expectancy may initiate OACs when CHA2DS2-VASc score ≥ 6.

A comparative metabolomics analysis of Açaí (Euterpe oleracea Mart.) fruit, food powder, and botanical dietary supplement extracts.

INTRODUCTION: Euterpe oleracea Mart. (açaí) is a botanical of interest to many who seek functional foods that provide antioxidant and anti-inflammatory properties. Cancer patients are increasingly taking botanical dietary supplements containing açaí to complement their conventional therapeutics, which may lead to serious adverse events. Before testing our açaí extracts in vitro for botanical-drug interactions, the goal is to chemically characterize our extracts for compounds whose biological activity in açaí is unknown. OBJECTIVE: The objective of this work was to develop a chemical fingerprinting method for untargeted characterization of açaí samples from a variety of sources, including food products and botanical dietary supplement capsules, made with multiple extraction solvents. METHODS: An optimized LC-MS method was generated for in-depth untargeted fingerprinting of chemical constituents in açaí extracts. Statistical analysis models were used to describe relationships between the açaí extracts based on molecular features found in both positive and negative mode ESI. RESULTS: In an attempt to elucidate the differences in metabolites among açaí extracts from different cultivars, we identified or tentatively identified 173 metabolites from the 16 extracts made from 6 different sources. Of these compounds, there are 138 reported in açaí for the first time. Statistical models showed similar yet distinct differences between the extracts tested based on the polarity of compounds present and the origin of the source material. CONCLUSION: A high-resolution mass spectrometry method was generated that allowed us to greatly characterize 16 complex extracts made from different sources of açaí with different extraction solvent polarities.

Screening for clinically relevant drug-drug interactions between direct oral anticoagulants and antineoplastic agents: a pharmacovigilance approach.

BACKGROUND: Use of direct oral anticoagulants (DOACs) in patients with cancer remains suboptimal due to the concern regarding potential drug-drug interactions (DDIs) with antineoplastic treatments. However, the clinical relevance of these DDIs is unknown. METHODS: We conducted a pharmacovigilance study of adverse event (AE) reports from the US Food and Drug Administration Adverse Event Reporting System from 1/1/2004 to 12/31/2021. AE reports containing DOACs and antineoplastic agents with CYP3A4/P-gp inhibitory or inducing activity suggested by published pharmacokinetic studies were included (n = 36,066). The outcomes of interest were bleeding or stroke, identified by MedDRA dictionary version 25.0. We used disproportionality analyses (DPA), logistic regression models (LR), and Multi-item Gamma-Poisson Shrinker (MGPS) (Empirical Bayes Geometric Means (EBGM) and 90% credible intervals (90% CIs)) algorithms to identify the safety signal of DDIs. RESULTS: The highest bleeding reporting rates for each drug class were the combination of DOACs with neratinib (39.08%, n = 34), tamoxifen (21.22%, n = 104), irinotecan (20.54%, n = 83), and cyclosporine (19.17%, n = 227). The highest rate of stroke was found for prednisolone (2.43%, n = 113). In the primary analysis, no signal of DDIs by the antineoplastic therapeutic class was detected by MGPS, DPA, and LR approaches. By individual antineoplastic drug, DOACs-neratinib was the only signal detected [EBGM (EB05-EB95) = 2.71 (2.03-3.54)]. CONCLUSION: No signal of DDIs between DOACs and antineoplastic agents was detected, except for DOAC-neratinib. Most DDIs between DOACs and antineoplastic agents may not be clinically relevant. The DDIs between DOACs and neratinib should be further examined in future research.

Distinct inhibitory strength of bisphenol A analogues on human and rat 11ß-hydroxysteroid dehydrogenase 1: 3D quantitative structure-activity relationship and in silico molecular docking analysis.

Bisphenol A (BPA) analogues are developed to replace BPA usage. However, their effects on 11ß-hydroxysteroid dehydrogenase 1 (11ß-HSD1) are largely unknown. The inhibitory effects of BPA and 10 BPA analogues with the substituents on the bridge moiety on human and rat 11ß-HSD1 were explored in human and rat liver microsomes. The strength of inhibiting human 11ß-HSD1 was bisphenol FL (IC50, 3.87 µM) > bisphenol Z (6.86 µM) > bisphenol AF (9.42 µM) > bisphenol C (16.14 µM) > bisphenol AP (32.14 µM) = bisphenol B (32.34 µM) > 4,4'-thiodiphenol (67.35 µM) > BPA (297.35 µM) > other BPA analogues (ineffective at 100 µM). The strength of inhibiting rat 11ß-HSD1 was bisphenol Z (IC50, 14.44 µM) > 4,4'-thiodiphenol (19.01 µM) > bisphenol B (20.13 µM) > bisphenol F (22.10 µM) > bisphenol E (33.04 µM) > bisphenol AF (49.67 µM) > bisphenol C > (56.97 µM) > bisphenol AP (62.71 µM) >bisphenol FL (96.31 µM) > other BPA analogues (ineffective at 100 µM). Bisphenol A, AF, AP, B, C, F, FL, Z, and 4,4'-thiodiphenol bind to the active sites of human and rat 11ß-HSD1. Regression of LogP and molecular weight with IC50 values revealed distinct inhibitory pattern (negative correlation for human 11ß-HSD1 vs. positive correlation for rat enzyme). Regression of the lowest binding energy with IC50 values revealed a significant positive regression. 3D QSAR pharmacophore analysis showed one hydrogen bond acceptor and two hydrogen bond donors for human 11ß-HSD1. In conclusion, most BPA analogues are more potent inhibitors of human and rat 11ß-HSD1 enzymes and there is structure-dependent and species-dependent inhibition.

Common and Distinct Roles of Frontal Midline Theta and Occipital Alpha Oscillations in Coding Temporal Intervals and Spatial Distances.

Judging how far away something is and how long it takes to get there is critical to memory and navigation. Yet, the neural codes for spatial and temporal information remain unclear, particularly the involvement of neural oscillations in maintaining such codes. To address these issues, we designed an immersive virtual reality environment containing teleporters that displace participants to a different location after entry. Upon exiting the teleporters, participants made judgments from two given options regarding either the distance they had traveled (spatial distance condition) or the duration they had spent inside the teleporters (temporal duration condition). We wirelessly recorded scalp EEG while participants navigated in the virtual environment by physically walking on an omnidirectional treadmill and traveling through teleporters. An exploratory analysis revealed significantly higher alpha and beta power for short-distance versus long-distance traversals, whereas the contrast also revealed significantly higher frontal midline delta-theta-alpha power and global beta power increases for short versus long temporal duration teleportation. Analyses of occipital alpha instantaneous frequencies revealed their sensitivity for both spatial distances and temporal durations, suggesting a novel and common mechanism for both spatial and temporal coding. We further examined the resolution of distance and temporal coding by classifying discretized distance bins and 250-msec time bins based on multivariate patterns of 2- to 30-Hz power spectra, finding evidence that oscillations code fine-scale time and distance information. Together, these findings support partially independent coding schemes for spatial and temporal information, suggesting that low-frequency oscillations play important roles in coding both space and time.

Electrochemical Nanoaptasensor for Continuous Monitoring of ATP Fluctuation at Subcellular Level.

Monitoring the fluctuation of adenosine 5'-triphosphate (ATP) at the subcellular level is important for the study of cell energy metabolism. Herein, we fabricated an electrochemical nanoaptasensor for continuously monitoring ATP fluctuation at the subcellular level. A gold nanoelectrode with a diameter of 120 nm was fabricated, and ferrocene (Fc)-labeled anti-ATP aptamer was self-assembled onto the nanoelectrode surface to form a nanoaptasensor. In the presence of ATP, the ferrocene-labeled anti-ATP aptamer bound with two ATP units to form an ATP-aptamer conjugation, resulting in the close proximity of Fc to the nanoelectrode surface and then an increase of oxidation current of Fc. ATP can be detected with a detection limit of 26 µM within 2 min. Cell viability assays indicated that the nanoaptasensor was biocompatible with negligible biological effects. By taking advantage of the good biocompatibility of the nanoaptasensor, ATP fluctuation at the subcellular level was monitored under glucose starvation and Ca2+ induction. This work demonstrates that the nanoaptasensor is a useful tool for investigating ATP-relevant biological processes via the electrochemical method.

CIP2A facilitates the G1/S cell cycle transition via B-Myb in human papillomavirus 16 oncoprotein E6-expressing cells.

Infection with high-risk human papillomaviruses (HR-HPVs, including HPV-16, HPV-18, HPV-31) plays a central aetiologic role in the development of cervical carcinoma. The transforming properties of HR-HPVs mainly reside in viral oncoproteins E6 and E7. E6 protein degrades the tumour suppressor p53 and abrogates cell cycle checkpoints. Cancerous inhibitor of protein phosphatase 2A (CIP2A) is an oncoprotein that is involved in the carcinogenesis of many human malignancies. Our previous data showed that CIP2A was overexpressed in cervical cancer. However, the regulation of CIP2A by HPV-16E6 remains to be elucidated. In this study, we demonstrated that HPV-16E6 significantly up-regulated CIP2A mRNA and protein expression in a p53-degradation-dependent manner. Knockdown of CIP2A by siRNA inhibited viability and DNA synthesis and caused G1 cell cycle arrest of 16E6-expressing cells. Knockdown of CIP2A resulted in a significant reduction in the expression of cyclin-dependent kinase 1 (Cdk1) and Cdk2. Although CIP2A has been reported to stabilize c-Myc by inhibiting PP2A-mediated dephosphorylation of c-Myc, we have presented evidence that the regulation of Cdk1 and Cdk2 by CIP2A is dependent on transcription factor B-Myb rather than c-Myc. Taken together, our study reveals the role of CIP2A in abrogating the G1 checkpoint in HPV-16E6-expressing cells and helps in understanding the molecular basis of HPV-induced oncogenesis.

CW_ICA: an efficient dimensionality determination method for independent component analysis.

Independent component analysis (ICA) is a widely used blind source separation method for signal pre-processing. The determination of the number of independent components (ICs) is crucial for achieving optimal performance, as an incorrect choice can result in either under-decomposition or over-decomposition. In this study, we propose a robust method to automatically determine the optimal number of ICs, named the column-wise independent component analysis (CW_ICA). CW_ICA divides the mixed signals into two blocks and applies ICA separately to each block. A quantitative measure, derived from the rank-based correlation matrix computed from the ICs of the two blocks, is utilized to determine the optimal number of ICs. The proposed method is validated and compared with the existing determination methods using simulation and scalp EEG data. The results demonstrate that CW_ICA is a reliable and robust approach for determining the optimal number of ICs. It offers computational efficiency and can be seamlessly integrated with different ICA methods.

Adsorption of metals on aged microplastics in intensive mariculture areas: Aggravating the potential ecological risks to marine organisms.

Field determination of the metal adsorption capacity of microplastics (MPs) by using a passive sampler had been done in typical subtropical mariculture area in China. The adsorption of eight metals (Fe, Mn, Cu, Zn, As, Pb, Cr and Cd) by five types of MPs (low-density polyethylene, polypropylene, polystyrene, poly(ethylene terephthalate) and poly(vinyl chloride) (PVC) was compared, including metal types, mariculture types (cage and longline culture), metal residue content in ambient environment, polymer types and particle sizes of MPs. The results showed that Cu, Zn, As, Cd, Pb and Cr in the mariculture environment were contaminated compared with the quality criteria. The concentrations of these six metals adsorbed on five MPs increased linearly with those in seawater. More enriched Cu and As in MPs in marine cage culture than in longline culture, due to the obvious endogenous pollution emissions for the artificial diets, fish medicine and disinfectants. Aged PVC with more cracks and pores showed higher metal adsorption capacity than any other polymers. MPs with a smaller size range of 50-74 µm tended to accumulate higher amounts of metals than those with a larger size range of 74-178 µm, consisting with the surface characteristics of MPs. The significant positive relationship between the concentrations of nutrients in seawater and the adsorption amounts of Cu, Zn and As on MPs implies that the eutrophication would promote their pollution. Based on the ecological risk assessment, the occurrence of MPs could aggravate the potential risk of metals to marine organisms in intensive mariculture areas. This is the first time to reveal the impacts of the adsorption of metals on aged MPs on the potential ecological risks of metals to organisms under the realistic environmental condition.

Machine Learning Approach for Cardiovascular Death Prediction among Nonalcoholic Steatohepatitis (NASH) Liver Transplant Recipients.

Cardiovascular disease is the leading cause of mortality among nonalcoholic steatohepatitis (NASH) patients who undergo liver transplants. In the present study, machine learning algorithms were used to identify important risk factors for cardiovascular death and to develop a prediction model. The Standard Transplant Analysis and Research data were gathered from the Organ Procurement and Transplantation Network. After cleaning and preprocessing, the dataset comprised 10,871 patients and 92 features. Recursive feature elimination (RFE) and select from model (SFM) were applied to select relevant features from the dataset and avoid overfitting. Multiple machine learning algorithms, including logistic regression, random forest, decision tree, and XGBoost, were used with RFE and SFM. Additionally, prediction models were developed using a support vector machine, Gaussian naïve Bayes, K-nearest neighbors, random forest, and XGBoost algorithms. Finally, SHapley Additive exPlanations (SHAP) were used to increase interpretability. The findings showed that the best feature selection method was RFE with a random forest estimator, and the most critical features were recipient and donor blood type, body mass index, recipient and donor state of residence, serum creatinine, and year of transplantation. Furthermore, among all the outcomes, the XGBoost model had the highest performance, with an accuracy value of 0.6909 and an area under the curve value of 0.86. The findings also revealed a predictive relationship between features and cardiovascular death after liver transplant among NASH patients. These insights may assist clinical decision-makers in devising strategies to prevent cardiovascular complications in post-liver transplant NASH patients.

Revealing the potential effects of oil phase on the stability and bioavailability of astaxanthin contained in Pickering emulsions: In vivo, in vitro and molecular dynamics simulation analysis.

This study investigated the effects of oil phases on the encapsulation rate, storage stability, and bioavailability of astaxanthin (ASTA) in Pickering emulsions (PEs). Results showed PEs of mixed oils (olive oil/edible tea oil) had excellent encapsulation efficiency (about 96.0%) and storage stability of ASTA. In vitro simulated gastrointestinal digestion results showed the mixed oil PE with a smaller interfacial area and higher monounsaturated fatty acid content may play a better role in improving ASTA retention and bioaccessibility. In vivo absorption results confirmed the mixed oil PE with an olive oil/edible tea oil of 7:3 was more favorable for ASTA absorption. Molecular dynamics simulation showed ASTA bound more strongly and stably to fatty acid molecules in the system of olive oil/edible tea oil of 7:3; and van der Waals force was the main binding force. NMR further proved there really were interactions between ASTA and four main fatty acids.

Development and Validation of Machine Learning Algorithms to Predict 1-Year Ischemic Stroke and Bleeding Events in Patients with Atrial Fibrillation and Cancer.

In this study, we leveraged machine learning (ML) approach to develop and validate new assessment tools for predicting stroke and bleeding among patients with atrial fibrillation (AFib) and cancer. We conducted a retrospective cohort study including patients who were newly diagnosed with AFib with a record of cancer from the 2012-2018 Surveillance, Epidemiology, and End Results (SEER)-Medicare database. The ML algorithms were developed and validated separately for each outcome by fitting elastic net, random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and neural network models with tenfold cross-validation (train:test = 7:3). We obtained area under the curve (AUC), sensitivity, specificity, and F2 score as performance metrics. Model calibration was assessed using Brier score. In sensitivity analysis, we resampled data using Synthetic Minority Oversampling Technique (SMOTE). Among 18,388 patients with AFib and cancer, 523 (2.84%) had ischemic stroke and 221 (1.20%) had major bleeding within one year after AFib diagnosis. In prediction of ischemic stroke, RF significantly outperformed other ML models [AUC (0.916, 95% CI 0.887-0.945), sensitivity 0.868, specificity 0.801, F2 score 0.375, Brier score = 0.035]. However, the performance of ML algorithms in prediction of major bleeding was low with highest AUC achieved by RF (0.623, 95% CI 0.554-0.692). RF models performed better than CHA2DS2-VASc and HAS-BLED scores. SMOTE did not improve the performance of the ML algorithms. Our study demonstrated a promising application of ML in stroke prediction among patients with AFib and cancer. This tool may be leveraged in assisting clinicians to identify patients at high risk of stroke and optimize treatment decisions.

Assessing the role of dryness and burning sensation in diagnosing laryngopharyngeal reflux.

Laryngopharyngeal reflux disease (LPRD) is a condition characterized by the regurgitation of stomach and duodenal contents into the laryngopharynx, with variable and non-specific symptoms. Therefore, developing an accurate symptom scale for different regions is essential. Notably, the symptoms of "dryness and burning sensation in the laryngopharynx or mouth" are prevalent among the Chinese population but are often omitted from conventional symptom assessment scales, such as the Reflux Symptom Index (RSI) and Reflux Symptom Score-12 (RSS-12) scales. To address this gap, our study incorporated the symptoms into the RSI and RSS-12 scales, developing the RSI-10/RSS-13 scales. Afterward, we assessed the role of the new scale's reliability (Cronbach's α and test-retest reliability), construct validity (confirmatory factor analysis and confirmatory factor analysis), and diagnostic efficiency. Our study encompassed 479 participants (average = 39.5 ± 13.4 years, 242 female) and 91 (average = 34.01 ± 13.50 years, 44 female) completed 24 h MII-pH monitoring. The Cronbach's α values of 0.80 and 0.82 for the RSI-10 and RSS-13 scales, respectively. RSI-10 and RSS-13 exhibited strong test-retest reliability (ICCs = 0.82-0.96) and diagnostic efficacy (AUC = 0.84-0.85). Furthermore, the factor analysis identified the RSS-13 and its three sub-scales (ear-nose-throat, digestive tract, respiratory tract) exhibited good to excellent structural validity (χ2/df = 1.95, P < 0.01; CFI = 0.95, RMSEA = 0.06, SRMR = 0.05). The AUC optimal thresholds for the RSI-10 and RSS-13 in the Chinese population were 13 and 36, respectively. Besides, the inclusion of the new item significantly improved the diagnostic efficiency of the RSI scale (P = 0.04), suggesting that RSI-10 holds promise as a more effective screening tool for LPRD, and global validation is needed to demonstrate the impact of this new symptom on the diagnosis of LPRD.

Effect of Laryngopharyngeal Reflux and Potassium-Competitive Acid Blocker (P-CAB) on the Microbiological Comprise of the Laryngopharynx.

OBJECTIVE: To probe the microbiota composition progressing from healthy individuals to those with laryngopharyngeal reflux disease (LPRD) and subsequently undergoing potassium-competitive acid inhibitor (P-CAB) therapy. STUDY DESIGN: Prospective case-control study. SETTING: Academic Medical Center. METHODS: Forty patients with LPRD and 51 patients without LPRD were recruited. An 8-week P-CAB therapy was initiated (post-T-LPRD), and 39 had return visits. In total, 130 laryngopharyngeal saliva samples were collected and sequenced by targeting the V3-V4 region of the 16S ribosomal RNA (rRNA) gene using an Illumina MiSeq. Amplicon sequence variants (ASVs) and clinical indices were analyzed. RESULTS: Alpha and beta diversities were compared among the non-LPRD, LPRD, and post-T-LPRD groups, and the Observed_ASVs were not significantly different. At the same time, the Shannon and Simpson indices, unweighted Unifrac, weighted Unifrac, and binary Jaccard distance were significantly different between non-LPRD and LPRD groups. In addition, significant differences were found in the abundance of Streptococcus, Prevotella, and Prevotellaceae in the LPRD versus non-LPRD groups, and Neisseria, Leptotrichia, and Allprevotella in the LPRD versus post-T-LPRD groups. The genera model was used to distinguish patients with LPRD from those without, and a better receiver operating characteristic curve was formed after combining the clinical indices of reflux symptom index, reflux finding score, and pepsin, with an area under the curve of 0.960. CONCLUSION: Laryngopharyngeal microbial communities changed after laryngopharyngeal reflux and were modified further after P-CAB treatment, which provides a potential diagnostic value for LPRD, especially when combined with clinical indices.

Amelioration of walnut, peony seed and camellia seed oils against D-galactose-induced cognitive impairment in mice by regulating gut microbiota.

Diet adjustment will affect the health of gut microbiota, which in turn influences the development and function of the organism's brain through the gut-brain axis. Walnut oil (WO), peony seed oil (PSO) and camellia seed oil (CSO), as typical representatives of woody plant oils, have been shown to have the potential to improve cognitive impairment in mice, but the function mechanisms are not clear. In this study, we comparatively investigated the neuroprotective effects of these three oils on D-galactose (D-gal)-induced cognitive impairment in mice, and found that the ameliorative effect of WO was more prominent. During the behavioral experiments, supplementation with all three oils would improve spatial learning and memory functions in D-gal mice, with a significant reduction in the error times (p < 0.001) and a significant increase in step-down latency (p < 0.001); walnut oil supplementation also significantly increased the number of hidden platform traversals, the target quadrant spent times and percentage of distance (p < 0.05). The results of biomarker analysis showed that WO, in addition to significantly inhibiting D-gal-induced oxidative stress and neuroinflammation as did PSO, significantly increased the ACh content in the mouse brain (p < 0.05) and modulated neurotransmitter levels. The results of further microbiota diversity sequencing experiments also confirmed that dietary supplementation with all three oils affected the diversity and composition of the gut microbiota in mice. Among them, WO significantly restored the balance of the mouse gut microbiota by increasing the abundance of beneficial bacteria (Bacteroidetes, Actinobacteria, Firmicutes) and decreasing the abundance of harmful bacteria (Clostridium, Shigella, Serratia), which was consistent with the results of behavioral experiments and biomarker analyses. Based on the analysis of the fatty acid composition of the three oils and changes in the gut microbiota, it is hypothesized that there is a correlation between the fatty acid composition of the dietary supplement oils and neuroprotective effects. The superiority of WO over PSO and CSO in improving cognitive impairment is mainly attributed to its balanced composition of omega-6 and omega-3 fatty acids.

Bisphenol a alternatives suppress human and rat aromatase activity: QSAR structure-activity relationship and in silico docking analysis.

The use of alternative substances to replace bisphenol A (BPA) has been encouraged. The objective of this study was to evaluate the effects of BPA and 9 BPA alternatives on human and rat aromatase (CYP19A1) in human and rat placental microsomes. The results revealed that bisphenol A, AP, B, C, E, F, FL, S, and Z, and 4,4'-thiodiphenol (TDP) inhibited human CYP19A1 and bisphenol A, AP, B, C, FL, Z, and TDP inhibited rat CYP19A1. The IC50 values of human CYP19A1 ranged from 3.3 to 172.63 µM and those of rat CYP19A1 ranged from 2.20 to over 100 µM. BPA alternatives were mixed/competitive inhibitors and inhibited estradiol production in BeWo placental cells. Molecular docking analysis showed that BPA alternatives bind to the domain between heme and steroid and form a hydrogen bond with catalytic residue Met374. Pharmacophore analysis showed that there were one hydrogen bond donor, one hydrophobic region, and one ring aromatic hydrophobic region. Bivariate correlation analysis showed that molecular weight, alkyl atom weight, and LogP of BPA alternatives were inversely correlated with their IC50 values. In conclusion, BPA alternatives can inhibit human and rat CYP19A1 and the lipophilicity and the substituted alkyl size determines their inhibitory strength.

Enhanced inhibition of human and rat aromatase activity by benzene ring substitutions in bisphenol A: QSAR structure-activity relationship and in silico docking analysis.

Bisphenol A (BPA) is a widely used plastic material, but its potential endocrine disrupting effect has restricted its use. The BPA alternatives have raised concerns. This study aimed to compare inhibitory potencies of 11 BPA analogues on human and rat placental aromatase (CYP19A1). The inhibitory potency on human CYP19A1 ranged from bisphenol H (IC50, 0.93 µM) to tetramethyl BPA and tetrabromobisphenol S (ineffective at 100 µM) when compared to BPA (IC50, 73.48 µM). Most of them were mixed/competitive inhibitors and inhibited estradiol production in human BeWo cells. Molecular docking analysis showed all BPA analogues bind to steroid active site or in between steroid and heme of CYP19A1 and form a hydrogen bond with catalytic residue Met374. Pharmacophore analysis showed that there were 4 hydrophobic regions for BPA analogues, with bisphenol H occupying 4 regions. Bivariate correlation analysis showed that LogP (lipophilicity) and LogS (water solubility) of BPA analogues were correlated with their IC50 values. Computerized drug metabolism and pharmacokinetics analysis showed that bisphenol H, tetrabromobisphenol A, and tetrachlorobisphenol A had low solubility, which might explain their weaker inhibition on estradiol production on BeWo cells. In conclusion, BPA analogues mostly can inhibit CYP19A1 and the lipophilicity determines their inhibitory strength.

Associations between memory performance and Bifidobacterium pseudolongum abundance in the canine gut microbiome.

Memory has been identified as the least heritable cognitive trait in canines, suggesting a significant influence of non-genetic factors. We observed a trend that overall memory scores (OMS) improve with age in a cohort of 27 young dogs, but considerable plasticity exists. Employing linear discriminant analysis of gut microbiome data from dogs exhibiting low and high OMS, a single bacterial species, Bifidobacterium pseudolongum, was identified and confirmed to be correlated with elevated OMS. Subsequent analysis using a random forest regression model revealed that sex, litter, and breed identity had minimal predictive importance. Age had some predictive value but failed to achieve statistical significance in this dataset. In sharp contrast, the abundance of 17 bacterial taxa in the microbiome showed a stronger predictive capacity for memory performance. Our findings provide insights into microbiome underpinnings of mammalian cognitive functions and suggest avenues for developing psychobiotics to enhance canine memory and learning.

Use of second-generation antidiabetic medication among a nationally representative sample.

OBJECTIVES: Existing studies have shown the benefits of second-generation antidiabetic medications in patients with type 2 diabetes (T2D). However, the medications' real-world utilization was not well understood. Our study assessed patient factors associated with the use of second-generation antidiabetic medications in a nationally representative sample of patients with T2D. STUDY DESIGN: This retrospective, cross-sectional analysis used the 2005 to 2018 National Health and Nutrition Examination Survey (NHANES) data. METHODS: Survey participants 18 years and older who had a diagnosis of T2D and had used antidiabetic medications in the past 30 days were included. The primary outcome was the prescription of any second-generation antidiabetic medication. Weighted stepwise multivariable logistic regression models were used to assess the associations between the use of second-generation antidiabetic medications and patients' characteristics. RESULTS: Among 4493 patients with T2D, 533 (weighted %, 13.67%) reported using at least 1 second-generation antidiabetic drug. In multivariable analyses, patients with incomes at least 400% of the federal poverty level (adjusted odds ratio [AOR], 2.30; 95% CI, 1.58-3.34), with higher hemoglobin A1c levels (AOR, 1.10; 95% CI, 1.02-1.18), and taking more medications (AOR, 1.14; 95% CI, 1.09-1.20) were more likely to use second-generation antidiabetic drugs compared with their counterparts. CONCLUSIONS: The uptake of second-generation antidiabetic medications was 14% among patients with T2D in the United States. Prescription benefit design that targets lower out-of-pocket payments for these newer drugs may improve patient access and clinical outcomes for patients with T2D.