scHiCStackL: a stacking ensemble learning-based method for single-cell Hi-C classification using cell embedding.

Single-cell Hi-C data are a common data source for studying the differences in the three-dimensional structure of cell chromosomes. The development of single-cell Hi-C technology makes it possible to obtain batches of single-cell Hi-C data. How to quickly and effectively discriminate cell types has become one hot research field. However, the existing computational methods to predict cell types based on Hi-C data are found to be low in accuracy. Therefore, we propose a high accuracy cell classification algorithm, called scHiCStackL, based on single-cell Hi-C data. In our work, we first improve the existing data preprocessing method for single-cell Hi-C data, which allows the generated cell embedding better to represent cells. Then, we construct a two-layer stacking ensemble model for classifying cells. Experimental results show that the cell embedding generated by our data preprocessing method increases by 0.23, 1.22, 1.46 and 1.61$\%$ comparing with the cell embedding generated by the previously published method scHiCluster, in terms of the Acc, MCC, F1 and Precision confidence intervals, respectively, on the task of classifying human cells in the ML1 and ML3 datasets. When using the two-layer stacking ensemble framework with the cell embedding, scHiCStackL improves by 13.33, 19, 19.27 and 14.5 over the scHiCluster, in terms of the Acc, ARI, NMI and F1 confidence intervals, respectively. In summary, scHiCStackL achieves superior performance in predicting cell types using the single-cell Hi-C data. The webserver and source code of scHiCStackL are freely available at http://hww.sdu.edu.cn:8002/scHiCStackL/ and https://github.com/HaoWuLab-Bioinformatics/scHiCStackL, respectively.

Prognostic implications of premature ventricular contractions and non-sustained ventricular tachycardia in light-chain cardiac amyloidosis.

AIMS: Premature ventricular contractions (PVC) and non-sustained ventricular tachycardia (NSVT) are commonly observed in light chain cardiac amyloidosis (AL-CA), but their association with prognosis is still unclear. We aimed to evaluate the prognostic value of PVCs and NSVT in patients with moderate-to-advanced AL-CA. METHODS AND RESULTS: We retrospectively included patients with AL-CA at modified 2004 Mayo stages II-IIIb between February 2014 and December 2020. Twenty-four-hour Holter recordings were assessed on admission. The outcomes included (i) new onset of adverse ventricular arrhythmia (VA) or sudden cardiac death (SCD) and (ii) cardiac death during follow-up. Of the 143 patients studied (60.41 ± 11.06 years, male 64.34%), 132 (92.31%) had presence of PVC, and 50 (34.97%) had NSVT on Holter. Twelve (8.4%) patients died in hospital and 131 patients were followed up (median 24.4 months), among whom 71 patients had cardiac death, and 15 underwent adverse VA/SCD. NSVT [hazard ratio (HR): 13.57, 95% confidence interval (CI): 3.06-60.18, P < 0.001], log-transformed PVC counts (HR: 1.46, 95%CI: 1.15-1.86, P = 0.002) and PVC burden (HR: 1.43 95%CI:1.14-1.80, P = 0.002) were predictive of new onset of adverse VA/SCD. The highest tertile of PVC counts (HR: 2.33, 95%CI: 1.27-4.28, P = 0.006) and PVC burden (HR: 2.58, 95%CI: 1.42-4.69, P = 0.002), rather than NSVT (HR: 1.16, 95%CI: 0.67-1.98, P = 0.603), was associated with cardiac death. Higher PVC counts/burden provided incremental value on modified 2004 Mayo stage in predicting cardiac death, with C index increasing from 0.681 to 0.712 and 0.717, respectively (P values <0.05). CONCLUSION: PVC count, burden, and NSVT significantly correlated with adverse VA/SCD during follow-up in patients with AL-CA. Higher PVC counts/burdens added incremental value for predicting cardiac death.

Two novel in vitro assays to screen chemicals for their capacity to inhibit thyroid hormone transmembrane transporter proteins OATP1C1 and OAT4.

Early brain development depends on adequate transport of thyroid hormones (THs) from the maternal circulation to the fetus. To reach the fetal brain, THs have to cross several physiological barriers, including the placenta, blood-brain-barrier and blood-cerebrospinal fluid-barrier. Transport across these barriers is facilitated by thyroid hormone transmembrane transporters (THTMTs). Some endocrine disrupting chemicals (EDCs) can interfere with the transport of THs by THTMTs. To screen chemicals for their capacity to disrupt THTMT facilitated TH transport, in vitro screening assays are required. In this study, we developed assays for two THTMTs, organic anion transporter polypeptide 1C1 (OATP1C1) and organic anion transporter 4 (OAT4), both known to play a role in the transport of THs across barriers. We used overexpressing cell models for both OATP1C1 and OAT4, which showed an increased uptake of radiolabeled T4 compared to control cell lines. Using these models, we screened various reference and environmental chemicals for their ability to inhibit T4 uptake by OATP1C1 and OAT4. Tetrabromobisphenol A (TBBPA) was identified as an OATP1C1 inhibitor, more potent than any of the reference chemicals tested. Additionally perfluorooctanesulfonic acid (PFOS), perfluoroctanic acid (PFOA), pentachlorophenol and quercetin were identified as OATP1C1 inhibitors in a similar range of potency to the reference chemicals tested. Bromosulfophthalein, TBBPA, PFOA and PFOS were identified as potent OAT4 inhibitors. These results demonstrate that EDCs commonly found in our environment can disrupt TH transport by THTMTs, and contribute to the identification of molecular mechanisms underlying TH system disruption chemicals.

Cardiac magnetic resonance-derived myocardial scar is associated with echocardiographic response and clinical prognosis of left bundle branch area pacing for cardiac resynchronization therapy.

AIMS: Left bundle branch area pacing (LBBAP) is a novel approach for cardiac resynchronization therapy (CRT), but the impact of myocardial substrate on its effect is poorly understood. This study aims to assess the association of cardiac magnetic resonance (CMR)-derived scar burden and the response of CRT via LBBAP. METHODS AND RESULTS: Consecutive patients with CRT indications who underwent CMR examination and successful LBBAP-CRT were retrospectively analysed. Cardiac magnetic resonance late gadolinium enhancement was used for scar assessment. Echocardiographic reverse remodelling and composite outcomes (defined as all-cause death or heart failure hospitalization) were evaluated. The echocardiographic response was defined as a ≥15% reduction of left ventricular end-systolic volume. Among the 54 patients included, LBBAP-CRT resulted in a 74.1% response rate. The non-responders had higher global, septal, and lateral scar burden (all P < 0.001). Global, septal, and lateral scar percentage all predicted echocardiographic response [area under the curve (AUC): 0.857, 0.864, and 0.822; positive likelihood ratio (+LR): 9.859, 5.594, and 3.059; and negative likelihood ratio (-LR): 0.323, 0.233, and 0.175 respectively], which was superior to QRS morphology criteria (Strauss left bundle branch abnormality: AUC: 0.696, +LR 2.101, and -LR 0.389). After a median follow-up time of 20.3 (11.5-38.7) months, higher global, lateral and septal scar burdens were all predictive of the composite outcome (hazard ratios: 4.996, 7.019, and 4.741, respectively; P's < 0.05). CONCLUSION: Lower scar burden was associated with higher response rate of LBBAP-CRT. The pre-procedure CMR scar evaluation provides further useful information to identify potential responders and clinical outcomes.

Screening of Endocrine Disrupting Potential of Surface Waters via an Affinity-Based Biosensor in a Rural Community in the Yellow River Basin, China.

Overcoming the limitations of traditional analytical methods and developing technologies to continuously monitor environments and produce a comprehensive picture of potential endocrine-disrupting chemicals (EDCs) has been an ongoing challenge. Herein, we developed a portable nuclear receptor (NR)-based biosensor within 90 min to perform highly sensitive analyses of a broad range of EDCs in environmental water samples. Based on the specific binding of the fluorescence-labeled NRs with their ligands, the receptors were attached to the EDC-functionalized fiber surface by competing with EDCs in the samples. The biosensor emitted fluorescence due to the evanescent wave excitation, thereby resulting in a turn-off sensing mode. The biosensor showed a detection limit of 5 ng/L E2-binding activity equivalent (E2-BAE) and 93 ng/L T3-BAE. As a case study, the biosensor was used to map the estrogenic binding activities of surface waters obtained from a rural community in the Yellow River basin in China. When the results obtained were compared with those from the traditional yeast two-hybrid bioassay, a high correlation was observed. It is anticipated that the good universality and versatility exhibited by this biosensor for various EDCs, which is achieved by using different NRs, will significantly promote the continuous assessment of global EDCs.

Freeze-thaw alternations accelerate plasticizers release and pose a risk for exposed organisms.

The application of plastic mulch films brings convenience to agricultural production, but also causes plastic waste that can be degraded into microplastics (MPs). However, little is known about the fate of plastic waste in agricultural ecosystem under freeze-thaw alternation in middle and high latitudes, as well as in highlands around the world. Whether the release of plasticizers, i.e. phthalate esters (PAEs), under such conditions would pose a potential risk to exposed organisms due to bioaccumulation is also unknown. To fill these data gaps, the agricultural fields in Liaoning of China with typical freeze-thaw alternation was selected as the study area. The transformation of plastic film was demonstrated by simulation freeze-thaw alternating from -30 to 20 â„ƒ. Soil samples were collected to investigate the patterns of MP composition, abundance, and distribution. Concurrently, the concentrations of two PAEs including bis(2-ethylhexyl) phthalate (DEHP) and diethyl phthalate (DEP) in soils were analyzed to provide information on the correlation between MPs abundance and PAEs concentrations as well as potential risks. The results showed that freeze-thaw alternating can accelerate the formation of MPs and release of PAEs from plastic waste. The abundance of MPs was positively correlated with the concentration of PAEs. Soil PAEs ranged from 3268 ± 213-6351 ± 110 µg/kg, indicating that over 40 % of the PAEs were transferred from plastic films to soils. Such residual amounts could pose risk for exposed organisms. Hence, the current study suggested that special concerns should be given to the release plasticizers in plastic waste of agricultural soils.

Thyroid Hormone Transporters in Pregnancy and Fetal Development.

Thyroid hormone is essential for fetal (brain) development. Plasma membrane transporters control the intracellular bioavailability of thyroid hormone. In the past few decades, 15 human thyroid hormone transporters have been identified, and among them, mutations in monocarboxylate transporter (MCT)8 and organic anion transporting peptide (OATP)1C1 are associated with clinical phenotypes. Different animal and human models have been employed to unravel the (patho)-physiological role of thyroid hormone transporters. However, most studies on thyroid hormone transporters focus on postnatal development. This review summarizes the research on the thyroid hormone transporters in pregnancy and fetal development, including their substrate preference, expression and tissue distribution, and physiological and pathophysiological role in thyroid homeostasis and clinical disorders. As the fetus depends on the maternal thyroid hormone supply, especially during the first half of pregnancy, the review also elaborates on thyroid hormone transport across the human placental barrier. Future studies may reveal how the different transporters contribute to thyroid hormone homeostasis in fetal tissues to properly facilitate development. Employing state-of-the-art human models will enable a better understanding of their roles in thyroid hormone homeostasis.

Toll-Like Receptor 4 Mediated Oxidized Low-Density Lipoprotein-Induced Foam Cell Formation in Vascular Smooth Muscle Cells via Src and Sirt1/3 Pathway.

Oxidized low-density lipoprotein (oxLDL) induced a foam-cell-like phenotype of the vascular smooth muscle cells (VSMCs), leading to the inflammatory responses incorporating Toll-like receptor- (Tlr-) mediated cellular alterations. However, the role of Tlr4 in foam cell formation and underlying molecular pathways has not been comprehensively elucidated. To further investigate the mechanism, VSMCs were incubated with different doses of oxLDL, and then, the lipid, reactive oxygen species (ROS) accumulation, Tlr family genes, and the foam cell phenotype were explored. We observed that oxLDL induced foam cell-like phenotype in VSMCs and led to lipid and ROS accumulation in a dose-dependent manner. Furthermore, in the Tlr family, Tlr4 demonstrated the strongest upregulation under oxLDL stimulation. Simultaneously, oxLDL induced activation of Src, higher expression of Nox2, and lower expression of Mnsod, Sirt1, and Sirt3. By interfering the TLR4 expression, the phenotype alteration, lipid accumulation in VSMCs, and Src kinase activation induced by oxLDL were abolished. After interfering Src activation, the oxLDL-induced lipid accumulation and foam cell phenotype in VSMCs were also alleviated. Furthermore, the ROS accumulation, upregulated Nox2 expression, downregulated Sirt1, Sirt3, and Mnsod expression in VSMCs under oxLDL stimulation were also relieved after the knockdown of Tlr4. Additionally, overexpression of Sirt1 and Sirt3 ameliorated the ROS accumulation and foam cell-like marker expression in VSMCs. These results demonstrated that beyond its familiar role in regulating inflammation response, Tlr4 is a critical regulator in oxLDL-induced foam cell formation in VSMCs via regulating Src kinase activation as well as Sirt1 and Sirt3 expression.

Association of carbamylated high-density lipoprotein with coronary artery disease in type 2 diabetes mellitus: carbamylated high-density lipoprotein of patients promotes monocyte adhesion.

BACKGROUND: Increasing evidence showed that carbamylated lipoprotein accelerated atherosclerosis. However, whether such modification of high-density lipoprotein (HDL) particles alters in type 2 diabetes mellitus (T2DM) patients and facilitates vascular complications remains unclear. We aimed to investigate the alteration of the carbamylation in HDL among T2DM patients and clarify its potential role in atherogenesis. METHODS: A total of 148 consecutive T2DM patients undergoning angiography and 40 age- and gender-matched control subjects were included. HDL was isolated from plasma samples, and the concentration of HDL carbamyl-lysine (HDL-CBL) was measured. Furthermore, the HDL from subjects and in-vitro carbamylated HDL (C-HDL) was incubated with endothelial cells and monocyte to endothelial cell adhesion. Adhesion molecule expression and signaling pathway were detected. RESULTS: Compared with the control group, the HDL-CBL level was remarkably increased in T2DM patients (6.13 ± 1.94 vs 12.00 ± 4.06 (ng/mg), P < 0.001). Of note, HDL-CBL demonstrated a more significant increase in T2DM patients with coronary artery disease (CAD) (n = 102) than those without CAD (n = 46) (12.75 ± 3.82 vs. 10.35 ± 4.11(ng/mg), P = 0.001). Multivariate logistic regression analysis demonstrated that higher HDL-CBL level was independently associated with a higher prevalence of CAD in diabetic patients after adjusting for established cofounders (adjusted odds ratio 1.174, 95% confidence Interval 1.045-1.319, p = 0.017). HDL from diabetic patients with CAD enhanced greater monocyte adhesion than that from the non-CAD or the control group (P < 0.001). Such pro-atherogenic capacity of diabetic HDL positively correlated with HDL-CBL level. Furthermore, in-vitro incubation of carbamylated HDL (C-HDL) with endothelial promoted monocyte to endothelial cell adhesion, induced upregulation of cell adhesion molecules expression, and activated NF-κB/p65 signaling in endothelial cells. Inhibiting carbamylation of HDL or NF-κB activation attenuated the monocyte to endothelial cell adhesion and cell surface adhesion molecules expression. CONCLUSIONS: Our study identified elevated carbamylation modification of HDL from T2DM patients, especially in those with concomitant CAD. We also evidenced that C-HDL enhanced monocyte to endothelial cell adhesion, indicating a potential pro-atherogenic role of C-HDL in atherosclerosis among T2DM patients. Trial registration https://register.clinicaltrials.gov , NCT04390711 Registered on 14 May 2020; Retrospectively registered.

Single-cell RNA Sequencing: In-depth Decoding of Heart Biology and Cardiovascular Diseases.

BACKGROUND: The cardiac system is a combination of a complex structure, various cells, and versatile specified functions and sophisticated regulatory mechanisms. Moreover, cardiac diseases that encompass a wide range of endogenous conditions, remain a serious health burden worldwide. Recent genome-wide profiling techniques have taken the lead in uncovering a new realm of cell types and molecular programs driving physiological and pathological processes in various organs and diseases. In particular, the emerging technique single-cell RNA sequencing dominates a breakthrough in decoding the cell heterogeneity, phenotype transition, and developmental dynamics in cardiovascular science. CONCLUSION: Herein, we review recent advances in single cellular studies of cardiovascular system and summarize new insights provided by single-cell RNA sequencing in heart developmental sciences, stem-cell researches as well as normal or disease-related working mechanisms.

The fate of the herbicide propanil in plants of the littoral zone of the Three Gorges Reservoir (TGR), China.

The anti-seasonal hydrology with 30m water fluctuations in the Three Gorges Reservoir (TGR) of China attracts growing environmental and ecological concerns. We investigated the biotransformation of the herbicide propanil in plants dominating in the littoral zone of the TGR by applying the 14C-ring-labeled herbicide into non-aseptic hydroponic plant systems (Cynodon dactylon, Nelumbo nucifera and Bidens pilosa), aseptic plants (Lemna minor and Lemna gibba) and cell suspension cultures (C. dactylon and L. minor). (1) Propanil absorbed in plants of the hydroponic systems was (12.46±1.63)% of applied radioactivity (AR) (C. dactylon), (52.36±6.38)% (N. nucifera) and (76.55±6.07)% (B. pilosa), respectively. The 14C-residues in the plant extractable fractions and the corresponding media were confirmed by radio-Thin Layer Chromatography (TLC), radio-High Performance Liquid Chromatography (HPLC) and Gas Chromatography-Electron Ionization Mass Spectrometry (GC-EIMS) as propanil, 3,4-dichloroaniline (DCA) and N-(3,4-dichlorophenyl)-ß-d-glucopyranosylamine (Glu-DCA). (2) About 8% of AR was taken up by both aseptic plants, from which 7.0% of AR was extracted and identified also as propanil, DCA and Glu-DCA. (3) Concerning cell suspension cultures, (39.22±9.39)% of AR was absorbed by C. dactylon after 72hr, whereas the accumulated 14C-propanil by L. minor cell suspension culture amounted to (65.04±1.72)% after 7days. The identified compounds in cell cultures are consistent with those in the tested plants. Most of the pesticide residues in the intact plants were un-extractable, which are recognized as the end of the detoxification process. We therefore consider these plants as suitable for the phytoremediation of the herbicide propanil in the TGR region.

Identification of Diagnostic Genes of Aortic Stenosis That Progresses from Aortic Valve Sclerosis.

Background: Aortic valve sclerosis (AVS) is a pathological state that can progress to aortic stenosis (AS), which is a high-mortality valvular disease. However, effective medical therapies are not available to prevent this progression. This study aimed to explore potential biomarkers of AVS-AS advancement. Methods: A microarray dataset and an RNA-sequencing dataset were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened from AS and AVS samples. Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning model construction were conducted to identify diagnostic genes. A receiver operating characteristic (ROC) curve was generated to evaluate diagnostic value. Immune cell infiltration was then used to analyze differences in immune cell proportion between tissues. Finally, immunohistochemistry was applied to further verify protein concentration of diagnostic factors. Results: A total of 330 DEGs were identified, including 92 downregulated and 238 upregulated genes. The top 5% of DEGs (n = 17) were screened following construction of a PPI network. IL-7 and VCAM-1 were identified as the most significant candidate genes via least absolute shrinkage and selection operator (LASSO) regression. The diagnostic value of the model and each gene were above 0.75. Proportion of anti-inflammatory M2 macrophages was lower, but the fraction of pro-inflammatory gamma-delta T cells was elevated in AS samples. Finally, levels of IL-7 and VCAM-1 were validated to be higher in AS tissue than in AVS tissue using immunohistochemistry. Conclusion: IL-7 and VCAM-1 were identified as biomarkers during the disease progression. This is the first study to analyze gene expression differences between AVS and AS and could open novel sights for future studies on alleviating or preventing the disease progression.

Genetically predicted systemic inflammation and the risk of atrial fibrillation: A bidirectional two-sample Mendelian randomization study.

Background: Systemic inflammation has been proposed to be associated with the incidence of atrial fibrillation (AF), but whether it is a cause or a consequence of AF remains uncertain. We sought to explore the causal associations between systemic inflammation and AF using bidirectional Mendelian randomization (MR) analysis. Methods: Independent genetic variants strongly associated with AF were selected as instrumental variables from the largest genome-wide association study (GWAS) with up to 1,030,836 individuals. Regarding inflammation traits, genetic associations with 41 inflammatory cytokines and 5 inflammatory biomarkers were obtained from their corresponding GWASs databases. Effect estimates were primarily evaluated using the inverse-variance weighted (IVW) method, supplemented by sensitivity analyses using MR-Egger, weighted median, and MR-PRESSO methods. Results: In our initial MR analyses, we observed suggestive associations of genetically predicted interleukin-17 (IL-17), interleukin-2 receptor subunit alpha (IL-2rα), and procalcitonin (PCT) with AF. One standard deviation (SD) increase in IL-17, IL-2rα, and PCT caused an increase in AF risk by 6.3 % (OR 1.063, 95 %CI 1.011---1.118, p = 0.018), 4.9 % (OR 1.049, 95 %CI 1.007---1.094, p = 0.023) and 3.4 % (OR 1.034, 95 %CI 1.005---1.064, p = 0.022), respectively. Furthermore, our reverse MR analyses indicated that genetically predicted AF contributed to a suggestive increase in the levels of macrophage inflammatory protein-1ß (MIP1ß) (ß 0.055, 95 %CI 0.006 to 0.103, p = 0.028), while a decrease in the levels of fibrinogen (Fbg) (ß -0.091, 95 %CI -0.140 to -0.041, p < 0.001), which remained significant after multiple test correction. Conclusions: Our MR study identified several inflammatory biomarkers with suggestive causal associations regarding the upstream and downstream regulation of AF occurrence, offering new insights for therapeutic exploitation of AF. Further research is required to validate the underlying link between systemic inflammation and AF in larger cohorts.

Development and Validation of a Novel Predictive Model for the Early Differentiation of Cardiac and Non-Cardiac Syncope.

Background: The diagnosis of cardiac syncope remains a challenge. This study sought to develop and validate a diagnostic model for the early identification of individuals likely to have a cardiac cause. Methods: 877 syncope patients with a determined cause were retrospectively enrolled at a tertiary heart center. They were randomly divided into the training set and validation set at a 7:3 ratio. We analyzed the demographic information, medical history, laboratory tests, electrocardiogram, and echocardiogram by the least absolute shrinkage and selection operator (LASSO) regression for selection of key features. Then a multivariable logistic regression analysis was performed to identify independent predictors and construct a diagnostic model. The receiver operating characteristic curves, area under the curve (AUC), calibration curves, and decision curve analysis were used to evaluate the predictive accuracy and clinical value of this nomogram. Results: Five independent predictors for cardiac syncope were selected: BMI (OR 1.088; 95% CI 1.022-1.158; P =0.008), chest symptoms preceding syncope (OR 5.251; 95% CI 3.326-8.288; P <0.001), logarithmic NT-proBNP (OR 1.463; 95% CI 1.240-1.727; P <0.001), left ventricular ejection fraction (OR 0.940; 95% CI 0.908-0.973; P <0.001), and abnormal electrocardiogram (OR 6.171; 95% CI 3.966-9.600; P <0.001). Subsequently, a nomogram based on a multivariate logistic regression model was developed and validated, yielding AUC of 0.873 (95% CI 0.845-0.902) and 0.856 (95% CI 0.809-0.903), respectively. The calibration curves showcased the nomogram's reasonable calibration, and the decision curve analysis demonstrated good clinical utility. Conclusion: A diagnostic tool providing individualized probability predictions for cardiac syncope was developed and validated, which may potentially serve as an effective tool to facilitate early identification of such patients.

Inclusion of reeling wastewater-derived sericin peptides in high-protein nutrition bars for antihardening and storage stability.

The utilization of agroindustrial wastes to enrich food protein resources and the exploration of their broader applications are crucial for addressing the food crisis and achieving sustainable development goals. In this study, reeling wastewater-derived sericin was hydrolyzed using papain and trypsin to prepare sericin peptide (SRP) and was used as an antihardening ingredient of high-protein nutrition bars (HPNBs). The mechanism of the antihardening effect of SRP was elucidated by investigating the content of advanced glycation end products and protein oxidation products (carbonyl and free sulfhydryl), and the molecular weight change of HPNBs during storage before and after the addition of SRP. Our results confirmed the fortification of HPNBs with SRP, which is beneficial for the promotion and expansion of sericin applications in the food industry, with positive implications for the rational utilization of protein resources and the enrichment of food protein sources.

3,3',5-Triiodothyroacetic Acid Transporters.

Introduction: Thyroid hormone transporters are essential for thyroid hormones to enter target cells. Monocarboxylate transporter (MCT) 8 is a key transporter and is expressed at the blood-brain barrier (BBB), in neural cells and many other tissues. Patients with MCT8 deficiency have severe neurodevelopmental delays because of cerebral hypothyroidism and chronic sequelae of peripheral thyrotoxicosis. The T3 analog 3,3',5-triiodothyroacetic acid (TRIAC) rescued neurodevelopmental features in animal models mimicking MCT8 deficiency and improved key metabolic features in patients with MCT8 deficiency. However, the identity of the transporter(s) that facilitate TRIAC transport are unknown. Here, we screened candidate transporters that are expressed at the human BBB and/or brain-cerebrospinal fluid barrier and known thyroid hormone transporters for TRIAC transport. Materials and Methods: Plasma membrane expression was determined by cell surface biotinylation assays. Intracellular accumulation of 1 nM TRIAC was assessed in COS-1 cells expressing candidate transporters in Dulbecco's phosphate-buffered saline (DPBS)/0.1% glucose or Dulbecco's modified Eagle's medium (DMEM) with or without 0.1% bovine serum albumin (BSA). Expression of Slc22a8 was determined by fluorescent in situ hybridization in brain sections from wild-type and Mct8/Oatp1c1 knockout mice at postnatal days 12, 21, and 120. Results: In total, 59 plasma membrane transporters were selected for screening of TRIAC accumulation (n = 40 based on expression at the human BBB and/or brain-cerebrospinal fluid barrier and having small organic molecules as substrates; n = 19 known thyroid hormone transporters). Screening of the selected transporter panel showed that 18 transporters facilitated significant intracellular accumulation of TRIAC in DPBS/0.1% glucose or DMEM in the absence of BSA. In the presence of BSA, substantial transport was noted for SLCO1B1 and SLC22A8 (in DPBS/0.1% glucose and DMEM) and SLC10A1, SLC22A6, and SLC22A24 (in DMEM). The zebrafish and mouse orthologs of these transporters similarly facilitated intracellular accumulation of TRIAC. Highest Slc22a8 mRNA expression was detected in mouse brain capillary endothelial cells and choroid plexus epithelial cells at early postnatal time points, but was reduced at P120. Conclusions: Human SLC10A1, SLCO1B1, SLC22A6, SLC22A8, and SLC22A24 as well as their mouse and zebrafish orthologs are efficient TRIAC transporters. These findings contribute to the understanding of TRIAC treatment in patients with MCT8 deficiency and animal models thereof.

A Comparison of the Association of Septal Scar Burden on Responses to LBBAP-CRT and BVP-CRT.

BACKGROUND: Left bundle branch area pacing (LBBAP) is an alternative to biventricular pacing (BVP) for cardiac resynchronization therapy (CRT). However, despite the presence of left bundle branch block, whether cardiac substrate may influence the effect between the 2 strategies is unclear. OBJECTIVES: This study aims to assess the association of septal scar on reverse remodeling and clinical outcomes of LBBAP compared with BVP. METHODS: We analyzed patients with nonischemic cardiomyopathy who had CRT indications undergoing preprocedure cardiac magnetic resonance examination. Changes in left ventricular ejection fraction (LVEF) and echocardiographic response (ER, ≥5% absolute LVEF increase) were assessed at 6 months. The clinical outcome was the composite of all-cause mortality, heart failure hospitalization, or major ventricular arrhythmia. RESULTS: There were 147 patients included (51 LBBAP and 96 BVP). Among patients with low septal scar burden (below median 5.7%, range: 0 to 5.3%), LVEF improvement was higher in the LBBAP than the BVP group (17.5% ± 10.9% vs 12.3% ± 11.8%; P = 0.037), with more than 3-fold increased odds of ER (odds ratio: 4.35; P = 0.033). In high sepal scar subgroups (≥5.7%, range: 5.7% to 65.9%), BVP trended towards higher LVEF improvement (9.2% ± 9.4% vs 6.4% ± 12.4%; P = 0.085). Interaction between septal scar burden and pacing strategy was significant for ER (P = 0.002) and LVEF improvement (P = 0.011) after propensity score adjustment. During median follow-up of 33.7 (Q1-Q3: 19.8 to 42.1) months, the composite clinical outcome occurred in 34.7% (n = 51) of patients. The high-burden subgroups had worse clinical outcomes independent of CRT method. CONCLUSIONS: Remodeling response to LBBAP and BVP among nonischemic cardiomyopathy patients is modified by septal scar burden. High septal scar burden was associated with poor clinical prognosis independent of CRT methods.

CMR feature tracking-based left atrial mechanics predicts response to cardiac resynchronization therapy and adverse outcomes.

BACKGROUND: Cardiac resynchronization therapy (CRT) is an established therapy for advanced heart failure (HF) with prolonged QRS duration. However, 30% of patients have shown no benefit from the treatment. OBJECTIVE: This study aimed to examine the value of left atrial (LA) mechanics by cardiac magnetic resonance (CMR) to predict response to CRT and clinical outcomes. METHODS: A total of 163 CRT recipients with preimplantation CMR examination were retrospectively recruited. CMR feature tracking was used to evaluate LA size and function. The end points include (1) improvement of at least 5% in left ventricular ejection fraction combined with a reduction of at least 1 New York Heart Association functional class at 6-month follow-up and (2) any all-cause death or HF hospitalization during follow-up. RESULTS: Overall, 82 (50.3%) were CRT responders. CRT nonresponders had larger LA and worse LA reservoir and booster pump function than did responders (P < .001 for all). LA structural (maximum volume index < 47 mL/m2) and functional (booster pump strain > 8.5%) criteria were incremental to traditional indicators in detecting CRT response (χ2, 40.83 vs 9.98; P < .001). During follow-up (median 41 months), survival free from death or HF hospitalization increased with the number of positive LA criteria (log-rank, P < .001). After adjustment for clinical confounders, the absence of the 2 criteria remained associated with a considerably increased risk of death or HF hospitalization (adjusted hazard ratio 6.2; 95% confidence interval 2.15-17.88; P = .001). CONCLUSION: The preprocedure LA mechanics evaluated using CMR may be useful to predict response to CRT and improve risk stratification in CRT recipients.

Statins Prevent the Deleterious Consequences of Placental Chemerin Upregulation in Preeclampsia.

BACKGROUND: Chemerin, an inflammatory adipokine, is upregulated in preeclampsia, and its placental overexpression results in preeclampsia-like symptoms in mice. Statins may lower chemerin. METHODS: Chemerin was determined in a prospective cohort study in women suspected of preeclampsia and evaluated as a predictor versus the sFlt-1 (soluble fms-like tyrosine kinase-1)/PlGF (placental growth factor) ratio. Chemerin release was studied in perfused placentas and placental explants with or without the statins pravastatin and fluvastatin. We also addressed statin placental passage and the effects of chemerin in chorionic plate arteries. RESULTS: Serum chemerin was elevated in women with preeclampsia, and its addition to a predictive model yielded significant effects on top of the sFlt-1/PlGF ratio to predict preeclampsia and its fetal complications. Perfused placentas and explants of preeclamptic women released more chemerin and sFlt-1 and less PlGF than those of healthy pregnant women. Statins reversed this. Both statins entered the fetal compartment, and the fetal/maternal concentration ratio of pravastatin was twice that of fluvastatin. Chemerin constricted plate arteries, and this was blocked by a chemerin receptor antagonist and pravastatin. Chemerin did not potentiate endothelin-1 in chorionic plate arteries. In explants, statins upregulated low-density lipoprotein receptor expression, which relies on the same transcription factor as chemerin, and NO release. CONCLUSIONS: Chemerin is a biomarker for preeclampsia, and statins both prevent its placental upregulation and effects, in an NO and low-density lipoprotein receptor-dependent manner. Combined with their capacity to improve the sFlt-1/PlGF ratio, this offers an attractive mechanism by which statins may prevent or treat preeclampsia.

MultiSimNeNc: A network representation learning-based module identification method by network embedding and clustering.

Accurate identification of gene modules based on biological networks is an effective approach to understanding gene patterns of cancer from a module-level perspective. However, most graph clustering algorithms just consider low-order topological connectivity, which limits their accuracy in gene module identification. In this study, we propose a novel network-based method, MultiSimNeNc, to identify modules in various types of networks by integrating network representation learning (NRL) and clustering algorithms. In this method, we first obtain the multi-order similarity of the network using graph convolution (GC). Then, we aggregate the multi-order similarity to characterize the network structure and use non-negative matrix factorization (NMF) to achieve low-dimensional node characterization. Finally, we predict the number of modules based on the bayesian information criterion (BIC) and use the gaussian mixture model (GMM) to identify modules. To testify to the efficacy of MultiSimeNc in module identification, we apply this method to two types of biological networks and six benchmark networks, where the biological networks are constructed based on the fusion of multi-omics data from glioblastoma (GBM). The analysis shows that MultiSimNeNc outperforms several state-of-the-art module identification algorithms in identification accuracy, which is an effective method for understanding biomolecular mechanisms of pathogenesis from a module-level perspective.