Tongue coating-dependent superior temporal sulcus remodeling in amnestic mild cognitive impairment.

Tongue coating affects cognition, and cognitive decline at early stage also showed relations to functional and structural remodeling of superior temporal sulcus (STS) in amnestic mild cognitive impairment (aMCI). The potential correlation between disparate cognitive manifestations in aMCI patients with different tongue coatings, and corresponding mechanisms of STS remodeling remains uncharted. In this case-control study, aMCI patients were divided into thin coating (n = 18) and thick coating (n = 21) groups. All participants underwent neuropsychological evaluations and multimodal magnetic resonance imaging. Group comparisons were conducted in clinical assessments and neuroimaging measures of banks of the STS (bankssts). Generalized linear models were constructed to explore relationships between neuroimaging measures and cognition. aMCI patients in the thick coating group exhibited significantly poorer immediate and delayed recall and slower information processing speed (IPS) (P < 0.05), and decreased functional connectivity (FC) of bilateral bankssts with frontoparietal cortices (P < 0.05, AlphaSim corrected) compared to the thin coating group. It was found notable correlations between cognition encompassing recall and IPS, and FC of bilateral bankssts with frontoparietal cortices (P < 0.05, Bonferroni's correction), as well as interaction effects of group × regional homogeneity (ReHo) of right bankssts on the first immediate recall (P < 0.05, Bonferroni's correction). aMCI patients with thick coating exhibited poor cognitive performance, which might be attributed to decreased FC seeding from bankssts. Our findings strengthen the understanding of brain reorganization of STS via which tongue coating status impacts cognition in patients with aMCI.

CT texture analysis of vertebrobasilar artery calcification to identify culprit plaques.

Objectives: The aim of this study was to extract radiomic features from vertebrobasilar artery calcification (VBAC) on head computed tomography (CT) images and investigate its diagnostic performance to identify culprit lesions responsible for acute cerebral infarctions. Methods: Patients with intracranial atherosclerotic disease who underwent vessel wall MRI (VW-MRI) and head CT examinations from a single center were retrospectively assessed for VBAC visual and textural analyses. Each calcified plaque was classified by the likelihood of having caused an acute cerebral infarction identified on VW-MRI as culprit or non-culprit. A predefined set of texture features extracted from VBAC segmentation was assessed using the minimum redundancy and maximum relevance method. Five key features were selected to integrate as a radiomic model using logistic regression by the Aikaike Information Criteria. The diagnostic value of the radiomic model was calculated for discriminating culprit lesions over VBAC visual assessments. Results: A total of 1,218 radiomic features were extracted from 39 culprit and 50 non-culprit plaques, respectively. In the VBAC visual assessment, culprit plaques demonstrated more observed presence of multiple calcifications, spotty calcification, and intimal predominant calcification than non-culprit lesions (all p < 0.05). In the VBAC texture analysis, 55 (4.5%) of all extracted features were significantly different between culprit and non-culprit plaques (all p < 0.05). The radiomic model incorporating 5 selected features outperformed multiple calcifications [AUC = 0.81 with 95% confidence interval (CI) of 0.72, 0.90 vs. AUC = 0.61 with 95% CI of 0.49, 0.73; p = 0.001], intimal predominant calcification (AUC = 0.67 with 95% CI of 0.58, 0.76; p = 0.04) and spotty calcification (AUC = 0.62 with 95% CI of 0.52, 0.72; p = 0.005) in the identification of culprit lesions. Conclusion: Culprit plaques in the vertebrobasilar artery exhibit distinct calcification radiomic features compared to non-culprit plaques. CT texture analysis of VBAC has potential value in identifying lesions responsible for acute cerebral infarctions, which may be helpful for stroke risk stratification in clinical practice.

Chitosan Oligosaccharides Mitigate Flooding Stress Damage in Rice by Affecting Antioxidants, Osmoregulation, and Hormones.

Rice (Oryza sativa L.) is one of the most important food crops worldwide. However, during direct seeding, rice is extremely vulnerable to flooding stress, which impairs rice's emergence and seedling growth and results in a significant yield loss. According to our research, chitosan oligosaccharides have the potential to be a chemical seed-soaking agent that greatly increases rice's resistance to flooding. Chitosan oligosaccharides were able to enhance seed energy supply, osmoregulation, and antioxidant capacity, according to physiological index assessments. Using transcriptome and metabolomic analysis, we discovered that important differential metabolites and genes were involved in the signaling pathway for hormone synthesis and antioxidant capacity. Exogenous chitosan oligosaccharides specifically and significantly inhibit genes linked to auxin, jasmonic acid, and abscisic acid. This suggested that applying chitosan oligosaccharides could stabilize seedling growth and development by controlling associated hormones and reducing flooding stress by enhancing membrane stability and antioxidant capacity. Finally, we verified the effectiveness of exogenous chitosan oligosaccharides imbibed in seeds by field validation, demonstrating that they can enhance rice seedling emergence and growth under flooding stress.

Dicliptera chinensis-derived polysaccharide enhanced the growth activity of submandibular gland cells in vitro after radiotherapy.

Objective: Radiotherapy for head and neck can damage the salivary gland cells, which can easily result in xerostomia. No effective treatment for radiation-induced salivary gland dysfunction currently exists. Thus, we aimed to study the protective effect of Dicliptera chinensis polysaccharides (DCP) on the prevention of submandibular gland (SMG) cell damage caused by radiotherapy in Sprague-Dawley rats. Design: Mechanical enzyme digestion was used to extract primary rat SMG cells. A radiation injury model was established by treating these cells with a dose of 8 Gy, followed by intervention using different DCP concentrations. The cell counting kit 8 assay was used to determine the inhibition rate of SMG cells in each group. The rates of apoptosis and cell cycle progression were detected using flow cytometry. Expression of the Mre11/Rad50/Nbs1 complex (MRN) was detected using western blotting. Results: DCP increased the proliferation of SMG cells after irradiation, and cell growth activity positively correlated with polysaccharide concentration. Flow cytometry analysis of SMG cell apoptosis revealed that DCP markedly reduced the total apoptosis rate after irradiation, especially the early apoptosis rate. Cell cycle results suggested that DCP reduced the number of cells in the S and G2 phases after irradiation and alleviated the S and G2 blocks. Western blot results indicated that the expression of Mre11, Rad50, and Nbs1 decreased in the radiation-injured group, whereas their expression increased after DCP treatment. Conclusions: DCP can protect the rat SMG cells after radiation and be used as a protective agent against salivary gland cell damage caused by radiotherapy.

Total paeony glycoside relieves neuroinflammation to exert antidepressant effect via the interplay between NLRP3 inflammasome, pyroptosis and autophagy.

BACKGROUND: Depression is a common mental illness characterised by abnormal and depressed emotions. Total paeony glycoside (TPG) is a naturally active saponin extracted from the traditional Chinese medicine Radix Paeoniae rubra. However, the antidepressant and neuroinflammatory effects of TPG have not been thoroughly studied. PURPOSE: To study the therapeutic potential of TGP in depression caused by neuronal injury and neuroinflammation and to explore the mechanism of TGP and the relationship between the NLRP3 inflammasome, pyroptosis, and autophagy. STUDY DESIGN: A chronic unpredictable mild stress (CUMS)-induced depression model and a cell model of corticosterone (CORT)-induced hippocampal neuron injury were established to evaluate the therapeutic effects of TPG. METHODS: The composition of TPG was analysed using high-performance liquid chromatography and mass spectrometry. The effects of TPG and fluoxetine on depression-like behaviour, neuronal injury, neuroinflammation, pyroptosis, and mitochondrial autophagy in the mice models were evaluated. RESULTS: TGP alleviated depression-like behaviours in mice and inhibited hippocampal neuronal apoptosis. The secretion of inflammatory cytokines was significantly reduced in CORT-induced hippocampal neuron cells and in the serum of a mouse model of CUMS-induced depression. In addition, TGP treatment reduced the levels of NLRP3 family pyrin structural domains, including NLRP3, pro-caspase-1, caspase-1, and IL-1ß, and the pyroptosis related proteins such as GSDMD-N. Importantly, TPG attenuated mitochondrial dysfunction, promoted the clearance of damaged mitochondria, and the activation of mitochondrial autophagy, which reduced ROS accumulation and NLRP3 inflammasome activation. An in-depth study observed that the regulatory effect of TPG on autophagy was attenuated by the autophagy inhibitor 3-methyladenine (3-MA) in vitro and in vivo. However, administration of the caspase-1 inhibitor Belnacasan (VX-765) successfully inhibited pyroptosis and showed a synergistic therapeutic effect with TPG. CONCLUSION: These results indicate that TPG can repair neuronal damage by activating autophagy, restoring mitochondrial function, and reducing inflammation-mediated pyroptosis, thereby playing an important role in the alleviation of neuroinflammation and depression. This study suggests new potential drugs and treatment strategies for neuroinflammation-related diseases and depression.

Effect of silencing SSB1 gene on the expression of NBS1 in irradiated rat submandibular gland cells.

The salivary gland (SGS) is a kind of organ vulnerable to ionizing radiation. Radiotherapy is an important treatment for head and neck tumors, but in the process of radiotherapy, tumor cells will be injured by radiation to a certain extent. Infrared-induced DNA double-strand break (IR-DSBs) is one of the most serious DNA damage. DNA repair proteins such as Nymegan rupture syndrome protein 1 (NBS1) play a key role in the identification and repair of DNA damage. but the interaction between SSB1 and NBS1 has not been elucidated. In this study, we irradiated rat submandibular gland (SMG) cells, which were either infected with a rAdE5-SSB1-1p2-shRNA recombinant adenovirus to silence SSB or a control virus, to explore the effect of IR on the expression NBS1 in the absence of SSB. Our results showed that the SSB1 mRNA transcripts and protein expression of SSB1 and NBS1 initially increased and decreased later with increased doses. The relative expression reached the highest levels when the SMG cells were irradiated with 2Gy of IR. Silencing the SSB1 gene suppressed the expression of both SSB1 and NBS1 regardless of irradiation. The expression of NBS1 decreased when the SSB1 gene was silenced. We concluded that IR affected the expression of both SSB1 and NBS1 and there is a synergistic effect on IR-induced NBS1 suppression and DSBs repair in SMG cells. These observations shed light on further investigation and elucidation of IR-caused DNA repair mechanisms.

SEGCN: a subgraph encoding based graph convolutional network model for social bot detection.

Message passing neural networks such as graph convolutional networks (GCN) can jointly consider various types of features for social bot detection. However, the expressive power of GCN is upper-bounded by the 1st-order Weisfeiler-Leman isomorphism test, which limits the detection performance for the social bots. In this paper, we propose a subgraph encoding based GCN model, SEGCN, with stronger expressive power for social bot detection. Each node representation of this model is computed as the encoding of a surrounding induced subgraph rather than encoding of immediate neighbors only. Extensive experimental results on two publicly available datasets, Twibot-20 and Twibot-22, showed that the proposed model improves the accuracy of the state-of-the-art social bot detection models by around 2.4%, 3.1%, respectively.

Inhaled RNA drugs to treat lung diseases: Disease-related cells and nano-bio interactions.

In recent years, RNA-based therapies have gained much attention as biomedicines due to their remarkable therapeutic effects with high specificity and potency. Lung diseases offer a variety of currently undruggable but attractive targets that could potentially be treated with RNA drugs. Inhaled RNA drugs for the treatment of lung diseases, including asthma, chronic obstructive pulmonary disease, cystic fibrosis, and acute respiratory distress syndrome, have attracted more and more attention. A variety of novel nanoformulations have been designed and attempted for the delivery of RNA drugs to the lung via inhalation. However, the delivery of RNA drugs via inhalation poses several challenges. It includes protection of the stability of RNA molecules, overcoming biological barriers such as mucus and cell membrane to the delivery of RNA molecules to the targeted cytoplasm, escaping endosomal entrapment, and circumventing unwanted immune response etc. To address these challenges, ongoing researches focus on developing innovative nanoparticles to enhance the stability of RNA molecules, improve cellular targeting, enhance cellular uptake and endosomal escape to achieve precise delivery of RNA drugs to the intended lung cells while avoiding unwanted nano-bio interactions and off-target effects. The present review first addresses the pathologic hallmarks of different lung diseases, disease-related cell types in the lung, and promising therapeutic targets in these lung cells. Subsequently we highlight the importance of the nano-bio interactions in the lung that need to be addressed to realize disease-related cell-specific delivery of inhaled RNA drugs. This is followed by a review on the physical and chemical characteristics of inhaled nanoformulations that influence the nano-bio interactions with a focus on surface functionalization. Finally, the challenges in the development of inhaled nanomedicines and some key aspects that need to be considered in the development of future inhaled RNA drugs are discussed.

Effects of atorvastatin and rosuvastatin on dysfunctional coronary circulation in patients with ST-segment elevation myocardial infarction.

OBJECTIVE: Evidence of therapy for dysfunctional coronary circulation in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (pPCI) is limited. This study was performed to compare the effects of atorvastatin and rosuvastatin on dysfunctional coronary circulation. METHODS: This retrospective study enrolled 597 consecutive patients with STEMI who underwent pPCI in 3 centers from June 2016 to December 2019. Dysfunctional coronary circulation was defined by the thrombolysis in myocardial infarction (TIMI) grade and the TIMI myocardial perfusion grade (TMPG). Logistic regression analysis was used to evaluate the impact of different statin types on dysfunctional coronary circulation. RESULTS: The incidence of TIMI no/slow reflow did not differ between the two groups, but the incidence of TMPG no/slow reflow was significantly lower in the atorvastatin than rosuvastatin group (44.58% vs. 57.69%, respectively). After multivariate adjustment, the odds ratio with 95% confidence interval of rosuvastatin was 1.72 (1.17-2.52) for after pretreatment TMPG no/slow reflow and 1.73 (1.16-2.58) for after stenting TMPG no/slow reflow. Atorvastatin and rosuvastatin showed no significant differences in clinical outcomes during hospitalization. CONCLUSIONS: Compared with rosuvastatin, atorvastatin was associated with better coronary microcirculatory perfusion in patients with STEMI who underwent pPCI.

A virtual-pinhole PET device for improving contrast recovery and enhancing lesion detectability of a one-meter-long PET scanner: a simulation study.

This paper presents a simulation study to demonstrate that the contrast recovery coefficients (CRC) and detectability of small lesions of a one-meter-long positron emission tomography (PET) scanner can be further enhanced by the integration of high resolution virtual-pinhole (VP) PET devices. The scanner under investigation is a Siemens Biograph Vision Quadra which has an axial field-of-view (FOV) of 106 cm. The VP-PET devices contain two high-resolution flat panel detectors, each composed of 2 × 8 detector modules each of which consists of 32 × 64 lutetium-oxyorthosilicate crystals (1.0 × 1.0 × 10.0 mm3each). Two configurations for the VP-PET device placement were evaluated: (1) place the two flat-panel detectors at the center of the scanner's axial FOV below the patient bed; (2) place one flat-panel detector at the center of the first and the last quarter of the scanner's axial FOV below the patient bed. Sensitivity profiles were measured by moving a point22Na source stepwise across the scanner's FOV axially at different locations. To assess the improvement in CRC and lesion detectability by the VP-PET devices, an elliptical torso phantom (31.6 × 22.8 × 106 cm3) was first imaged by the native scanner then subsequently by the two VP-PET geometry configurations. Spherical lesions (4 mm in diameter) having 5:1 lesion-to-background radioactivity concentration ratio were grouped and placed at nine regions in the phantom to analyze the dependence of the improvement in plane. Average CRCs and their standard deviations of the 7 tumors in each group were computed and the receiver operating characteristic (ROC) curves were drawn to evaluate the improvement in lesion detectability by the VP-PET device over the native long axial PET scanner. The fraction of coincidence events between the inserts and the scanner detectors was 13%-16% (out of the total number of coincidences) for VP-PET configuration 1 and 2, respectively. The VP-PET systems provide higher CRCs for lesions in all regions in the torso, with more significant enhancement at regions closer to the inserts, than the native scanner does. For any given false positive fraction, the VP-PET systems offer higher true positive fraction compared to the native scanner. This work provides a potential solution to further enhance the image resolution of a long axial FOV PET scanner to maximize its lesion detectability afforded by its super high effective sensitivity.

Airway epithelial cell-specific delivery of lipid nanoparticles loading siRNA for asthma treatment.

With specific and inherent mRNA cleaving activity, small interfering RNA (siRNA) has been deemed promising therapeutics to reduce the exacerbation rate of asthma by inhibiting the expression and release of proinflammatory cytokines from airway epithelial cells (AECs). To exert the therapeutic effects of siRNA drugs, nano-formulations with high efficiency and safety are required to deliver these nucleic acids to the target cells. Herein, we exploited novel inhaled lipid nanoparticles (LNPs) targeting intercellular adhesion molecule-1 (ICAM-1) receptors on the apical side of AECs. This delivery system is meant to enhance the specific delivery efficiency of siRNA in AECs to prevent the expression of proinflammatory cytokines in AECs and the concomitant symptoms in parallel. A cyclic peptide that resembles part of the capsid protein of rhinovirus and binds to ICAM-1 receptors was initially conjugated with cholesterol and subsequently assembled with ionizable cationic lipids to form the LNPs (Pep-LNPs) loaded with siRNA against thymic stromal lymphopoietin (TSLP siRNA). The obtained Pep-LNPs were subjected to thorough characterization and evaluations in vitro and in vivo. Pep-LNPs significantly enhanced cellular uptake and gene silencing efficiency in human epithelial cells expressing ICAM-1 in vitro, exhibited AEC-specific delivery and improved the gene silencing effect in ovalbumin-challenged asthmatic mice after pulmonary administration. More importantly, Pep-LNPs remarkably downregulated the expression of TSLP in AECs, effectively alleviated inflammatory cell infiltration, and reduced the secretion of other proinflammatory cytokines, including IL-4 and IL-13, as well as mucus production in asthmatic mice. This study demonstrates that Pep-LNPs are safe and efficient to deliver siRNA drugs to asthmatic AECs and could potentially alleviate allergic asthma by inhibiting the overexpression of proinflammatory cytokines in the airway.

Towards artificial general intelligence via a multimodal foundation model.

The fundamental goal of artificial intelligence (AI) is to mimic the core cognitive activities of human. Despite tremendous success in the AI research, most of existing methods have only single-cognitive ability. To overcome this limitation and take a solid step towards artificial general intelligence (AGI), we develop a foundation model pre-trained with huge multimodal data, which can be quickly adapted for various downstream cognitive tasks. To achieve this goal, we propose to pre-train our foundation model by self-supervised learning with weak semantic correlation data crawled from the Internet and show that promising results can be obtained on a wide range of downstream tasks. Particularly, with the developed model-interpretability tools, we demonstrate that strong imagination ability is now possessed by our foundation model. We believe that our work makes a transformative stride towards AGI, from our common practice of "weak or narrow AI" to that of "strong or generalized AI".

MHCRoBERTa: pan-specific peptide-MHC class I binding prediction through transfer learning with label-agnostic protein sequences.

Predicting the binding of peptide and major histocompatibility complex (MHC) plays a vital role in immunotherapy for cancer. The success of Alphafold of applying natural language processing (NLP) algorithms in protein secondary struction prediction has inspired us to explore the possibility of NLP methods in predicting peptide-MHC class I binding. Based on the above motivations, we propose the MHCRoBERTa method, RoBERTa pre-training approach, for predicting the binding affinity between type I MHC and peptides. Analysis of the results on benchmark dataset demonstrates that MHCRoBERTa can outperform other state-of-art prediction methods with an increase of the Spearman rank correlation coefficient (SRCC) value. Notably, our model gave a significant improvement on IC50 value. Our method has achieved SRCC value and AUC value as 0.785 and 0.817, respectively. Our SRCC value is 14.3% higher than NetMHCpan3.0 (the second highest SRCC value on pan-specific) and is 3% higher than MHCflurry (the second highest SRCC value on all methods). The AUC value is also better than any other pan-specific methods. Moreover, we visualize the multi-head self-attention for the token representation across the layers and heads by this method. Through the analysis of the representation of each layer and head, we can show whether the model has learned the syntax and semantics necessary to perform the prediction task well. All these results demonstrate that our model can accurately predict the peptide-MHC class I binding affinity and that MHCRoBERTa is a powerful tool for screening potential neoantigens for cancer immunotherapy. MHCRoBERTa is available as an open source software at github (https://github.com/FuxuWang/MHCRoBERTa).

Breast carcinoma-amplified sequence 2 regulates adult neurogenesis via ß-catenin.

BACKGROUND: Breast carcinoma-amplified sequence 2 (BCAS2) regulates ß-catenin gene splicing. The conditional knockout of BCAS2 expression in the forebrain (BCAS2 cKO) of mice confers impaired learning and memory along with decreased ß-catenin expression. Because ß-catenin reportedly regulates adult neurogenesis, we wondered whether BCAS2 could regulate adult neurogenesis via ß-catenin. METHODS: BCAS2-regulating neurogenesis was investigated by characterizing BCAS2 cKO mice. Also, lentivirus-shBCAS2 was intracranially injected into the hippocampus of wild-type mice to knock down BCAS2 expression. We evaluated the rescue effects of BCAS2 cKO by intracranial injection of adeno-associated virus encoding BCAS2 (AAV-DJ8-BCAS2) and AAV-ß-catenin gene therapy. RESULTS: To show that BCAS2-regulating adult neurogenesis via ß-catenin, first, BCAS2 cKO mice showed low SRY-box 2-positive (Sox2+) neural stem cell proliferation and doublecortin-positive (DCX+) immature neurons. Second, stereotaxic intracranial injection of lentivirus-shBCAS2 knocked down BCAS2 in the hippocampus of wild-type mice, and we confirmed the BCAS2 regulation of adult neurogenesis via ß-catenin. Third, AAV-DJ8-BCAS2 gene therapy in BCAS2 cKO mice reversed the low proliferation of Sox2+ neural stem cells and the decreased number of DCX+ immature neurons with increased ß-catenin expression. Moreover, AAV-ß-catenin gene therapy restored neuron stem cell proliferation and immature neuron differentiation, which further supports BCAS2-regulating adult neurogenesis via ß-catenin. In addition, cells targeted by AAV-DJ8 injection into the hippocampus included Sox2 and DCX immature neurons, interneurons, and astrocytes. BCAS2 may regulate adult neurogenesis by targeting Sox2+ and DCX+ immature neurons for autocrine effects and interneurons or astrocytes for paracrine effects. CONCLUSIONS: BCAS2 can regulate adult neurogenesis in mice via ß-catenin.

Rheumatoid Arthritis and Cardio-Cerebrovascular Disease: A Mendelian Randomization Study.

Significant genetic association exists between rheumatoid arthritis (RA) and cardiovascular disease. The associated mechanisms include common inflammatory mediators, changes in lipoprotein composition and function, immune responses, etc. However, the causality of RA and vascular/heart problems remains unknown. Herein, we performed Mendelian randomization (MR) analysis using a large-scale RA genome-wide association study (GWAS) dataset (462,933 cases and 457,732 controls) and six cardio-cerebrovascular disease GWAS datasets, including age angina (461,880 cases and 447,052 controls), hypertension (461,880 cases and 337,653 controls), age heart attack (10,693 cases and 451,187 controls), abnormalities of heartbeat (461,880 cases and 361,194 controls), stroke (7,055 cases and 454,825 controls), and coronary heart disease (361,194 cases and 351,037 controls) from United Kingdom biobank. We further carried out heterogeneity and sensitivity analyses. We confirmed the causality of RA with age angina (OR = 1.17, 95% CI: 1.04-1.33, p = 1.07E-02), hypertension (OR = 1.45, 95% CI: 1.20-1.75, p = 9.64E-05), age heart attack (OR = 1.15, 95% CI: 1.05-1.26, p = 3.56E-03), abnormalities of heartbeat (OR = 1.07, 95% CI: 1.01-1.12, p = 1.49E-02), stroke (OR = 1.06, 95% CI: 1.01-1.12, p = 2.79E-02), and coronary heart disease (OR = 1.19, 95% CI: 1.01-1.39, p = 3.33E-02), contributing to the understanding of the overlapping genetic mechanisms and therapeutic approaches between RA and cardiovascular disease.

Association between the Plasma-Glycosylated Hemoglobin A1c/High-Density Lipoprotein Cholesterol Ratio and Carotid Atherosclerosis: A Retrospective Study.

BACKGROUND: Diabetes mellitus (DM) and dyslipidemia are the main risk factors for atherosclerosis. Elevated glycosylated hemoglobin A1c (HbA1c) and reduced high-density lipoprotein cholesterol (HDL-C) are associated with the progression of atherosclerosis. The aim of this study is at exploring the relationship between the HbA1c/HDL-C ratio and atherosclerosis evaluated using carotid artery intima-media thickness (cIMT) and carotid artery plaque. METHODS: In this retrospective study, we enrolled 1304 patients who had multiple cardiovascular risk factors or symptoms of suspected coronary artery disease. cIMT and carotid artery plaque were measured using ultrasonography. Logistic regression was used to explore the correlation between the HbA1c/HDL-C ratio and cIMT or carotid artery plaque. We used restricted cubic spline curves to assess nonlinear relationships between the HbA1c/HDL-C ratio and cIMT or carotid artery plaque. RESULTS: With increased quartiles of HbA1c/HDL-C, patients had higher cIMT and a greater carotid plaque burden. After adjusting for other relevant clinical covariates, patients with the highest HbA1c/HDL-C ratio (quartile 4 (Q4)) had a 2.88 times (95% confidence interval (CI): 2.02-4.10, P < 0.001) more abnormal mean cIMT, 3.72 times (95% CI: 2.55-5.44, P < 0.001) more abnormal maximum cIMT, and 2.58 times (95% CI: 1.70-3.91, P < 0.001) greater carotid artery plaque burden compared with patients who had the lowest HbA1c/HDL-C ratio (Q1). Moreover, the association of HbA1c/HDL-C with atherosclerosis remained significant in a subsample of patients with and without DM. CONCLUSION: As a novel compound indicator for evaluating blood glucose homeostasis and dyslipidemia, the HbA1c/HDL-C ratio was positively correlated with carotid atherosclerosis evaluated using the mean and maximum cIMT as well as the carotid artery plaque burden.

Corrigendum: Exploring the Causality Between Hypothyroidism and Non-alcoholic Fatty Liver: A Mendelian Randomization Study.

[This corrects the article DOI: 10.3389/fcell.2021.643582.].

Exploring the Causality Between Hypothyroidism and Non-alcoholic Fatty Liver: A Mendelian Randomization Study.

The etiology of non-alcoholic fatty liver disease (NAFLD) involves complex interaction of genetic and environmental factors. A large number of observational studies have shown that hypothyroidism contributes to a high risk of NAFLD. However, the exact causality is still unknown. Due to the progress of genome-wide association study (GWAS) and the discovery of Mendelian randomization (MR), it is possible to explore the causality between the two diseases. In this study, in order to research into the influence of intermediate phenotypes on outcome, nine independent genetic variants of hypothyroidism obtained from the GWAS were used as instrumental variables (IVs) to perform MR analysis on NAFLD. Since there was no heterogeneity between IVs (P = 0.70), a fixed-effects model was used. The correlation between hypothyroidism and NAFLD was evaluated by using inverse-variance weighted (IVW) method and weighted median method. Then the sensitivity test was analyzed. The results showed that there was a high OR (1.7578; 95%CI 1.1897-2.5970; P = 0.0046) and a low intercept (-0.095; P = 0.431). None of the genetic variants drove the overall result (P < 0.01). Simply, we proved for the first time that the risk of NAFLD increases significantly on patients with hypothyroidism. Furthermore, we explained possible causes of NAFLD caused by hypothyroidism.

PremPS: Predicting the impact of missense mutations on protein stability.

Computational methods that predict protein stability changes induced by missense mutations have made a lot of progress over the past decades. Most of the available methods however have very limited accuracy in predicting stabilizing mutations because existing experimental sets are dominated by mutations reducing protein stability. Moreover, few approaches could consistently perform well across different test cases. To address these issues, we developed a new computational method PremPS to more accurately evaluate the effects of missense mutations on protein stability. The PremPS method is composed of only ten evolutionary- and structure-based features and parameterized on a balanced dataset with an equal number of stabilizing and destabilizing mutations. A comprehensive comparison of the predictive performance of PremPS with other available methods on nine benchmark datasets confirms that our approach consistently outperforms other methods and shows considerable improvement in estimating the impacts of stabilizing mutations. A protein could have multiple structures available, and if another structure of the same protein is used, the predicted change in stability for structure-based methods might be different. Thus, we further estimated the impact of using different structures on prediction accuracy, and demonstrate that our method performs well across different types of structures except for low-resolution structures and models built based on templates with low sequence identity. PremPS can be used for finding functionally important variants, revealing the molecular mechanisms of functional influences and protein design. PremPS is freely available at https://lilab.jysw.suda.edu.cn/research/PremPS/, which allows to do large-scale mutational scanning and takes about four minutes to perform calculations for a single mutation per protein with ~ 300 residues and requires ~ 0.4 seconds for each additional mutation.

PremPRI: Predicting the Effects of Missense Mutations on Protein-RNA Interactions.

Protein-RNA interactions are crucial for many cellular processes, such as protein synthesis and regulation of gene expression. Missense mutations that alter protein-RNA interaction may contribute to the pathogenesis of many diseases. Here, we introduce a new computational method PremPRI, which predicts the effects of single mutations occurring in RNA binding proteins on the protein-RNA interactions by calculating the binding affinity changes quantitatively. The multiple linear regression scoring function of PremPRI is composed of three sequence- and eight structure-based features, and is parameterized on 248 mutations from 50 protein-RNA complexes. Our model shows a good agreement between calculated and experimental values of binding affinity changes with a Pearson correlation coefficient of 0.72 and the corresponding root-mean-square error of 0.76 kcal·mol-1, outperforming three other available methods. PremPRI can be used for finding functionally important variants, understanding the molecular mechanisms, and designing new protein-RNA interaction inhibitors.