Glucose-oxygen coupling can serve as a biomarker for neuroinflammation-related genetic variants.

The single-nucleotide polymorphism rs3197999 in the macrophage-stimulating protein 1 gene is a missense variant. Studies have indicated that macrophage-stimulating protein 1 mediates neuronal loss and synaptic plasticity damage, and overexpression of the macrophage-stimulating protein 1 gene leads to the excessive activation of microglial cells, thereby resulting in an elevation of cerebral glucose metabolism. Traditional diagnostic models may be disrupted by neuroinflammation, making it difficult to predict the pathological status of patients solely based on single-modal images. We hypothesize that the macrophage-stimulating protein 1 rs3197999 single-nucleotide polymorphism may lead to imbalances in glucose and oxygen metabolism, thereby influencing cognitive resilience and the progression of Alzheimer's disease. In this study, we found that among 121 patients with mild cognitive impairment, carriers of the macrophage-stimulating protein 1 rs3197999 risk allele showed a significant reduction in the coupling of glucose and oxygen metabolism in the dorsolateral prefrontal cortex region. However, the rs3197999 variant did not induce significant differences in glucose metabolism and neuronal activity signals. Furthermore, the rs3197999 risk allele correlated with a higher rate of increase in clinical dementia score, mediated by the coupling of glucose and oxygen metabolism.

Genetic analysis and intracytoplasmic sperm injection outcomes of Chinese patients with congenital bilateral absence of vas deferens.

PURPOSE: Congenital bilateral absence of the vas deferens (CBAVD) is a major cause of obstructive azoospermia and male factor infertility. CBAVD is mainly caused by mutations in the genes encoding CFTR (cystic fibrosis transmembrane conductance regulator) and ADGRG2 (adhesion G protein-coupled receptor G2). This study aimed to describe CFTR and ADGRG2 variations in 46 Chinese CBAVD patients and evaluated sperm retrieval and assisted reproductive technology outcomes. METHODS: The CFTR and ADGRG2 genes were sequenced and analyzed by whole-exome sequencing (WES), and variations were identified by Sanger sequencing. Bioinformatic analysis was performed. We retrospectively reviewed the outcomes of patients undergoing sperm retrieval surgery and intracytoplasmic sperm injection (ICSI). RESULTS: In total, 35 of 46 (76.09%) patients carried at least one variation in CFTR, but no copy number variants or ADGRG2 variations were found. In addition to the IVS9-5 T allele, there were 27 CFTR variations, of which 4 variations were novel and predicted to be damaging by bioinformatics. Spermatozoa were successfully retrachieved in 46 patients, and 39 of the patients had their own offspring through ICSI. CONCLUSION: There are no obvious hotspot CFTR mutations in Chinese CBAVD patients besides the IVS9-5 T allele. Therefore, WES might be the best detection method, and genetic counseling should be different from that provided to Caucasian populations. After proper counseling, all patients can undergo sperm retrieval from their epididymis or testis, and most of them can have their own children through ICSI.

Soluble epoxide hydrolase deficiency attenuates lipotoxic cardiomyopathy via upregulation of AMPK-mTORC mediated autophagy.

Obesity-driven cardiac lipid accumulation can progress to lipotoxic cardiomyopathy. Soluble epoxide hydrolase (sEH) is the major enzyme that metabolizes epoxyeicosatrienoic acids (EETs), which have biological activity of regulating lipid metabolism. The current study explores the unknown role of sEH deficiency in lipotoxic cardiomyopathy and its underlying mechanism. Wild-type and Ephx2 knock out (sEH KO) C57BL/6 J mice were fed with high-fat diet (HFD) for 24 weeks to induce lipotoxic cardiomyopathy animal models. Palmitic acid (PA) was utilized to induce lipotoxicity to cardiomyocytes for in vitro study. We found sEH KO, independent of plasma lipid and blood pressures, significantly attenuated HFD-induced myocardial lipid accumulation and cardiac dysfunction in vivo. HFD-induced lipotoxic cardiomyopathy and dysfunction of adenosine 5'-monophosphate-activated protein kinase-mammalian target of rapamycin complex (AMPK-mTORC) signaling mediated lipid autophagy in heart were restored by sEH KO. In primary neonatal mouse cardiomyocytes, both sEH KO and sEH substrate EETs plus sEH inhibitor AUDA treatments attenuated PA-induced lipid accumulation. These effects were blocked by inhibition of AMPK or autophagy. The outcomes were supported by the results that sEH KO and EETs plus AUDA rescued HFD- and PA-induced impairment of autophagy upstream signaling of AMPK-mTORC, respectively. These findings revealed that sEH deficiency played an important role in attenuating myocardial lipid accumulation and provided new insights into treating lipotoxic cardiomyopathy. Regulation of autophagy via AMPK-mTORC signaling pathway is one of the underlying mechanisms.

The absolute and relative changes in high-sensitivity cardiac troponin I are associated with the in-hospital mortality of patients with fulminant myocarditis.

BACKGROUND: We sought to describe the tendency and extent of high-sensitivity cardiac troponin I (hs-cTnI) changes in patients with fulminant myocarditis (FM) after admission and to explore the relationship between the in-hospital mortality of FM and the absolute and relative changes in hs-cTnI within 24 h and 48 h after admission. METHODS: In the retrospective study, the object are patients diagnosed with FM in our single centre. The value of cardiac troponin was recorded after patients admitted to hospital in succession. The absolute and relative changes in hs-cTnI within 24 h and 48 h were described as range distributions. Receiver operating characteristic (ROC) curve and Cox analyses were performed to determine the relationship between in-hospital mortality of FM and hs-cTnI changes. RESULTS: A total of 83 FM patients admitted to our centre from January 1, 2010 to December 31, 2019 were included; 69 patients survived and 14 patients died. In the survival group, 78% of patients experienced a decline in hs-cTnI within 24 h, while 36% of the mortality group exhibited a declining tendency in hs-cTnI (P = 0.003). Nearly 60% of survival group had a 0-2000 ng/l reduction in troponin from baseline within 24 h of admission. However, troponin levels of 50% of patients in the mortality group were 0-10,000 ng/ L higher than baseline 24 h after admission. Multivariable logistic analysis revealed that the declining tendency of hs-cTnI within 24 h, in addition to time from onset to admittance to hospital, intravenous immunoglobulin treatment and the abnormal level of creatinine, were associated with the in-hospital mortality of FM (for the declining tendency of hs-cTnI within 24 h, OR = 0.10, 95% CI 0.02-0.68, P = 0.018). The ROC curve revealed optimal cut-off values of - 618 ng/l for absolute change within 24 h (AUC = 0.800, P < 0.01), - 4389 ng/l for absolute change within 48 h (area under the curve = 0.711, P < 0.01), - 28.46% for relative change within 24 h (AUC = 0.810, P < 0.01), and - 52.23% for relative change within 48 h (AUC = 0.795, P < 0.01). Absolute changes and relative changes in hs-cTnI within 24 h and 48 h were strong predictors of in-hospital mortality by Cox regression analysis after adjustment for sex, time from onset to admission, and occurrence of ventricular tachycardia or ventricular fibrillation. CONCLUSION: Most FM patients who survived experienced a decline in hs-cTnI within 24 h. The absolute and relative changes in hs-cTnI within 24 h and 48 h were strong predictors of in-hospital mortality.

The Dynamic EEG Microstates in Mental Rotation.

Mental rotation is generally analyzed based on event-related potential (ERP) in a time domain with several characteristic electrodes, but neglects the whole spatial-temporal brain pattern in the cognitive process which may reflect the underlying cognitive mechanism. In this paper, we mainly proposed an approach based on microstates to examine the encoding of mental rotation from the spatial-temporal changes of EEG signals. In particular, we collected EEG data from 11 healthy subjects in a mental rotation cognitive task using 12 different stimulus pictures representing left and right hands at various rotational angles. We applied the microstate method to investigate the microstates conveyed by the event-related potential extracted from EEG data during mental rotation, and obtained four microstate modes (referred to as modes A, B, C, D, respectively). Subsequently, we defined several measures, including microstate sequences, topographical map, hemispheric lateralization, and duration of microstate, to characterize the dynamics of microstates during mental rotation. We observed that (1) the microstates sequence had a specified progressing mode, i.e., A → B → A ; (2) the activation of the right parietal occipital region was stronger than that of the left parietal occipital region according to the hemispheric lateralization of the microstates mode A; and (3) the duration of the second microstates mode A showed the shorter duration in the vertical stimuli, named "angle effect".

APOA1/C3/A4/A5 Gene Cluster at 11q23.3 and Lipid Metabolism Disorders: From Epigenetic Mechanisms to Clinical Practices.

The APOA1/C3/A4/A5 cluster is an essential component in regulating lipoprotein metabolism and maintaining plasma lipid homeostasis. A genome-wide association analysis and Mendelian randomization have revealed potential associations between genetic variants within this cluster and lipid metabolism disorders, including hyperlipidemia and cardiovascular events. An enhanced understanding of the complexity of gene regulation has led to growing recognition regarding the role of epigenetic variation in modulating APOA1/C3/A4/A5 gene expression. Intensive research into the epigenetic regulatory patterns of the APOA1/C3/A4/A5 cluster will help increase our understanding of the pathogenesis of lipid metabolism disorders and facilitate the development of new therapeutic approaches. This review discusses the biology of how the APOA1/C3/A4/A5 cluster affects circulating lipoproteins and the current progress in the epigenetic regulation of the APOA1/C3/A4/A5 cluster.

Exploring the impact of a KCNH2 missense variant on Long QT syndrome: insights into a novel gender-selective, incomplete penetrance inheritance mode.

Background: Long QT syndrome (LQTS) is an inherited malignant arrhythmia syndrome that poses a risk of sudden death. Variants in the Potassium Voltage-Gated Channel Subfamily H Member 2 (KCNH2) gene are known to cause Long QT syndrome through an autosomal dominant inheritance pattern. However, as of now, there have been no reports of any KCNH2 variant leading to Long QT syndrome exhibiting incomplete penetrance that is influenced by gender. Methods: Whole-exome sequencing (WES) was conducted on the proband to identify pathogenic variants. Subsequently, Sanger sequencing was employed to validate the identified likely pathogenic variants in all family members. Results: We analyzed a pedigree spanning three-generations afflicted by Long QT syndrome. WES revealed a novel KCNH2 missense variant (p.Val630Gly, c.1889 T>G) as the causative factor for the family's phenotype. Within this family, all three male carriers of the KCNH2 variant carriers exhibited the Long QT syndrome phenotype: one experienced sudden death during sleep, another received an implantable cardioverter defibrillator (ICD), and a younger man displayed a prolonged QTc interval without any instances of syncope or malignant arrhythmia to date. Interestingly, the middle-aged female carrier showed no Long QT Syndrome phenotype. However, her offspring, diagnosed with Turner syndrome (45, X) and also a carrier of this variant, experienced frequent syncope starting at 12 years old and was diagnosed with Long QT syndrome, leading to an ICD implantation when she was 15 years old. These observations suggest that the manifestation of Long QT syndrome associated with this KCNH2 variant exhibits incomplete penetrance influenced by gender within this family, indicating potential protective mechanisms against the syndrome in females affected by this variant. Conclusion: Our investigation has led to the identification of a novel pathogenic KCNH2 variant responsible for Long QT syndrome within a familial context characterized by gender-selective, incomplete penetrance. This discovery highlights a unique pathogenic inheritance pattern for the KCNH2 gene associated with Long QT syndrome, and could potentially shed light on the distinct penetrance behaviors and patterns of the KCNH2 gene. This discovery broadens our exploration of the KCNH2 gene in cardiac arrhythmias, highlighting the intricate genetic dynamics behind Long QT syndrome.

Novel Alzheimer's disease subtypes based on functional brain connectivity in human connectome project.

The pathogenesis of Alzheimer's disease (AD) remains unclear, but revealing individual differences in functional connectivity (FC) may provide insights and improve diagnostic precision. A hierarchical clustering-based autoencoder with functional connectivity was proposed to categorize 82 AD patients from the Alzheimer's Disease Neuroimaging Initiative. Compared to directly performing clustering, using an autoencoder to reduce the dimensionality of the matrix can effectively eliminate noise and redundant information in the data, extract key features, and optimize clustering performance. Subsequently, subtype differences in clinical and graph theoretical metrics were assessed. Results indicate a significant inter-subject heterogeneity in the degree of FC disruption among AD patients. We have identified two neurophysiological subtypes: subtype I exhibits widespread functional impairment across the entire brain, while subtype II shows mild impairment in the Limbic System region. What is worth noting is that we also observed significant differences between subtypes in terms of neurocognitive assessment scores associations with network functionality, and graph theory metrics. Our method can accurately identify different functional disruptions in subtypes of AD, facilitating personalized treatment and early diagnosis, ultimately improving patient outcomes.

A hybrid multimodal machine learning model for Detecting Alzheimer's disease.

Alzheimer's disease (AD) diagnosis utilizing single modality neuroimaging data has limitations. Multimodal fusion of complementary biomarkers may improve diagnostic performance. This study proposes a multimodal machine learning framework integrating magnetic resonance imaging (MRI), positron emission tomography (PET) and cerebrospinal fluid (CSF) assays for enhanced AD characterization. The model incorporates a hybrid algorithm combining enhanced Harris Hawks Optimization (HHO) algorithm referred to as ILHHO, with Kernel Extreme Learning Machine (KELM) classifier for simultaneous feature selection and classification. ILHHO enhances HHO's search efficiency by integrating iterative mapping (IM) to improve population diversity and local escaping operator (LEO) to balance exploration-exploitation. Comparative analysis with other improved HHO algorithms, classic meta-heuristic algorithms (MHAs), and state-of-the-art MHAs on IEEE CEC2014 benchmark functions indicates that ILHHO achieves superior optimization performance compared to other comparative algorithms. The synergistic ILHHO-KELM model is evaluated on 202 AD Neuroimaging Initiative (ADNI) subjects. Results demonstrate superior multimodal classification accuracy over single modalities, validating the importance of fusing heterogeneous biomarkers. MRI + PET + CSF achieves 99.2 % accuracy for AD vs. normal control (NC), outperforming conventional and proposed methods. Discriminative feature analysis provides further insights into differential AD-related neurodegeneration patterns detected by MRI and PET. The differential PET and MRI features demonstrate how the two modalities provide complementary biomarkers. The neuroanatomical relevance of selected features supports ILHHO-KELM's potential for extracting sensitive AD imaging signatures. Overall, the study showcases the advantages of capitalizing on complementary multimodal data through advanced feature learning techniques for improving AD diagnosis.

Cardiac magnetic resonance imaging detection of intramyocardial hemorrhage in patients with ST-elevated myocardial infarction: comparison between susceptibility-weighted imaging and T1/T2 mapping techniques.

Background: Susceptibility-weighted imaging (SWI) and T1/T2 mapping can be used to detect reperfusion intramyocardial hemorrhage (IMH) in ST-segment elevation myocardial infarction (STEMI) patients. However, the sensitivity and accuracy of the SWI and T1/T2 mapping sequences were not systematically compared. The study aimed to evaluate image quality and diagnostic performance of SWI in patients with IMH, compared with T1/T2 mapping. Methods: A prospective study was conducted on consecutive acute STEMI patients who were recruited from January to July 2022. Within 2-6 days after reperfusion treatment, all patients underwent a 3T cardiac magnetic resonance (CMR) examination, including T2-weighted short-tau inversion recovery (T2W-STIR), T1/T2 mapping, and SWI. A total of 36 patients [age, 56.50±17.25 years; males, 83.33% (30/36)] were enrolled. The relative infarct-remote myocardium signal intensity ratio (SIinfarct-remote) and contrast-to-noise ratio (CNR) were calculated for each patient on T1/T2 mapping and SWI, and the difference between relative signal intensity-to-noise ratio (rSNR) in the IMH (rSNRIMH) was measured for IMH patients on T1/T2 mapping and SWI. SIinfarct-remote, CNR, and rSNRIMH were compared among the three sequences. Receiver operating characteristic (ROC) analyses were used to evaluate the diagnostic performance of three sequences by SIinfarct-remote and visual assessment. Results: A total of 26 (72.22%) patients had IMH. Quantitatively, the SIinfarct-remote of three sequences had excellent diagnostic performance for detecting IMH [SWI area under the curve (AUC) =1.000, 95% confidence interval (CI): 1.000-1.000 vs. T1 mapping AUC =0.954, 95% CI: 0.885-1.000 vs. T2 mapping AUC =0.985, 95% CI: 0.955-1.000; SWI vs. T1 mapping, P=0.300; SWI vs. T2 mapping, P=0.188; T1 mapping vs. T2 mapping, P=0.302). Qualitatively, three sequences had similar performance on detecting IMH (SWI AUC =0.895, 95% CI: 0.784-1.000; T1 mapping AUC =0.835, 95% CI: 0.711-0.958; and T2 mapping AUC =0.855, 95% CI: 0.735-0.974; SWI vs. T1 mapping, P=0.172; SWI vs. T2 mapping, P=0.317; T1 mapping vs. T2 mapping, P=0.710). The rSNRIMH was highest in T1 mapping, followed by T2 mapping and SWI, but SWI had the highest CNR. Conclusions: SWI, as well as T1/T2 mapping, is a feasible and accurate approach for clinical diagnosis of IMH with excellent performance.

Intratumoural delivery of TRAIL mRNA induces colon cancer cell apoptosis.

Novel strategies in intratumoral injection and emerging immunotherapies have heralded a new era of precise cancer treatments. The affinity of SARS-CoV-2 to ACE2 receptors, a feature which facilitates virulent human infection, is leveraged in this research. Colon cancer cells, with their high ACE2 expression, provide a potentially strategic target for using this SARS-CoV-2 feature. While the highly expression of ACE2 is observed in several cancer types, the idea of using the viral spike protein for targeting colon cancer cells offers a novel approach in cancer treatment. Intratumoral delivery of nucleic acid-based drugs is a promising alternative to overcoming the limitations of existing therapies. The increasing importance of nucleic acids in this realm, and the use of Lipid Nanoparticles (LNPs) for local delivery of nucleic acid therapeutics, are important breakthroughs. LNPs protect nucleic acid drugs from degradation and enhance cellular uptake, making them a rapidly evolving nano delivery system with high precision and adaptability. Our study leveraged a tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) combined with a receptor-binding domain from the SARS-CoV-2 spike protein, encapsulated in LNPs, to target colon cancer cells. Our results indicated that the TRAIL fusion-mRNA induced apoptosis in vitro and in vivo. Collectively, our findings highlight LNP-encapsulated TRAIL fusion-mRNA as a potential colon cancer therapy.

Enhanced Harris hawks optimization-based fuzzy k-nearest neighbor algorithm for diagnosis of Alzheimer's disease.

In order to stop deterioration and give patients with Alzheimer's disease (AD) early therapy, it is crucial to correctly diagnose AD and its early stage, mild cognitive impairment (MCI). A framework for diagnosing AD is presented in this paper, which includes magnetic resonance imaging (MRI) image preprocessing, feature extraction, and the Fuzzy k-nearest neighbor algorithm (FKNN) model. In particular, the framework's novelty lies in the use of an improved Harris Hawks Optimization (HHO) algorithm named SSFSHHO, which integrates the Sobol sequence and Stochastic Fractal Search (SFS) mechanisms for optimizing the parameters of FKNN. The HHO method improves the quality of the initial population overall by incorporating the Sobol sequence, and the SFS mechanism increases the algorithm's capacity to get out of the local optimum solution. Comparisons with other classical meta-heuristic algorithms, state-of-the-art HHO variants in low and high dimensions, and enhanced meta-heuristic algorithms on 30 typical IEEE CEC2014 benchmark test problems show that the overall performance of SSFSHHO is significantly better than other comparative algorithms. Moreover, the created framework based on the SSFSHHO-FKNN model is employed to classify AD and MCI using MRI scans from the ADNI dataset, achieving high classification performance for 6 representative cases. Experimental findings indicate that the proposed algorithm performs better than a number of high-performance optimization algorithms and classical machine learning algorithms, thus offering a promising approach for AD classification. Additionally, the proposed strategy can successfully identify relevant features and enhance classification performance for AD diagnosis.

Dissociation of energy connectivity and functional connectivity in Alzheimer's disease is associated with maintenance of cognitive performance.

The correlation between functional connectivity (FC) network segregation, glucose metabolism and cognitive decline has been recently identified. The coupling relationship between glucose metabolism and the intensity of neuronal activity obtained using hybrid PET/MRI techniques can provide additional information on the physiological state of the brain in patients with AD and mild cognitive impairment (MCI). It is a valuable task to use the above rules for constructing biomarkers that are closely related to the cognitive ability of individuals to monitor the pathological status of patients. This study proposed the concept of the energy connectivity (EC) network and its construction method. We hypothesized that the dissociation between energy connectivity and functional connectivity of brain regions is a valid indicator of cognitive ability in patients with dementia. The number of EC-attenuated brain regions (EC-AR) and the number of FC-attenuated brain regions (FC-AR) are obtained by comparison with the normal group, and the dissociation between functional connectivity and energy connectivity is indicated using the ratio of FC-AR to EC-AR for individuals in the disease group. The findings suggest that FC-AR/EC-AR values are accurate predictors of cognitive performance, while taking into account the cognitive recovery due to compensatory effects of the brain. The cognitive ability of some patients with cognitive recovery can also be predicted more accurately. This also indicates that lower functional connectivity and higher energy connectivity between network modules may be one of the important features that maintain cognitive performance. The concept of energy connectivity also has potential to help explore the pathological state of AD.

The role of endothelial cell in cardiac hypertrophy: Focusing on angiogenesis and intercellular crosstalk.

Cardiac hypertrophy is characterized by cardiac structural remodeling, fibrosis, microvascular rarefaction, and chronic inflammation. The heart is structurally organized by different cell types, including cardiomyocytes, fibroblasts, endothelial cells, and immune cells. These cells highly interact with each other by a number of paracrine or autocrine factors. Cell-cell communication is indispensable for cardiac development, but also plays a vital role in regulating cardiac response to damage. Although cardiomyocytes and fibroblasts are deemed as key regulators of hypertrophic stimulation, other cells, including endothelial cells, also exert important effects on cardiac hypertrophy. More particularly, endothelial cells are the most abundant cells in the heart, which make up the basic structure of blood vessels and are widespread around other cells in the heart, implicating the great and inbuilt advantage of intercellular crosstalk. Cardiac microvascular plexuses are essential for transport of liquids, nutrients, molecules and cells within the heart. Meanwhile, endothelial cell-mediated paracrine signals have multiple positive or negative influences on cardiac hypertrophy. However, a comprehensive discussion of these influences and consequences is required. This review aims to summarize the basic function of endothelial cells in angiogenesis, with an emphasis on angiogenic molecules under hypertrophic conditions. The secondary objective of the research is to fully discuss the key molecules involved in the intercellular crosstalk and the endothelial cell-mediated protective or detrimental effects on other cardiac cells. This review provides a more comprehensive understanding of the overall role of endothelial cells in cardiac hypertrophy and guides the therapeutic approaches and drug development of cardiac hypertrophy.

COVID-19 infection with complicated fulminant myocarditis: a case report.

Herein, we report the case of a young female patient who suffered from myositis and heart failure due to fulminant myocarditis induced by the 2019 coronavirus disease (COVID-19). After receiving intra-aortic balloon pump (IABP) and immunomodulatory treatment, her vital signs gradually stabilized and the IABP was removed. Cardiac and muscle magnetic resonance imaging confirmed extensive myocardial and skeletal muscle edema. Though it is not uncommon for COVID-19 infection to be complicated by myocarditis and myositis, such serious muscle injury warrants clinical vigilance.

Characteristics of Electrocardiogram Findings in Fulminant Myocarditis.

Fulminant myocarditis (FM) is an acute and severe form of myocarditis with rapid progression and poor clinical outcomes in the absence of acute or chronic coronary artery disease. Electrocardiogram (ECG) abnormalities can provide preliminary clues for diagnosis; however, there is a lack of systemic descriptions on ECG changes in FM populations. Thus, a retrospective analysis of 150 consecutive FM patients and 300 healthy controls was performed to determine the characteristic ECG findings in FM. All patients included had markedly abnormal ECG findings. Specifically, 83 (55.33%) patients had significantly lower voltage with remarkably decreased QRS amplitudes in all leads compared with healthy controls (p < 0.01), and 77 (51.33%) patients had a variety of arrhythmias with lethality ventricular tachycardia/ventricular fibrillation in 21 (14.00%) patients and third-degree atrioventricular block in 21 (14.00%) patients, whereas sinus tachycardia was only found in 43 (28.67%) patients with the median heart rate (HR; 88.00 bpm, IQR: 76.00-113.50) higher than that of controls (73.00 bpm, IQR: 68.00-80.00) (p = 0.000). Conduction and repolarization abnormalities were common in patients. A longer QTc interval (452.00 ms, IQR: 419.00-489.50) and QRS duration (94.00 ms, IQR: 84.00-119.00) were observed in patients compared to controls (QTc interval = 399.00 ms, IQR: 386.00-414.00; QRS duration = 90.00 ms, IQR: 86.00-98.00) (p < 0.05). Additionally, HR > 86.50 bpm, QTc > 431.50 ms, and RV5 + SV1 < 1.715 mV can be used to predict FM. Thus, marked and severe ECG abnormalities provide preliminary clues for the diagnosis of FM.

Myocardial injury and related mortality in hospitalized patients with COVID-19 during the Omicron pandemic: new perspectives and insights.

Myocardial injury is one of the most common comorbidity in SARS-CoV-2 infected patients, and has poor prognosis. However, the incidence of myocardial injury in patients with SARS-CoV-2 infection has not been sufficiently investigated during the Omicron wave. We conducted a retrospective study of 2690 patients with confirmed SARS-CoV-2 Omicron infection from Tongji Hospital. The results indicated that the myocardial injury accounted for 30.8% of the total patients with SARS-CoV-2 infection and was associated with higher in-hospital mortality than those without injury before and after propensity score matching (PSM) [adjusted hazard ratio (HR), 10.61; 95% confidence interval (CI), 7.76-14.51; P â€‹< â€‹0.001; adjusted HR, 2.70; 95% CI, 1.86-3.93; P â€‹< â€‹0.001; respectively]. Further, the levels of cytokines (IL-1ß, IL-6, IL-10, and TNF-α) in patients with myocardial injury were higher than those without injury, and the higher levels of cytokines in the myocardial injury group were associated with increased mortality. Administration of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARB) could significantly reduce the mortality in patients with myocardial injury (adjusted HR, 0.52; 95% CI, 0.38-0.71; P â€‹< â€‹0.001). Additionally, the level of angiotensin II increased in patients with SARS-CoV-2 infection was even higher in myocardial injury group compared to those without injury. Collectively, the study summarized the clinical characteristic and outcome of SARS-CoV-2 infected patients with myocardial injury during the Omicron wave in China, and validated the protective role of ACEI/ARB in improving the survival of those with myocardial injury.

Tripartite Evolutionary Game of Agricultural Service Scale Management and Small Farmers' Interests under Government Preferential Policies.

In agricultural production with small farmers as the main body, the service scale operation is one of the ways to obtain scale operation benefits. This paper constructs a tripartite evolutionary game model of agricultural scale service providers (integrators), demand subjects (farmers), and agriculture-related government departments and analyzes the influencing factors, influencing relations, and evolutionary stable equilibrium results of each participant's strategy choice. The results show that improving rewards and punishments and strengthening supervision by agriculture-related government departments will help integrators provide high-quality services and encourage farmers to actively produce and reduce speculation; when the cost difference between high-quality service and low-quality service is large, the probability of high-quality service provided by integrators will be reduced, and the evolution result of low Pareto efficiency may appear in the system; when the speculative cost of farmers is not high, the lobbying efforts of integrators will increase the speculative behavior of farmers. Finally, MATLAB2018a is used to simulate and analyze the validity of the model results, which provides a theoretical reference for the scale operation of agricultural services.

Parallel MR image reconstruction based on triple cycle optimization.

The self-calibration parallel imaging (SC-SENSE) method reconstructs the image by estimating the coil sensitivity matrix. In order to obtain the sensitivity matrix, it is necessary to take a small amount of automatic calibration signal lines (ACSL) in the center of k-space. This method uses the data of the central region to obtain the sensitivity matrix, and then the reconstructed image is obtained. This paper proposed the triple cycle optimization (TCO) method to continuously optimize reconstructed images. The proposed TCO method takes the sensitivity matrix obtained by ACSL and substituted the reconstructed image as the initial data generation into the loop, and estimates the k-space data repeatedly. A new sensitivity matrix is obtained by using k-space data and the reconstructed image, and a stable triple cycle is obtained. In the cycle, all data are optimized to a certain extent, including the reconstructed image. Experimental results show that under the same sampling density, images reconstructed by using the triple cycle optimization method have lower noise and artifacts than those of the traditional method. When combined with the variable density sampling method, the effect is remarkable with a much low sampling rate.

A review ofimaging genetics in Alzheimer's disease.

Determining the association between genetic variation and phenotype is a key step to study the mechanism of Alzheimer's disease (AD), laying the foundation for studying drug therapies and biomarkers. AD is the most common type of dementia in the aged population. At present, three early-onset AD genes (APP, PSEN1, PSEN2) and one late-onset AD susceptibility gene apolipoprotein E (APOE) have been determined. However, the pathogenesis of AD remains unknown. Imaging genetics, an emerging interdisciplinary field, is able to reveal the complex mechanisms from the genetic level to human cognition and mental disorders via macroscopic intermediates. This paper reviews methods of establishing genotype-phenotype to explore correlations, including sparse canonical correlation analysis, sparse reduced rank regression, sparse partial least squares and so on. We found that most research work did poorly in supervised learning and exploring the nonlinear relationship between SNP-QT.