Effective multi-modal clustering method via skip aggregation network for parallel scRNA-seq and scATAC-seq data.

In recent years, there has been a growing trend in the realm of parallel clustering analysis for single-cell RNA-seq (scRNA) and single-cell Assay of Transposase Accessible Chromatin (scATAC) data. However, prevailing methods often treat these two data modalities as equals, neglecting the fact that the scRNA mode holds significantly richer information compared to the scATAC. This disregard hinders the model benefits from the insights derived from multiple modalities, compromising the overall clustering performance. To this end, we propose an effective multi-modal clustering model scEMC for parallel scRNA and Assay of Transposase Accessible Chromatin data. Concretely, we have devised a skip aggregation network to simultaneously learn global structural information among cells and integrate data from diverse modalities. To safeguard the quality of integrated cell representation against the influence stemming from sparse scATAC data, we connect the scRNA data with the aggregated representation via skip connection. Moreover, to effectively fit the real distribution of cells, we introduced a Zero Inflated Negative Binomial-based denoising autoencoder that accommodates corrupted data containing synthetic noise, concurrently integrating a joint optimization module that employs multiple losses. Extensive experiments serve to underscore the effectiveness of our model. This work contributes significantly to the ongoing exploration of cell subpopulations and tumor microenvironments, and the code of our work will be public at https://github.com/DayuHuu/scEMC.

HyperTMO: a trusted multi-omics integration framework based on hypergraph convolutional network for patient classification.

MOTIVATION: The rapid development of high-throughput biomedical technologies can provide researchers with detailed multi-omics data. The multi-omics integrated analysis approach based on machine learning contributes a more comprehensive perspective to human disease research. However, there are still significant challenges in representing single-omics data and integrating multi-omics information. RESULTS: This article presents HyperTMO, a Trusted Multi-Omics integration framework based on Hypergraph convolutional network for patient classification. HyperTMO constructs hypergraph structures to represent the association between samples in single-omics data, then evidence extraction is performed by hypergraph convolutional network, and multi-omics information is integrated at an evidence level. Last, we experimentally demonstrate that HyperTMO outperforms other state-of-the-art methods in breast cancer subtype classification and Alzheimer's disease classification tasks using multi-omics data from TCGA (BRCA) and ROSMAP datasets. Importantly, HyperTMO is the first attempt to integrate hypergraph structure, evidence theory, and multi-omics integration for patient classification. Its accurate and robust properties bring great potential for applications in clinical diagnosis. AVAILABILITY AND IMPLEMENTATION: HyperTMO and datasets are publicly available at https://github.com/ippousyuga/HyperTMO.

Impact of body mass index on long-term outcomes in patients undergoing percutaneous coronary intervention stratified by diabetes mellitus: a retrospective cohort study.

BACKGROUND: Patients with diabetes mellitus (DM) caused by obesity have increased in recent years. The impact of obesity on long-term outcomes in patients undergoing percutaneous coronary intervention (PCI) with or without DM remains unclear. METHODS: We retrospectively analysed data from 1918 patients who underwent PCI. Patients were categorized into four groups based on body mass index (BMI, normal weight: BMI < 25 kg/m2; overweight and obese: BMI ≥ 25 kg/m2) and DM status (presence or absence). The primary endpoint was the occurrence of major adverse cardiac and cerebrovascular events (MACCE; defined as all-cause death, myocardial infarction, stroke, and unplanned repeat revascularization). RESULTS: During a median follow-up of 7.0 years, no significant differences in MACCE, myocardial infarction, or stroke were observed among the four groups. Overweight and obese individuals exhibited lower all-cause mortality rates compared with normal-weight patients (without DM: hazard ratio [HR]: 0.54, 95% confidence interval [CI]: 0.37 to 0.78; with DM: HR: 0.57, 95% CI: 0.38 to 0.86). In non-diabetic patients, the overweight and obese group demonstrated a higher risk of unplanned repeat revascularization than the normal-weight group (HR:1.23, 95% CI:1.03 to 1.46). After multivariable adjustment, overweight and obesity were not significantly associated with MACCE, all-cause death, myocardial infarction, stroke, or unplanned repeat revascularization in patients with and without diabetes undergoing PCI. CONCLUSION: Overweight and obesity did not demonstrate a significant protective effect on long-term outcomes in patients with and without diabetes undergoing PCI.

Chronic diseases spectrum and multimorbidity in elderly inpatients based on a 12-year epidemiological survey in China.

BACKGROUND: The number and proportion of the elderly population have been continuously increasing in China, leading to the elevated prevalence of chronic diseases and multimorbidity, which ultimately brings heavy burden to society and families. Meanwhile, the status of multimorbidity tends to be more complex in elderly inpatients than community population. In view of the above concerns, this study was designed to investigate the health status of elderly inpatients by analyzing clinical data in Chinese People's Liberation Army (PLA) General Hospital from 2008 to 2019, including the constitution of common diseases, comorbidities, the status of multimorbidity, in-hospital death and polypharmacy among elderly inpatients, so as to better understand the diseases spectrum and multimorbidity of elderly inpatients and also to provide supporting evidence for targeted management of chronic diseases in the elderly. METHODS: A clinical inpatients database was set up by collecting medical records of elderly inpatients from 2008 to 2019 in Chinese PLA General Hospital, focusing on diseases spectrum and characteristics of elderly inpatients. In this study, we collected data of inpatients aged ≥ 65 years old, and further analyzed the constitution of diseases, multimorbidity rates and mortality causes in the past decade. In addition, the prescriptions were also analyzed to investigate the status of polypharmacy in elderly inpatients. RESULTS: A total of 210,169 elderly patients were hospitalized from January 1st, 2008 to December 31st, 2019. The corresponding number of hospitalizations was 290,833. The average age of the study population was 72.67 years old. Of the total population, 73,493 elderly patients were re-admitted within one year, with the re-hospitalization rate of 25.27%. Malignant tumor, hypertension, ischemic heart disease, diabetes mellitus and cerebrovascular disease were the top 5 diseases. Among the study population, the number of patients with two or more long-term health conditions was 267,259, accounting for 91.89%, with an average of 4.68 diseases. In addition, the average number of medications taken by the study population was 5.4, among which, the proportion of patients taking more than 5 types of medications accounted for 55.42%. CONCLUSIONS: By analyzing the constitution of diseases and multimorbidity, we found that multimorbidity has turned out to be a prominent problem in elderly inpatients, greatly affecting the process of healthy aging and increasing the burden on families and society. Therefore, multidisciplinary treatment should be strengthened to make reasonable preventive and therapeutic strategies to improve the life quality of the elderly. Meanwhile, more attention should be paid to reasonable medications for elderly patients with multimorbidity to avoid preventable side effects caused by irrational medication therapy.

DeepKG: an end-to-end deep learning-based workflow for biomedical knowledge graph extraction, optimization and applications.

SUMMARY: DeepKG is an end-to-end deep learning-based workflow that helps researchers automatically mine valuable knowledge in biomedical literature. Users can utilize it to establish customized knowledge graphs in specified domains, thus facilitating in-depth understanding on disease mechanisms and applications on drug repurposing and clinical research. To improve the performance of DeepKG, a cascaded hybrid information extraction framework is developed for training model of 3-tuple extraction, and a novel AutoML-based knowledge representation algorithm (AutoTransX) is proposed for knowledge representation and inference. The system has been deployed in dozens of hospitals and extensive experiments strongly evidence the effectiveness. In the context of 144 900 COVID-19 scholarly full-text literature, DeepKG generates a high-quality knowledge graph with 7980 entities and 43 760 3-tuples, a candidate drug list, and relevant animal experimental studies are being carried out. To accelerate more studies, we make DeepKG publicly available and provide an online tool including the data of 3-tuples, potential drug list, question answering system, visualization platform. AVAILABILITY AND IMPLEMENTATION: All the results are publicly available at the website (http://covidkg.ai/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Association between the triglyceride-glucose index and the risk of mortality among patients with chronic heart failure: results from a retrospective cohort study in China.

BACKGROUND: The triglyceride-glucose (TyG) index has been demonstrated to be a reliable surrogate marker of insulin resistance (IR) and an effective predictive index of cardiovascular (CV) disease risk. However, its long-term prognostic value in patients with chronic heart failure (CHF) remains uncertain. METHODS: A total of 6697 consecutive patients with CHF were enrolled in this study. Patients were divided into tertiles according to their TyG index. The incidence of primary outcomes, including all-cause death and CV death, was recorded. The TyG index was calculated as ln [fasting triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. RESULTS: During a median follow-up of 3.9 years, a total of 2158 (32.2%) all-cause deaths and 1305 (19.5%) CV deaths were documented. The incidence of primary events from the lowest to the highest TyG index tertiles were 50.61, 64.64, and 92.25 per 1000 person-years for all-cause death and 29.05, 39.40, and 57.21 per 1000 person-years for CV death. The multivariate Cox hazards regression analysis revealed hazard ratios for all-cause and CV deaths of 1.84 (95% CI 1.61-2.10; P for trend < 0.001) and 1.94 (95% CI 1.63-2.30; P for trend < 0.001) when the highest and lowest TyG index tertiles were compared. In addition, the predictive ability of the TyG index against all-cause death was more prominent among patients with metabolic syndrome and those with heart failure with preserved ejection fraction phenotype (both P for interaction < 0.05). Furthermore, adding the TyG index to the established model for all-cause death improved the C­statistic value (0.710 for the established model vs. 0.723 for the established model + TyG index, P < 0.01), the integrated discrimination improvement value (0.011, P < 0.01), the net reclassification improvement value (0.273, P < 0.01), and the clinical net benefit (probability range, 0.07-0.36). CONCLUSIONS: The TyG index was significantly associated with the risk of mortality, suggesting that it may be a reliable and valuable predictor for risk stratification and an effective prognostic indicator in patients with CHF.

Serum uric acid and outcome in hospitalized elderly patients with chronic heart failure through the whole spectrum of ejection fraction phenotypes.

INTRODUCTION: Elevated serum uric acid (SUA) levels have been associated with poor outcome in patients with heart failure (HF). Uric acid is associated with inflammation and microvascular dysfunction, which may differentially affect left ventricular ejection fraction (EF) phenotypes. We aimed to identify the role of SUA across EF phenotypes in hospitalized elderly patients with chronic HF. METHODS: We analyzed 1355 elderly patients who were diagnosed with chronic HF. All patients had SUA levels measured within the first 24 h following admission. Patients with left ventricle EF were categorized as having HF with reduced EF (HFrEF, EF < 40%), HF with mid-range EF (HFmrEF, 40%≦LVEF ≦ 49%) or HF with preserved EF (HFpEF, LVEF ≥ 50%). Endpoints were cardiovascular death, HF rehospitalization, and their composite. The median follow-up period was 18 months. RESULTS: Compared with the lowest SUA quartile, the highest SUA quartile was significantly associated with the endpoints (adjusted HR: 2.404, 95% CI: 1.178-4.906, P = 0.016; HR: 1.418, 95% CI: 1.021-1.971, P = 0.037; HR: 1.439, 95% CI: 1.049-1.972, P = 0.024, respectively). After model adjustment, a significant association of SUA with cardiovascular death and the composite endpoint persisted among HFrEF and HFmrEF patients in the highest SUA quartile (P < 0.05 for all). CONCLUSIONS: In hospitalized elderly patients with chronic HF, SUA is an independent predictor of adverse outcomes, which can be seen in HFrEF and HFmrEF patients.

Origin, evolution, and diversification of the wall-associated kinase gene family in plants.

KEY MESSAGE: The study of the origin, evolution, and diversification of the wall-associated kinase gene family in plants facilitates their functional investigations in the future. Wall-associated kinases (WAKs) make up one subfamily of receptor-like kinases (RLKs), and function directly in plant cell elongation and responses to biotic and abiotic stresses. The biological functions of WAKs have been extensively characterized in angiosperms; however, the origin and evolutionary history of the WAK family in green plants remain unclear. Here, we performed a comprehensive analysis of the WAK family to reveal its origin, evolution, and diversification in green plants. In total, 1061 WAK genes were identified in 37 species from unicellular algae to multicellular plants, and the results showed that WAK genes probably originated before bryophyte differentiation and were widely distributed in land plants, especially angiosperms. The phylogeny indicated that the land plant WAKs gave rise to five clades and underwent lineage-specific expansion after species differentiation. Cis-acting elements and expression patterns analyses of WAK genes in Arabidopsis and rice demonstrated the functional diversity of WAK genes in these two species. Many gene gains and losses have occurred in angiosperms, leading to an increase in the number of gene copies. The evolutionary trajectory of the WAK family during polyploidization was uncovered using Gossypium species. Our results provide insights into the evolution of WAK genes in green plants, facilitating their functional investigations in the future.

Heart failure classifications via non-invasive pressure volume loops from echocardiography.

BACKGROUND: Left ventricular pressure-volume (LV-PV) loops provide comprehensive characterization of cardiovascular system in both health and disease, which are the essential element of the hemodynamic evaluation of heart failure (HF). This study attempts to achieve more detailed HF classifications by non-invasive LV-PV loops from echocardiography and analyzes contribution of parameters to HF classifications. METHODS: Firstly, non-invasive PV loops are established by time-varying elastance model where LV volume curves were extracted from apical-four-chambers view of echocardiographic videos. Then, 16 parameters related to cardiac structure and functions are automatically acquired from PV loops. Next, we applied six machine learning (ML) methods to divide four categories. On this premise, we choose the best performing classifier among machine learning approaches for feature ranking. Finally, we compare the contributions of different parameters to HF classifications. RESULTS: By the experimental, the PV loops were successfully acquired in 1076 cases. When single left ventricular ejection fraction (LVEF) is used for HF classifications, the accuracy of the model is 91.67%. When added parameters extracted from ML-derived LV-PV loops, the classification accuracy is 96.57%, which improved by 5.1%. Especially, our parameters have a great improvement in the classification of non-HF controls and heart failure with preserved ejection fraction (HFpEF). CONCLUSIONS: We successfully presented the classification of HF by machine derived non-invasive LV-PV loops, which has the potential to improve the diagnosis and management of heart failure in clinic. Moreover, ventriculo-arterial (VA) coupling and ventricular efficiency were demonstrated important factors for ML-based HF classification model besides LVEF.

Roles of S-Adenosylmethionine and Its Derivatives in Salt Tolerance of Cotton.

Salinity is a major abiotic stress that restricts cotton growth and affects fiber yield and quality. Although studies on salt tolerance have achieved great progress in cotton since the completion of cotton genome sequencing, knowledge about how cotton copes with salt stress is still scant. S-adenosylmethionine (SAM) plays important roles in many organelles with the help of the SAM transporter, and it is also a synthetic precursor for substances such as ethylene (ET), polyamines (PAs), betaine, and lignin, which often accumulate in plants in response to stresses. This review focused on the biosynthesis and signal transduction pathways of ET and PAs. The current progress of ET and PAs in regulating plant growth and development under salt stress has been summarized. Moreover, we verified the function of a cotton SAM transporter and suggested that it can regulate salt stress response in cotton. At last, an improved regulatory pathway of ET and PAs under salt stress in cotton is proposed for the breeding of salt-tolerant varieties.

[Design and implementation of Internet of Things for emergency medical devices based on cloud-edge-device architecture].

Internet of Things (IoT) technology plays an important role in smart healthcare. This paper discusses IoT solution for emergency medical devices in hospitals. Based on the cloud-edge-device architecture, different medical devices were connected; Streaming data were parsed, distributed, and computed at the edge nodes; Data were stored, analyzed and visualized in the cloud nodes. The IoT system has been working steadily for nearly 20 months since it run in the emergency department in January 2021. Through preliminary analysis with collected data, IoT performance testing and development of early warning model, the feasibility and reliability of the in-hospital emergency medical devices IoT was verified, which can collect data for a long time on a large scale and support the development and deployment of machine learning models. The paper ends with an outlook on medical device data exchange and wireless transmission in the IoT of emergency medical devices, the connection of emergency equipment inside and outside the hospital, and the next step of analyzing IoT data to develop emergency intelligent IoT applications.

[Review of Research Advances in Medical Service Robotics].

With the progress of science and technology and the increase of clinical demand, medical robots have developed rapidly and played a important role in promoting the medical cause. Service robot is a branch of medical robot, which is mainly oriented to medical service and assistance needs, and has been applied in many medical scenarios and achieved demonstration effects. This research first describes the development of medical service robots, and then summarizes the key technologies and clinical applications of robots. Finally, it points out the challenges and directions that medical service robots face at present, and puts forward prospects for their further development in the medical field.

Glucose regulates cotton fiber elongation by interacting with brassinosteroid.

In plants, glucose (Glc) plays important roles, as a nutrient and signal molecule, in the regulation of growth and development. However, the function of Glc in fiber development of upland cotton (Gossypium hirsutum) is unclear. Here, using gas chromatography-mass spectrometry (GC-MS), we found that the Glc content in fibers was higher than that in ovules during the fiber elongation stage. In vitro ovule culture revealed that lower Glc concentrations promoted cotton fiber elongation, while higher concentrations had inhibitory effects. The hexokinase inhibitor N-acetylglucosamine (NAG) inhibited cotton fiber elongation in the cultured ovules, indicating that Glc-mediated fiber elongation depends on the Glc signal transduced by hexokinase. RNA sequencing (RNA-seq) analysis and hormone content detection showed that 150mM Glc significantly activated brassinosteroid (BR) biosynthesis, and the expression of signaling-related genes was also increased, which promoted fiber elongation. In vitro ovule culture clarified that BR induced cotton fiber elongation in a dose-dependent manner. In hormone recovery experiments, only BR compensated for the inhibitory effects of NAG on fiber elongation in a Glc-containing medium. However, the ovules cultured with the BR biosynthetic inhibitor brassinazole and from the BR-deficient cotton mutant pag1 had greatly reduced fiber elongation at all the Glc concentrations tested. This demonstrates that Glc does not compensate for the inhibition of fiber elongation caused by BR biosynthetic defects, suggesting that the BR signaling pathway works downstream of Glc during cotton fiber elongation. Altogether, our study showed that Glc plays an important role in cotton fibre elongation, and crosstalk occurs between Glc and BR signaling during modulation of fiber elongation.

Calsyntenin-1 Promotes Doxorubicin-induced Dilated Cardiomyopathy in Rats.

PURPOSE: Doxorubicin is an important cancer chemotherapeutic agent with severe cardiotoxic effects that eventually lead to dilated cardiomyopathy (DCM). Calsyntenin-1(CLSTN1) plays a critical role in the nervous system, but its relevance in cardiovascular diseases is unknown. We investigated the significance of CLSTN1 in doxorubicin-induced DCM. METHODS: CLSTN1 expression in doxorubicin-induced DCM rats and H9c2 cells was determined using western blotting. To further explore the functions of CLSTN1, a cardiac-specific CLSTN1 overexpression rat model was constructed. The rats were subjected to analysis using echocardiographic, hemodynamic, and electrocardiographic parameters. Potential downstream molecules in CLSTN1 overexpression heart tissue were investigated using proteomics and western blotting. Finally, a knockdown of CLSTN1 was constructed to investigate the rescue function on doxorubicin-induced cell toxicity. RESULTS: CLSTN1 protein expression increased drastically in doxorubicin-induced DCM rats and H9c2 cells. Under doxorubicin treatment, CLSTN1 protein-specific overexpression in the heart muscle promoted cardiac chamber enlargement and heart failure, while the knockdown of CLSTN1 reduced doxorubicin-induced cardiomyocyte toxicity in vitro. At the mechanistic level, overexpression of CLSTN1 downregulated SERCA2 expression and increased the phosphorylation levels of PI3K-Akt and CaMK2. CONCLUSION: Our findings demonstrated that CLSTN1 promotes the pathogenesis of doxorubicin-induced DCM. CLSTN1 could be a therapeutic target to prevent the development of doxorubicin-induced DCM.

Perk heterozygosity ameliorates chronic hypoxia-induced pulmonary hypertension and right ventricular hypertrophy in male rats.

BACKGROUND: Pulmonary hypertension (PH) is a rare and deadly disease characterized by remodeling of the pulmonary vasculature and increased pulmonary artery pressure. hypobaric pulmonary hypertension (HPH) is clinically classified as group 4 of pulmonary hypertension and has a poor prognosis . Previous reports showed that HPH was associated with increased endoplasmic reticulum (ER) stress. The protein kinase R-like endoplasmic reticulum kinase (PERK) is an ER-associated stress protein. However, to date, its physiological effects on HPH and RVF development remains unknown. This study aimed to assess PERK's role in HPH and RV function using in vivo experimental model. METHODS: Perk-knockout male Sprague-Dawley rats were generated and were housed in either a hypobaric chamber or in a normoxic environment. After stimulation for 4 weeks, the hemodynamic parameters of the rats were measured. The heart and lungs were harvested for pathological observation. Blood was collected for the detection of inflammatory indexes. The right ventricle tissue was collected to assess phosphorylated-AKT, ROCK1, ET1, and MMP2 protein expression. RESULTS: WE FIRSTLY GENERATED PERK+/− RATS,: Under normal conditions, Perk+/- rats showed no changes in mPAP(mean pulmonary artery pressure), RVHI(Right ventricular hypertrophy index), cardiomyocyte size and interstitial fibrosis, and pulmonary vascular remodeling. However, in response to chronic hypoxia, Perk+/- rats exhibited decreased in mPAP, RVHI, ventricular fibrosis, and lung remodeling compared to wild-type rats. Perk+/- rats also showed lower expression of phosphor-AKT, ROCK1, ET1, and MMP2 protein in response to chronic hypoxia. CONCLUSIONS: These findings suggest that Perk heterozygosity protects against HPH and Perk may be a suitable target for treating HPH.

The miR-182/Myadm axis regulates hypoxia-induced pulmonary hypertension by balancing the BMP- and TGF-ß-signalling pathways in an SMC/EC-crosstalk-associated manner.

We recently identified oncologic miR-182 as a new regulator of pulmonary artery hypertension (PAH) that targets myeloid-associated differentiation marker (Myadm), which is expressed in bone marrow stem cells and multipotent progenitors. Both miR-182 and Myadm are expressed in the cardiopulmonary system and correlated with the balance between the bone morphogenetic protein (BMP) and the transforming growth factor (TGF)-ß signalling pathways, which are disturbed in PAH. We hypothesize that miR-182/Myadm are involved in BMP-TGF-ß-signalling way in PAH. Hypoxia triggered pathological progression in cardiopulmonary PAH in vivo and in vitro; these changes were accompanied by strongly dowregulated BMP/SMAD1/5/8 expression and enhanced TGF-ß/SMAD2/3 signalling pathway, favouring SMAD4/SMAD2 transcript formation and inhibiting the PAH negative regulator Id1 expression. miR-182 gain-of-function significantly inhibited the pathological progression in hypoxia-induced PAH (HPH) in vivo and in vitro, with a restoration of the balance in BMP-TGF-ß signalling pathway. This recovery was abrogated by overexpression of Myadm. Conversely, loss-of-function of miR-182 increased the pathological progression of HPH followed by severe disturbance of BMP and TGF-ß signal transduction and reduced Id1 expression, which was restored by Myadm knockdown. We also showed that the miR-182/Myadm relate BMP-TGF-ß pathway is associated with NOS3/NO/cGMP via the crosstalk between endothelial cells and smooth muscle cells. Our findings further support the therapeutic significance of miR-182/Myadm in PAH via the balance of BMP- and TGF-ß-associated mechanisms.

Elevated glucose level leads to rapid COVID-19 progression and high fatality.

OBJECTIVES: We aimed to identify high-risk factors for disease progression and fatality for coronavirus disease 2019 (COVID-19) patients. METHODS: We enrolled 2433 COVID-19 patients and used LASSO regression and multivariable cause-specific Cox proportional hazard models to identify the risk factors for disease progression and fatality. RESULTS: The median time for progression from mild-to-moderate, moderate-to-severe, severe-to-critical, and critical-to-death were 3.0 (interquartile range: 1.8-5.5), 3.0 (1.0-7.0), 3.0 (1.0-8.0), and 6.5 (4.0-16.3) days, respectively. Among 1,758 mild or moderate patients at admission, 474 (27.0%) progressed to a severe or critical stage. Age above 60 years, elevated levels of blood glucose, respiratory rate, fever, chest tightness, c-reaction protein, lactate dehydrogenase, direct bilirubin, and low albumin and lymphocyte count were significant risk factors for progression. Of 675 severe or critical patients at admission, 41 (6.1%) died. Age above 74 years, elevated levels of blood glucose, fibrinogen and creatine kinase-MB, and low plateleta count were significant risk factors for fatality. Patients with elevated blood glucose level were 58% more likely to progress and 3.22 times more likely to die of COVID-19. CONCLUSIONS: Older age, elevated glucose level, and clinical indicators related to systemic inflammatory responses and multiple organ failures, predict both the disease progression and the fatality of COVID-19 patients.

Macitentan Attenuates Chronic Mountain Sickness in Rats by Regulating Arginine and Purine Metabolism.

Chronic mountain sickness (CMS) is a high altitude complication with high rates of morbidity and mortality. CMS is characterized by high-altitude polycythemia (HAPC) and high-altitude pulmonary hypertension (HAPH). In this study, macitentan, a dual endothelin receptor antagonist, was used to treat CMS, and the induced metabolomics changes were studied. CMS was induced in rats in a hypobaric hypoxia chamber (simulating a 5500 m plateau) for 4 weeks. Macitentan was administered in the third and fourth weeks (30 mg·kg-1·day-1). At the end of the follow-up period, we performed echocardiography, measured hemodynamic parameters and hematocrit, and performed histological staining. Furthermore, ultraperformance liquid chromatography-mass spectrometry (UPLC-MS)-based metabolic analysis was applied to explore metabolic changes associated with hypobaric hypoxia, with or without macitentan. qRT-PCR and kits for the determination of xanthine oxidase (XO) activity were used for validation experiments. Macitentan was effective in attenuating CMS, including CMS-induced right ventricle hypertrophy, HAPC, and HAPH. The levels of 48 metabolites were significantly changed in the CMS model group compared to the control group. Of these changes, 21 were reversed by treatment with macitentan. Enrichment analysis revealed that the purine metabolism pathway, as well as the arginine/proline metabolism pathway, might be the key pathways adjusted by macitentan. Furthermore, we verified macitentan played a beneficial role by directly regulating the expression of arginine1 and arginine2 in the arginine/proline metabolic pathway, and the activity of xanthine oxidase in the purine metabolic pathway. In conclusion, this study demonstrated that macitentan significantly ameliorated CMS in rats, and the mechanism was attributed to the reversion of the disorder in purine and arginine/proline metabolism, via direct regulation of XO activity and arginine1/2 expression. These findings are expected to provide new insights into the therapeutics and mechanism of macitentan in CMS.

Genome-wide association study reveals the genetic basis of fiber quality traits in upland cotton (Gossypium hirsutum L.).

BACKGROUND: Fiber quality is an important economic trait of cotton, and its improvement is a major goal of cotton breeding. To better understand the genetic mechanisms responsible for fiber quality traits, we conducted a genome-wide association study to identify and mine fiber-quality-related quantitative trait loci (QTLs) and genes. RESULTS: In total, 42 single nucleotide polymorphisms (SNPs) and 31 QTLs were identified as being significantly associated with five fiber quality traits. Twenty-five QTLs were identified in previous studies, and six novel QTLs were firstly identified in this study. In the QTL regions, 822 genes were identified and divided into four clusters based on their expression profiles. We also identified two pleiotropic SNPs. The SNP locus i52359Gb was associated with fiber elongation, strength, length and uniformity, while i11316Gh was associated with fiber strength and length. Moreover, these two SNPs were nonsynonymous and located in genes Gh_D09G2376 and Gh_D06G1908, respectively. RT-qPCR analysis revealed that these two genes were preferentially expressed at one or more stages of cotton fiber development, which was consistent with the RNA-seq data. Thus, Gh_D09G2376 and Gh_D06G1908 may be involved in fiber developmental processes. CONCLUSIONS: The findings of this study provide insights into the genetic bases of fiber quality traits, and the identified QTLs or genes may be applicable in cotton breeding to improve fiber quality.

Ursolic Acid Improves Monocrotaline-Induced Right Ventricular Remodeling by Regulating Metabolism.

Pulmonary arterial hypertension (PAH) is a progressive and malignant disease characterized by pulmonary small arteries and right ventricle (RV) remodeling that can lead to severe RV dysfunction and death. The current therapeutic targets for RV dysfunction, which is strongly linked to mortality, are far from adequate. Therefore, we investigated the effect of ursolic acid (UA), a pentacyclic triterpenoid carboxylic acid, on PAH-induced RV remodeling and its underlying mechanism. We established a PAH model by injecting Sprague Dawley rats with monocrotaline (MCT, 60 mg/kg, ip), as verified by echocardiography and hemodynamic examination. Proteomic analysis was performed on RV samples using a Q Exactive high-field mass spectrometer, followed by KEGG enrichment analysis. The effect of 4 weeks of UA (50 mg/kg) treatment on RV remodeling was explored based on ultrasound, hemodynamic parameters, and histological changes, with the mechanism verified in vivo and in vitro by qRT-PCR and western blotting. RV hypertrophy, fibrosis, increased apoptosis, and abnormal metabolism were induced by MCT and suppressed by UA via a mechanism that changed the expression of key markers. UA also attenuated the Phenylephrine-induced hypertrophy of neonatal rat ventricular myocytes and upregulated peroxisome proliferator-activated receptor-alpha (PPARα), a key fatty acid metabolism regulator, and its downstream factor carnitine palmitoyl transferase 1b. In conclusion, UA exerts beneficial effects on PAH-induced RV dysfunction and remodeling by regulating PPARα-dependent fatty acid metabolism.