LncRNA RP11-301G19.1 is required for the maintenance of vascular smooth muscle cell contractile phenotype via sponging miR-17-5P/ATOH8 axis.

Long noncoding RNAs (LncRNAs) play essential roles in regulating gene expression in various biological processes. However, the function of lncRNAs in vascular smooth muscle cell (VSMC) transformation remains to be explained. In this work, we discover that a new bone marrow protein (BMP) signaling target, lncRNA RP11-301G19.1, is significantly induced in BMP7-treated VSMCs through lncRNA microarray analysis. Addition of BMP signaling inhibitor LDN-193189 attenuates the expression of ACTA2 and SM-22α, as well as the mRNA level of RP11-301G19.1. Furthermore, lncRNA RP11-301G19.1 is critical to the VSMC differentiation and is directly activated by SMAD1/9. Mechanistically, knocking down of RP11-301G19.1 leads to the decrease of ATOH8, another BMP target, while the forced expression of RP11-301G19.1 reactivates ATOH8. In addition, miR-17-5p, a miRNA negatively regulated by BMP-7, contains predicted binding sites for lncRNA RP11-301G19.1 and ATOH8 3'UTR. Accordingly, overexpression of miR-17-5p decreases the levels of them. Together, our results revealed the role of lncRNA RP11-301G19.1 as a miRNA sponge to upregulate ATOH8 in VSMC phenotype transformation.

Wetting Effect Induced Depletion and Adsorption Layers: Diffuse Interface Perspective.

When a multi-component fluid contacts arigid solid substrate, the van der Waals interaction between fluids and substrate induces a depletion/adsorption layer depending on the intrinsic wettability of the system. In this study, we investigate the depletion/adsorption behaviors of A-B fluid system. We derive analytical expressions for the equilibrium layer thickness and the equilibrium composition distribution near the solid wall, based on the theories of de Gennes and Cahn. Our derivation is verified through phase-field simulations, wherein the substrate wettability, A-B interfacial tension, and temperature are systematically varied. Our findings underscore two pivotal mechanisms governing the equilibrium layer thickness. With an increase in the wall free energy, the substrate wettability dominates the layer formation, aligning with de Gennes' theory. When the interfacial tension increases, or temperature rises, the layer formation is determined by the A-B interactions, obeying Cahn's theory. Additionally, we extend our study to non-equilibrium systems where the initial composition deviates from the binodal line. Notably, macroscopic depletion/adsorption layers form on the substrate, which are significantly thicker than the equilibrium microscopic layers. This macroscopic layer formation is attributed to the interplay of phase separation and Ostwald ripening. We anticipate that the present finding could deepen our knowledge on the depletion/adsorption behaviors of immiscible fluids.

Prospective Evaluation of the Peripheral Perfusion Index in Assessing the Organ Dysfunction and Prognosis of Adult Patients With Sepsis in the ICU.

Background: The peripheral perfusion index (PI) reflects microcirculatory blood flow perfusion and indicates the severity and prognosis of sepsis. Method: The cohort comprised 208 patients admitted to the intensive care unit (ICU) with infection, among which 117 had sepsis. Demographics, medication history, ICU variables, and laboratory indexes were collected. Primary endpoints were in-hospital mortality and 28-day mortality. Secondary endpoints included organ function variables (coagulation function, liver function, renal function, and myocardial injury), lactate concentration, mechanical ventilation time, and length of ICU stay. Univariate and multivariate analyses were conducted to assess the associations between the PI and clinical outcomes. Sensitivity analyses were performed to explore the associations between the PI and organ functions in the sepsis and nonsepsis groups. Result: The PI was negatively associated with in-hospital mortality (odds ratio [OR] 0.29, 95% confidence interval [CI] 0.15 to 0.55), but was not associated with 28-day mortality. The PI was negatively associated with the coagulation markers prothrombin time (PT) (ß -0.36, 95% CI -0.59 to 0.13) and activated partial thromboplastin time (APTT) (ß -1.08, 95% CI -1.86 to 0.31), and the myocardial injury marker cardiac troponin I (cTnI) (ß -2085.48, 95% CI -3892.35 to 278.61) in univariate analysis, and with the PT (ß -0.36, 95% CI -0.60 to 0.13) in multivariate analysis. The PI was negatively associated with the lactate concentration (ß -0.57, 95% CI -0.95 to 0.19), mechanical ventilation time (ß -23.11, 95% CI -36.54 to 9.69), and length of ICU stay (ß -1.28, 95% CI -2.01 to 0.55). Sensitivity analyses showed that the PI was significantly associated with coagulation markers (PT and APTT) and a myocardial injury marker (cTnI) in patients with sepsis, suggesting that the associations between the PI and organ function were stronger in the sepsis group than the nonsepsis group. Conclusion: The PI provides new insights for assessing the disease severity, short-term prognosis, and organ function damage in ICU patients with sepsis, laying a theoretical foundation for future research.

Community screening for dementia among older adults in China: a machine learning-based strategy.

BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI). METHODS: The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments. Permutation importance was used to select features. Five ML models using BalanceCascade were applied to predict CI: a support vector machine (SVM), multilayer perceptron (MLP), AdaBoost, gradient boosting decision tree (GBDT), and logistic regression (LR). An AD8 score ≥ 2 was used to define CI as a baseline. SHapley Additive exPlanations (SHAP) values were used to interpret the results of ML models. RESULTS: The first and sixth items of AD8, platelets, waist circumference, body mass index, carcinoembryonic antigens, age, serum uric acid, white blood cells, abnormal electrocardiogram, heart rate, and sex were selected as predictive features. Compared to the baseline (AUC = 0.65), the MLP showed the highest performance (AUC: 0.83 ± 0.04), followed by AdaBoost (AUC: 0.80 ± 0.04), SVM (AUC: 0.78 ± 0.04), GBDT (0.76 ± 0.04). Furthermore, the accuracy, sensitivity and specificity of four ML models were higher than the baseline. SHAP summary plots based on MLP showed the most influential feature on model decision for positive CI prediction was female sex, followed by older age and lower waist circumference. CONCLUSIONS: The diagnostic models of CI applying ML, especially the MLP, were substantially more effective than the traditional AD8 scale with a score of ≥ 2 points. Our findings may provide new ideas for community dementia screening and to promote such screening while minimizing medical and health resources.

Echocardiographic features of right ventricle in septic patients with elevated central venous pressure.

BACKGROUND: Elevated central venous pressure (CVP) is deemed as a sign of right ventricular (RV) dysfunction. We aimed to characterize the echocardiographic features of RV in septic patients with elevated CVP, and quantify associations between RV function parameters and 30-day mortality. METHODS: We retrospectively reviewed a cohort of septic patients with CVP ≥ 8 mmHg in a tertiary hospital intensive care unit. General characteristics and echocardiographic parameters including tricuspid annular plane systolic excursion (TAPSE), pulmonary vascular resistance (PVR) as well as prognostic data were collected. Associations between RV function parameters and 30-day mortality were assessed using Cox regression models. RESULTS: Echocardiography was performed in 244 septic patients with CVP ≥ 8 mmHg. Echocardiographic findings revealed that various types of abnormal RV function can occur individually or collectively. Prevalence of RV systolic dysfunction was 46%, prevalence of RV enlargement was 34%, and prevalence of PVR increase was 14%. In addition, we collected haemodynamic consequences and found that prevalence of systemic venous congestion was 16%, prevalence of RV-pulmonary artery decoupling was 34%, and prevalence of low cardiac index (CI) was 23%. The 30-day mortality of the enrolled population was 24.2%. In a Cox regression analysis, TAPSE (HR:0.542, 95% CI:0.302-0.972, p = 0.040) and PVR (HR:1.384, 95% CI:1.007-1.903, p = 0.045) were independently associated with 30-day mortality. CONCLUSIONS: Echocardiographic findings demonstrated a high prevalence of RV-related abnormalities (RV enlargement, RV systolic dysfunction and PVR increase) in septic patients with elevated CVP. Among those echocardiographic parameters, TAPSE and PVR were independently associated with 30-day mortality in these patients.

RfxCas13d-mediated inhibition of Circ1647 alleviates renal fibrosis via PI3K/AKT signaling pathway.

BACKGROUND: Circular RNAs (CircRNAs) have been shown to be involved in the development of chronic kidney disease (CKD). This study aimed to investigate the role of Circ1647 in renal fibrosis, which is a hallmark of CKD. METHODS: In this study, we established a unilateral ureteral obstruction (UUO) model and delivered Circ1647 RfxCas13d knockdown plasmid into renal parenchymal cells via retrograde injection through the ureter followed by electroporation. After that, the pathological changes were determined by Hematoxylin and Eosin. Meanwhile, Immunohistochemistry, qRT-PCR and Western blot were conducted to assess the degree of fibrosis. In addition, overexpressing of Circ1647 in renal tubular epithelial cells (TCMK1) was performed to investigate the underlying mechanisms of Circ1647. RESULTS: Our results displayed that electroporation-mediated knockdown of Circ1647 by RfxCas13d knockdown plasmid significantly inhibited renal fibrosis in UUO mice as evidenced by reduced expression of fibronectin and α-SMA (alpha-smooth muscle actin). Conversely, overexpression of Circ1647 in TCMK1 cells promoted the fibrosis. In terms of mechanism, Circ1647 may mediate the PI3K/AKT Signaling Pathway as demonstrated by the balance of the phosphorylation of PI3K and AKT in vivo and the aggravated phosphorylation of PI3K and AKT in vitro. These observations were corroborated by the effects of the PI3K inhibitor LY294002, which mitigated fibrosis post Circ1647 overexpression. CONCLUSION: Our study suggests that Circ1647 plays a significant role in renal fibrosis by mediating the PI3K/AKT signaling pathway. RfxCas13d-mediated inhibition of Circ1647 may serve as a therapeutic target for renal fibrosis in CKD.

Accurate and sensitive low-density lipoprotein (LDL) detection based on the proximity ligation assisted rolling circle amplification (RCA).

Metabolic-associated fatty liver disease (MAFLD) is one of the leading causes of mortality from chronic diseases worldwide, and it is strongly linked to dyslipidemia. Dyslipidemia typically presents as an elevated concentration of low density lipoprotein (LDL). Hence, accurate quantification of LDL particles is crucial for predicting the risks of cardiovascular illnesses. Nevertheless, conventional techniques can merely provide indirect measurements of LDL particle concentrations through the detection of cholesterol or proteins within LDL particles, and they often require significant effort and time. Therefore, an accurate and effective method for identifying intact LDL particles is highly desired. We have devised a method that allows for the measurement of LDL concentration without the need for isolation. This method relies on proximity ligation rolling circle amplification (RCA). This technique enables the direct and precise measurement of the concentration of "actual" LDL particles, rather than measuring the cholesterol content inside LDL. It has a detection limit of 7.3 µg dL-1, which also meets the requirements for analyzing lipoproteins in clinical samples. Hence, this platform exhibits immense potential in clinical applications and health management.

Estimated plasma volume status as a simple and accessible predictor of 28-day mortality in septic shock: insights from a retrospective study of the MIMIC-IV database.

Background: Assessing volume status in septic shock patients is crucial for tailored fluid resuscitation. Estimated plasma volume status (ePVS) has emerged as a simple and effective tool for evaluating patient volume status. However, the prognostic value of ePVS in septic shock patients remains underexplored. Methods: The study cohort consisted of septic shock patients admitted to the ICU, sourced from the MIMIC-IV database. Patients were categorized into two groups based on 28-day survival outcomes, and their baseline characteristics were compared. According to the ePVS (6.52 dL/g) with a hazard ratio of 1 in the restricted cubic spline (RCS) analysis, patients were further divided into high and low ePVS groups. A multivariable Cox regression model was utilized to evaluate the association between ePVS and 28-day mortality rate. The Kaplan-Meier survival curve was plotted, and all-cause mortality was compared between the high and low groups using the log-rank test. Results: A total of 7,607 septic shock patients were included in the study, among whom 2,144 (28.2%) died within 28 days. A J-shaped relationship was observed between ePVS at ICU admission and 28-day mortality, with an increase in mortality risk noted when ePVS exceeded 6.52 dL/g. The high ePVS group exhibited notably higher mortality rates compared to the low ePVS group (28-day mortality: 26.2% vs. 30.2%; 90-day mortality: 35% vs. 42.3%). After adjustment for confounding factors, ePVS greater than 6.52 dL/g independently correlated with an increased risk of 28-day mortality (HR: 1.20, 95% CI: 1.10-1.31, p < 0.001) and 90-day mortality (HR: 1.25, 95% CI: 1.15-1.35, p < 0.001). Kaplan-Meier curves demonstrated a heightened risk of mortality associated with ePVS values exceeding 6.52 dL/g. Conclusion: A J-shaped association was observed between ePVS and 28-day mortality in septic shock patients, with higher ePVS levels associated with increased risk of mortality.

The knowledge structure and research trends between light and myopia: A bibliometric analysis from 1981 to 2024.

BACKGROUND: This bibliometric analysis explored the knowledge structure of and research trends in the relationship between light and myopia. METHODS: Relevant literature published from 1981 to 2024 was collected from the Web of Science Core Collection database. Visual maps were generated using CiteSpace and VOSviewer. We analyzed the included studies in terms of the annual publication count, countries, institutional affiliations, prolific authors, source journals, top 10 most cited articles, keyword co-occurrence, and cocitations. RESULTS: A total of 525 papers examining the relationship between light and myopia published between 1981 and 2024 were collected. The United States ranked first in terms of the number of publications and actively engaged in international cooperation with other countries. The New England College of Optometry, which is located in the United States, was the most active institution and ranked first in terms of the number of publications. Schaeffel Frank was the most prolific author. The most active journal in the field was Investigative Ophthalmology & Visual Science. The most frequently cited paper in the included studies was written by Saw, SM and was published in 2002. The most common keywords in basic research included "refractive error," "longitudinal chromatic aberration," and "compensation." The most common keywords in clinical research mainly included "light exposure," "school," and "outdoor activity." The current research hotspots in this field are "progression," "refractive development," and "light exposure." The cocitation analysis generated 17 clusters. CONCLUSION: This study is the first to use bibliometric methods to analyze existing research on the relationship between light and myopia. In recent years, the intensity and wavelength of light have become research hotspots in the field. Further research on light of different intensities and wavelengths may provide new perspectives in the future for designing more effective treatments and interventions to reduce the incidence of myopia.

A Prospective Study of the Association of IL6 with the Critical Unit and Their Effect on in-Hospital Mortality in Critically Ill Patients.

Purpose: We previously proposed a new concept, the "critical unit", which covers the structural integrity and function of mitochondria and endothelium. Injury of the critical unit plays a key role in the development of critical illnesses. High levels of inflammation may lead to abnormalities of the critical unit, which is an important mechanism for critical illnesses, and both inflammation and critical unit dysfunction may affect patient prognosis. Here we evaluated the correlation between interleukin-6 (IL6) and the critical unit biomarkers in critically ill patients and the impact of both on prognosis. Patients and Methods: This study included adult patients admitted to the intensive care unit for various reasons from January 1st to May 31st, 2023. Baseline characteristics, intensive care unit parameters, and laboratory test and outcome data were obtained from the electronic medical records system. Critical unit parameters were measured using polymerase chain reaction and enzyme-linked immunosorbent assay methods. Correlations were examined between IL6, critical unit parameters, and various outcomes. Results: In critically ill patients, IL6 was closely associated with all the critical unit biomarkers (activated partial thromboplastin time, sphingosine 1-phosphate, mitochondrial DNA, mitochondrial fission 1, and Parkin) and the prognoses of patients. A nomogram was constructed using the critical unit biomarkers to predict the in-hospital mortality of critically ill patients. The area under the curve for the mortality prediction model was 0.708. In sensitivity analyses, the predictive effect was better in the non-surgery and tumor groups compared with the surgery and non-tumor groups, with area under the curve values of 0.885 and 0.891, respectively. Conclusion: Our study innovatively integrated mitochondrial and endothelial markers in the critical unit to comprehensively evaluate patient prognosis, which may be a trend in the future assessment of critically ill patients. There are few such studies, and ours may promote the progress of related research.

Can central venous pressure help identify acute right ventricular dysfunction in mechanically ventilated critically ill patients?

OBJECTIVE: To investigate the relationship between central venous pressure (CVP) and acute right ventricular (RV) dysfunction in critically ill patients on mechanical ventilation. METHODS: This retrospective study enrolled mechanically ventilated critically ill who underwent transthoracic echocardiographic examination and CVP monitoring. Echocardiographic indices including tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), and tricuspid lateral annular systolic velocity wave (S') were collected to assess RV function. Patients were then classified into three groups based on their RV function and presence of systemic venous congestion as assessed by inferior vena cava diameter (IVCD) and hepatic vein (HV) Doppler: normal RV function (TAPSE ≥ 17 mm, FAC ≥ 35% and S' ≥9.5 cm/sec), isolated RV dysfunction (TAPSE < 17 mm or FAC < 35% or S' <9.5 cm/sec with IVCD ≤ 20 mm or HV S ≥ D), and RV dysfunction with congestion (TAPSE < 17 mm or FAC < 35% or S' <9.5 cm/sec with IVCD > 20 mm and HV S < D). RESULTS: A total of 518 patients were enrolled in the study, of whom 301 were categorized in normal RV function group, 164 in isolated RV dysfunction group and 53 in RV dysfunction with congestion group. Receiver operating characteristic analysis revealed a good discriminative ability of CVP for identifying patients with RV dysfunction and congestion(AUC 0.839; 95% CI: 0.795-0.883; p < 0.001). The optimal CVP cutoff was 10 mm Hg, with sensitivity of 79.2%, specificity of 69.4%, negative predictive value of 96.7%, and positive predictive value of 22.8%. A large gray zone existed between 9 mm Hg and 12 mm Hg, encompassing 95 patients (18.3%). For identifying all patients with RV dysfunction, CVP demonstrated a lower discriminative ability (AUC 0.616; 95% CI: 0.567-0.665; p < 0.001). Additionally, the gray zone was even larger, ranging from 5 mm Hg to 12 mm Hg, and included 349 patients (67.4%). CONCLUSIONS: CVP may be a helpful indicator of acute RV dysfunction patients with systemic venous congestion in mechanically ventilated critically ill, but its accuracy is limited. A CVP less than10 mm Hg can almost rule out RV dysfunction with congestion. In contrast, CVP should not be used to identify general RV dysfunction.

Associations of low-density lipoprotein cholesterol with all-cause and cause-specific mortality in older adults in China.

CONTEXT: Limited information was available on detailed associations of low-density lipoprotein cholesterol (LDL-C) with all-cause and cause-specific mortality in older adults. METHODS: This prospective cohort study included a representative sample of 211,290 adults aged 65 or older, who participated in Shenzhen Healthy Aging Research 2018-2019. The vital status of the participants by 31 December, 2021 was determined. We estimated the hazard ratios (HR) with 95% confidence intervals for all-cause or cause-specific mortality using multivariable Cox proportional hazards models and Cox models with restricted cubic spline(RCS) . RESULTS: The median follow-up time was 3.08 years. A total of 5,333 participants were confirmed to have died. Among them, 2,303 cardiovascular disease (CVD) deaths and 1,881 cancer deaths occurred. Compared to those with LDL-C of 100-129 mg/dL, the all-cause mortality risk was significantly higher for individuals with LDL-C level that was very low (< 70 mg/dL) or low (70-99 mg/dL). Compared with individuals with the reference LDL-C level, the multivariable-adjusted HR for CVD-specific mortality was 1.327 for those with very low LDL-C level (< 70 mg/dL), 1.437 for those with high LDL-C level (160 mg/dL ≦ LDL-C < 190mg/dL), 1.528 for those with very high LDL-C level (≥ 190 mg/dL). Low LDL-C level (70-99 mg/dL) and very low LDL-C level (< 70 mg/dL) were also associated with increased cancer mortality and other-cause mortality, respectively. The results from RCS curve showed similar results. CONCLUSION: Considering the risk of all-causes mortality and cause-specific mortality, we recommended 100-159 mg/dL as the optimal range of LDL-C among older adults in China.

Integrating multi-task and cost-sensitive learning for predicting mortality risk of chronic diseases in the elderly using real-world data.

BACKGROUND AND OBJECTIVE: Real-world data encompass population diversity, enabling insights into chronic disease mortality risk among the elderly. Deep learning excels on large datasets, offering promise for real-world data. However, current models focus on single diseases, neglecting comorbidities prevalent in patients. Moreover, mortality is infrequent compared to illness, causing extreme class imbalance that impedes reliable prediction. We aim to develop a deep learning framework that accurately forecasts mortality risk from real-world data by addressing comorbidities and class imbalance. METHODS: We integrated multi-task and cost-sensitive learning, developing an enhanced deep neural network architecture that extends multi-task learning to predict mortality risk across multiple chronic diseases. Each patient cohort with a chronic disease was assigned to a separate task, with shared lower-level parameters capturing inter-disease complexities through distinct top-level networks. Cost-sensitive functions were incorporated to ensure learning of positive class characteristics for each task and achieve accurate prediction of the risk of death from multiple chronic diseases. RESULTS: Our study covers 15 prevalent chronic diseases and is experimented with real-world data from 482,145 patients (including 9,516 deaths) in Shenzhen, China. The proposed model is compared with six models including three machine learning models: logistic regression, XGBoost, and CatBoost, and three state-of-the-art deep learning models: 1D-CNN, TabNet, and Saint. The experimental results show that, compared with the other compared algorithms, MTL-CSDNN has better prediction results on the test set (ACC=0.99, REC=0.99, PRAUC=0.97, MCC=0.98, G-means = 0.98). CONCLUSIONS: Our method provides valuable insights into leveraging real-world data for precise multi-disease mortality risk prediction, offering potential applications in optimizing chronic disease management, enhancing well-being, and reducing healthcare costs for the elderly population.