The Relationship of Waist Circumference with the Morbidity of Cardiovascular Diseases and All-Cause Mortality in Metabolically Healthy Individuals: A Population-Based Cohort Study.

Background: This study explores the relationship between waist circumference and morbidity of cardiovascular diseases (CVD) and all-cause mortality in metabolically healthy individuals. Methods: A cohort of 5775 metabolically healthy participants from the 2001-2014 US National Health and Nutrition Examination Survey and National Death Index database was tracked over a median period of 81 months. These participants were divided into quartiles (Q1, Q2, Q3, Q4) based on increasing waist circumference. To compensate for missing covariates, multivariate multiple imputation methods were used. Adjusted logistic regression models were employed to examine the correlation between waist circumference and cardiovascular disease prevalence. Furthermore, Kaplan-Meier curves and multivariable Cox regression analysis were utilized to evaluate the association between waist circumference and all-cause mortality, both qualitatively and quantitatively. Results: The adjusted logistic regression model indicated that a 10 cm increase in waist circumference was associated with a 1.45 times higher prevalence of CVD. As a categorical variable, there was a significant upward trend in CVD incidence across quartiles of waist circumference. The adjusted odds ratios (95% confidence intervals) were 2.41 (1.13-5.53) for Q2, 2.65 (1.18-6.39) for Q3, and 2.53 (0.9-7.44) for Q4, compared to Q1. Notably, individuals with high waist circumference showed significantly poorer survival compared to those with low waist circumference (p = 0.008). The Cox regression analysis revealed that each 10 cm increase in waist circumference contributed to an ~8% increase in all-cause mortality. Conclusions: This study underscores a positive correlation between waist circumference and both CVD morbidity and all-cause mortality in metabolically healthy individuals. The findings highlight the significance of routinely monitoring waist circumference for effective CVD risk management, regardless of metabolic health status.

Diagnosis of preeclampsia using metabolomic biomarkers.

The diagnostic criteria for preeclampsia do not accurately reflect the pathophysiological characteristics of patients with preeclampsia. Conventional biomarkers and diagnostic approaches have proven insufficient to fully comprehend the intricacies of preeclampsia. This study aimed to screen differentially abundant metabolites as candidate biomarkers for preeclampsia. A propensity score matching method was used to perform a 1:1 match between preeclampsia patients (n = 70) and healthy control individuals (n = 70). Based on univariate and multivariate statistical analysis methods, the different characteristic metabolites were screened and identified. Least absolute shrinkage and selection operator (LASSO) regression analysis was subsequently used to further screen for differentially abundant metabolites. A receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic efficacy of the metabolites. A total of 1,630 metabolites were identified and quantified in maternal serum samples. Fifty-three metabolites were significantly increased, and two were significantly decreased in preeclampsia patients. The area under the curve (AUC) of the model composed of isobutyryl-L-carnitine and acetyl-leucine was 0.878, and the sensitivity and specificity in detecting preeclampsia were 81.4% and 87.1%, respectively. There are significant differences in metabolism between preeclampsia patients and healthy pregnant women, and a range of novel biomarkers have been identified. These findings lay the foundation for the use of metabolomic biomarkers for the diagnosis of preeclampsia.

Trends in cardiovascular risk factor prevalence, treatment, and control among US adolescents aged 12 to 19 years, 2001 to March 2020.

BACKGROUND: Early-life cardiovascular risk factors (CVRFs) are known to be associated with target organ damage during adolescence and premature cardiovascular morbidity and mortality during adulthood. However, contemporary data describing whether the prevalence of CVRFs and treatment and control rates have changed are limited. This study aimed to examine the temporal trends in the prevalence, treatment, and control of CVRFs among US adolescents over the past 2 decades. METHODS: This is a serial cross-sectional study using data from nine National Health and Nutrition Examination Survey cycles (January 2001-March 2020). US adolescents (aged 12 to 19 years) with information regarding CVRFs (including hypertension, elevated blood pressure [BP], diabetes, prediabetes, hyperlipidemia, obesity, overweight, cigarette use, inactive physical activity, and poor diet quality) were included. Age-adjusted trends in CVRF prevalence, treatment, and control were examined. Joinpoint regression analysis was performed to estimate changes in the prevalence, treatment, and control over time. The variation by sociodemographic characteristics were also described. RESULTS: A total of 15,155 US adolescents aged 12 to 19 years (representing ≈ 32.4 million people) were included. From 2001 to March 2020, there was an increase in the prevalence of prediabetes (from 12.5% [95% confidence interval (CI), 10.2%-14.9%] to 37.6% [95% CI, 29.1%-46.2%]) and overweight/obesity (from 21.1% [95% CI, 19.3%-22.8%] to 24.8% [95% CI, 21.4%-28.2%]; from 16.0% [95% CI, 14.1%-17.9%] to 20.3% [95% CI, 17.9%-22.7%]; respectively), no improvement in the prevalence of elevated BP (from 10.4% [95% CI, 8.9%-11.8%] to 11.0% [95% CI, 8.7%-13.4%]), diabetes (from 0.7% [95% CI, 0.2%-1.2%] to 1.2% [95% CI, 0.3%-2.2%]), and poor diet quality (from 76.1% [95% CI, 74.0%-78.2%] to 71.7% [95% CI, 68.5%-74.9%]), and a decrease in the prevalence of hypertension (from 8.1% [95% CI, 6.9%-9.4%] to 5.5% [95% CI, 3.7%-7.3%]), hyperlipidemia (from 34.2% [95% CI, 30.9%-37.5%] to 22.8% [95% CI, 18.7%-26.8%]), cigarette use (from 18.0% [95% CI, 15.7%-20.3%] to 3.5% [95% CI, 2.0%-5.0%]), and inactive physical activity (from 83.0% [95% CI, 80.7%-85.3%] to 9.5% [95% CI, 4.2%-14.8%]). Sex and race/ethnicity affected the evolution of CVRF prevalence differently. Whilst treatment rates for hypertension and diabetes did not improve significantly (from 9.6% [95% CI, 3.5%-15.8%] to 6.0% [95% CI, 1.4%-10.6%]; from 51.0% [95% CI, 23.3%-78.7%] to 26.5% [95% CI, 0.0%-54.7%]; respectively), BP control was relatively stable (from 75.7% [95% CI, 56.8%-94.7%] to 73.5% [95% CI, 40.3%-100.0%]), while glycemic control improved to a certain extent, although it remained suboptimal (from 11.8% [95% CI, 0.0%-31.5%] to 62.7% [95% CI, 62.7%-62.7%]). CONCLUSIONS: From 2001 to March 2020, although prediabetes and overweight/obesity increased, hypertension, hyperlipidemia, cigarette use, and inactive physical activity decreased among US adolescents aged 12 to 19 years, whereas elevated BP, diabetes, and poor diet quality remained unchanged. There were disparities in CVRF prevalence and trends across sociodemographic subpopulations. While treatment and control rates for hypertension and diabetes plateaued, BP control were stable, and improved glycemic control was observed.

A stretchable conductive elastomer sensor with self-healing and highly linear strain for human movement detection and pressure response.

Expanding the detection information of wearable smart devices in applications has practical implications for their use in daily life and healthcare. Damage and breakage caused by mechanical injuries and continuous use are unavoidable for polymer matrices so self-healing properties are expected to be conferred on flexible sensors to extend their life and durability. In addition, a good linearity of relative resistance change vs. strain (gauge factor, GF) facilitates the streamlined conversion of electrical signals to 3D information of human motion, whereas existing works on sensors neglect the quantitative analysis of signals. This letter reports a self-healable flexible electronic sensor based on hydrogen bonding and electrostatic interaction between maleic acid-grafted natural rubber (MNR), polyaniline (PANI), and phytic acid (PA). MNR is the flexible matrix and the template for aniline (ANI) polymerization, and PA acts as the dopant and crosslinking agent. The MNR-PANI-PA sensor shows easy self-healing at room temperature, enhanced mechanical behaviour (∼2.5 MPa, 1000% strain), and excellent linearity (GF of 13.8 over 250% strain and GF of 32.0 over 250-100% strain). Due to the highly linear relationship between ΔR/R and bending angle, the electrical signals of human limb movement can output relevant information on bending angle and frequency. By constructing a sensing array, changes in the position and magnitude of applied pressure could also be detected in real-time. Based on these advantages, the MNR-PANI-PA composite sensor is expected to have potential applications in health monitoring, body motion detection, and electronic skins.

Risk factors and prediction model for new-onset hypertensive disorders of pregnancy: a retrospective cohort study.

Background and aims: Hypertensive disorders of pregnancy (HDP) is a significant cause of maternal and neonatal mortality. This study aims to identify risk factors for new-onset HDP and to develop a prediction model for assessing the risk of new-onset hypertension during pregnancy. Methods: We included 446 pregnant women without baseline hypertension from Liyang People's Hospital at the first inspection, and they were followed up until delivery. We collected maternal clinical parameters and biomarkers between 16th and 20th weeks of gestation. Logistic regression was used to determine the effect of the risk factors on HDP. For model development, a backward selection algorithm was applied to choose pertinent biomarkers, and predictive models were created based on multiple machine learning methods (generalised linear model, multivariate adaptive regression splines, random forest, and k-nearest neighbours). Model performance was evaluated using the area under the curve. Results: Out of the 446 participants, 153 developed new-onset HDP. The HDP group exhibited significantly higher baseline body mass index (BMI), weight change, baseline systolic/diastolic blood pressure, and platelet counts than the control group. The increase in baseline BMI, weight change, and baseline systolic and diastolic blood pressure significantly elevated the risk of HDP, with odds ratios and 95% confidence intervals of 1.10 (1.03-1.17), 1.10 (1.05-1.16), 1.04 (1.01-1.08), and 1.10 (1.05-1.14) respectively. Restricted cubic spline showed a linear dose-dependent association of baseline BMI and weight change with the risk of HDP. The random forest-based prediction model showed robust performance with the area under the curve of 0.85 in the training set. Conclusion: This study establishes a prediction model to evaluate the risk of new-onset HDP, which might facilitate the early diagnosis and management of HDP.

Molecular mechanisms and potential therapeutic targets in the pathogenesis of hypertension in visceral adipose tissue induced by a high-fat diet.

Background: Hypertension (HTN) presents a significant global public health challenge with diverse causative factors. The accumulation of visceral adipose tissue (VAT) due to a high-fat diet (HFD) is an independent risk factor for HTN. While various studies have explored pathogenic mechanisms, a comprehensive understanding of impact of VAT on blood pressure necessitates bioinformatics analysis. Methods: Datasets GSE214618 and GSE188336 were acquired from the Gene Expression Omnibus and analyzed to identify shared differentially expressed genes between HFD-VAT and HTN-VAT. Gene Ontology enrichment and protein-protein interaction analyses were conducted, leading to the identification of hub genes. We performed molecular validation of hub genes using RT-qPCR, Western-blotting and immunofluorescence staining. Furthermore, immune infiltration analysis using CIBERSORTx was performed. Results: This study indicated that the predominant characteristic of VAT in HTN was related to energy metabolism. The red functional module was enriched in pathways associated with mitochondrial oxidative respiration and ATP metabolism processes. Spp1, Postn, and Gpnmb in VAT were identified as hub genes on the pathogenic mechanism of HTN. Proteins encoded by these hub genes were closely associated with the target organs-specifically, the resistance artery, aorta, and heart tissue. After treatment with empagliflozin, there was a tendency for Spp1, Postn, and Gpnmb to decrease in VAT. Immune infiltration analysis confirmed that inflammation and immune response may not be the main mechanisms by which visceral adiposity contributes to HTN. Conclusions: Our study pinpointed the crucial causative factor of HTN in VAT following HFD. Spp1, Postn, and Gpnmb in VAT acted as hub genes that promote elevated blood pressure and can be targets for HTN treatment. These findings contributed to therapeutic strategies and prognostic markers for HTN.

SALL4 in gastrointestinal tract cancers: upstream and downstream regulatory mechanisms.

Effective therapeutic targets and early diagnosis are major challenges in the treatment of gastrointestinal tract (GIT) cancers. SALL4 is a well-known transcription factor that is involved in organogenesis during embryonic development. Previous studies have revealed that SALL4 regulates cell proliferation, survival, and migration and maintains stem cell function in mature cells. Additionally, SALL4 overexpression is associated with tumorigenesis. Despite its characterization as a biomarker in various cancers, the role of SALL4 in GIT cancers and the underlying mechanisms are unclear. We describe the functions of SALL4 in GIT cancers and discuss its upstream/downstream genes and pathways associated with each cancer. We also consider the possibility of targeting these genes or pathways as potential therapeutic options for GIT cancers.

Revisiting Waist Circumference: A Hypertension Risk Factor that Requires a More In-depth Understanding.

As a major cause of various cardiovascular diseases, the prevalence of hypertension has been increasing in the past 30 years, leading to significant socioeconomic and health burdens. Obesity is one of the major risk factors for hypertension. Body mass index (BMI) is the most used anthropometric index to measure obesity in clinical practice and to assess the risk of obesity-related diseases. However, obesity is a heterogeneous disease, and the accumulation of fat in different body regions leads to differences in cardiovascular and metabolic risks. BMI only reflects the overall obesity but does not consider the distribution of fat and muscle mass. The limitation of BMI makes it insufficient to assess the risk of hypertension attributed to obesity. In addition, waist circumference is an easily obtainable anthropometric index to evaluate abdominal fat distribution. High waist circumference is an independent risk factor for various cardiovascular diseases and all-cause mortality regardless of BMI. Preliminary data indicate that waist circumference is significantly associated with the risk of hypertension at different BMI levels. However, routine measurement of waist circumference is currently not required in current clinical guidelines or is only recommended for obese populations, indicating an insufficient understanding of waist circumference. In this review, we summarize the measurement methods and diagnostic thresholds of waist circumference for abdominal obesity, the trend of central obesity prevalence, the superiority of waist circumference over other anthropometric indices, and recent cross-sectional and longitudinal studies on the association between obesity and hypertension.

Research on dynamic characteristics of cutter breaking frozen soil and optimal drum rotation speed of the new shaft tunneling machine.

To improve the efficiency of frozen soil excavation, the new shaft tunneling machine was developed. The new shaft tunneling machine exerts pressure on the frozen soil through the cutter under the joint action of its own gravity, the drum rotational force and the inertia force, and the frozen soil is damaged. By unique way of breaking frozen soil to improve the efficiency of frozen soil excavation, the drum rotation speed is one of the factors affecting the performance of frozen soil excavation. This article applies SolidWorks software to establish the model of cutter breaking frozen soil, takes advantage of Hyper Mesh finite element software coupled with LS-DYNA solver to acquire the regular pattern of change in the force change, frozen soil stress-strain and specific energy of cutter crushing frozen soil, etc., which analyzes the destruction of frozen soil when the drum of the new shaft tunneling machine is rotating at the speed of 25-40 rpm. Combine with field test to investigate the mechanism of cutter breaking frozen soil under the optimal drum rotation speed. The investigation results demonstrate that: when frozen soil's self-bearing capacity is lower than the force of cutter, it breaks up and detaches from the soil body, and frozen soil undergoes tensile, compressive and shear damages. For this research, it is instructive for practical engineering.

Continuous ultrasonic ozone coupling technology-assisted control of ceramic membrane fouling coupled enhanced multiphase mixing to treat dye wastewater and CFD flow field simulation.

In this study, ozone catalysts (hydrogenation-modified red mud, HM-RM) successfully prepared by hydrogenation-modification of industrial hazardous solid waste red mud (RM) as a raw material in accordance with the viewpoint of treating waste with waste and using waste. Meanwhile, as for the common phenomenon of membrane fouling, uneven distribution of multiphase solid catalysts and ozone in liquids, the addition of ultrasound can not only disperse materials, but also play a role in online cleaning of ceramic membranes and catalysts. The optimum treatment conditions for Rhodamine B (RhB) solution with volume of 2 L and concentration of 40 mg/L were catalyst concentration of 0.4 mg/L, reaction temperature of 45 °C, ultrasonic time of 1 h, ultrasonic intensity of 600 W, removal rate of RhB was up to 90 %. In addition, the computational fluid dynamics (CFD) simulation method was used to investigate the fluid flow between the two gas-liquid phases and the effect of the negative pressure of the membrane pump on the fluid by the analysis of flow, pressure and ozone flux of the ceramic membrane(CM) reaction apparatus. The CFD simulation results showed that at the inlet gas-liquid flow rate of 3 m/s and the negative pressure of 20,000 Pa, the maximum flow rates of CM-1 were 3 m/s, 0.752 m/s for CM-2, and 0.228 m/s for CM-3, respectively. Vortices, which are beneficial to solid-liquid mixing and gas-liquid mass transfer, formed between the suction port CM-1 of CM-1 and the inlets of CM-2 and CM-3. This discovery is consistent with relevant experimental research results. Significantly higher concentrations of both •OH and dissolved ozone were observed in the US/HM-RM/O3 system compared to other systems, indicating the significant improvement in ozone utilization rate through the application of ultrasound. The superiority of the US/HM-RM/O3 device was demonstrated. The real dye effluent was tested under optimum operating conditions and the results showed that COD and TOC were reduced by 81.34 % and 60.23 % respectively after 180 min of treatment. The above research can provide technical support for the treatment of dye wastewater using Ultrasound-enhanced ozone oxidation ceramic membranes.

The potential mechanisms underlying the modulating effect of perirenal adipose tissue on hypertension: Physical compression, paracrine, and neurogenic regulation.

Hypertension, a prevalent global cardiovascular disease, affects approximately 45.4 % of adults worldwide. Despite advances in therapy, hypertension continues to pose a significant health risk due to inadequate management. It has been established that excessive adiposity contributes majorly to hypertension, accounting for 65 to 75 % of primary cases. Fat depots can be categorised into subcutaneous and visceral adipose tissue based on anatomical and physiological characteristics. The metabolic impact and the risk of hypertension are determined more significantly by visceral fat. Perirenal adipose tissue (PRAT), a viscera enveloping the kidney, is known for its superior vascularisation and abundant innervation. Although traditionally deemed as a mechanical support tissue, recent studies have indicated its contributing potential to hypertension. Hypertensive patients tend to have increased PRAT thickness compared to those without, and there is a positive correlation between PRAT thickness and elevated systolic blood pressure. This review encapsulates the anatomical characteristics and biogenesis of PRAT. We provide an overview of the potential mechanisms where PRAT may modulate blood pressure, including physical compression, paracrine effects, and neurogenic regulation. PRAT has become a promising target for hypertension management, and continuous effort is required to further explore the underlying mechanisms.

Association between P-wave terminal force in lead V1 and extent of left atrial low-voltage substrate in older patients with paroxysmal atrial fibrillation.

BACKGROUND: The P-wave terminal force in lead V1 (PTFV1) is a marker of cardiomyopathy and risk of atrial fibrillation (AF). Low-voltage area (LVA) in the left atrium (LA), which indicates underlying atrial fibrosis, could predict AF recurrence. This study aimed to investigate the correlation between PTFV1 and LVA in older patients with paroxysmal AF. METHODS: From May 1, 2020, to October 31, 2021, a total of 162 patients aged 65-80 years with paroxysmal AF who underwent index ablation procedures were enrolled. PTFV1 was measured in sinus rhythm (SR) using 12-lead electrocardiograms prior to the ablation. Abnormal PTFV1 was defined as a ≥ 4 mVms depression. Additional LVA ablation beyond circumferential pulmonary vein isolation (CPVI) was performed if LVAs were found. RESULTS: Among the 162 patients, 88 had a normal PTFV1 and 74 had an abnormal PTFV1 prior to ablation. There was a significant difference in LVA in patients with and without an abnormal PTFV1 (LVA, 11.0 vs. 5.1 cm2, P < 0.001; LVA burden, 8.9% vs. 4.5%, P < 0.001). PTFV1 and PTAV1 were highest in the upper tertile with extensive LVAs (P < 0.001). Multivariate analysis revealed that abnormal PTFV1 was an independent predictor of LVAs (ß = 4.961; 95% CI, 2.135-7.788; P < 0.001). After a median follow-up of 23 months, the AF-free survival rate was similar between the normal PTFV1 group and the abnormal PTFV1 group (13/88 vs. 12/74, hazard ratio [HR], 0.933 [95% CI, 0.425-2.047]; P = 0.861). CONCLUSIONS: Abnormal PTFV1 at baseline was independently associated with the extent of LVA in older patients with paroxysmal AF.

Low lean mass with obesity in older adults with hypertension: prevalence and association with mortality rate.

BACKGROUND: The influence of sarcopenic obesity (SO) on overall survival in older adults with hypertension has not been addressed. The aim of this study was to investigate the prevalence and mortality predictive value of various body composition phenotypes, focusing mainly on SO, in older adults with hypertension. METHODS: We included 1105 hypertensive patients aged ≥ 60 years from the National Health and Nutrition Examination Survey 1999-2004. Sarcopenia was broadly defined based on low lean mass (LLM; as measured by dual-energy X-ray absorptiometry), and was defined using appendicular lean mass (ALM) divided by height squared (ALM/height2), weight (ALM/weight), and body mass index (BMI; ALM/BMI), respectively. Obesity was defined as BMI ≥ 30 kg/m2, body fat percentage ≥ 30/42%, or waist circumference ≥ 102/88 cm. The prevalence of LLM with obesity was estimated according to each ALM index (ALMI). Multivariable Cox regression analysis and sensitivity analysis were used to examine the association between various body composition phenotypes and all-cause mortality. RESULTS: In older adults with hypertension, the prevalence of LLM with obesity by the ALM/height2 index (9.8%) was lower relative to the ALM/weight (11.7%) and ALM/BMI indexes (19.6%). After a median follow-up of 15.4 years, 642 deaths occurred. In the fully adjusted models, LLM with obesity was significantly associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.14-2.49, P = 0.008; HR 1.48, 95% CI 1.04-2.10, P = 0.028; HR 1.30, 95% CI 1.02-1.66, P = 0.037; respectively) compared with the normal body phenotype, with no statistical differences found in individuals with LLM or obesity alone. Sensitivity analysis confirmed the robustness of the results. CONCLUSIONS: The prevalence of LLM with obesity markedly differed in older adults with hypertension according to the 3 different ALMIs, varying from 9.8%, 11.7%, to 19.6%. Patients with both LLM and obesity had a higher risk of all-cause mortality. Further large, prospective, cohort studies are warranted to validate these findings and uncover underlying mechanisms.

Study on Early Hydration Mechanism of Double-Liquid Grouting Material Modified by Composite Early Strength Agent.

To achieve an adjustable setting time and significantly improved early strength of a new type of sulphoaluminate cement-based double-liquid grouting material (SACDL), the effects of calcium formate, sodium sulfate, lithium carbonate, and a composite early strength agent on the setting hardening and early hydration behavior of SACDL paste were studied by means of setting time, fluidity, compressive strength, and viscosity tests. The results showed that the adsorption and osmosis of calcium formate, the complex decomposition of sodium sulfate, the precipitation polarization of lithium carbonate and the synergistic action of the composite early strength agent could accelerate the early hydration rate of SACDL, shorten the coagulation time, and improve the early strength of SACDL. The composite effect of 0.8% calcium formate and 0.5% sodium sulfate is the most significant in promoting coagulation and early strength; the initial setting time and final setting time of the slurry were shortened to 5 min and 10 min, respectively; and the 3 h compressive strength was capable of reaching 16.7 MPa, 31% higher than that of the blank group. In addition, X-ray diffraction and SEM morphology observation were used to study the composition of the hydration products and the evolution of the microstructure, which revealed the early hydration mechanism of SACDL under the synergistic effect of the composite early strength agent: (1) The solubility of tricalcium aluminate (C3A) and dihydrate gypsum (CaSO4·2H2O) increased under the low content composite early strength agent condition, which increased the ettringite (AFt) formation rate. HCOO- was able to penetrate the hydration layers of tricalcium silicate (C3S) and dicalcium silicate (C2S), accelerating the dissolution of C3S and C2S and promoting the early hydration of SACDL. (2) Under the condition of a high dosage of the composite early strength agent, the further increase in Ca2+ concentration promoted the crystallization nodules and precipitation of CH and accelerated the formation of calcium silicate hydrate (C-S-H) gel. C-S-H was filled between a large number of rod-like AFt crystals, thus making the structure more dense.

Ultra-fast and accurate electron ionization mass spectrum matching for compound identification with million-scale in-silico library.

Spectrum matching is the most common method for compound identification in mass spectrometry (MS). However, some challenges limit its efficiency, including the coverage of spectral libraries, the accuracy, and the speed of matching. In this study, a million-scale in-silico EI-MS library is established. Furthermore, an ultra-fast and accurate spectrum matching (FastEI) method is proposed to substantially improve accuracy using Word2vec spectral embedding and boost the speed using the hierarchical navigable small-world graph (HNSW). It achieves 80.4% recall@10 accuracy (88.3% with 5 Da mass filter) with a speedup of two orders of magnitude compared with the weighted cosine similarity method (WCS). When FastEI is applied to identify the molecules beyond NIST 2017 library, it achieves 50% recall@1 accuracy. FastEI is packaged as a standalone and user-friendly software for common users with limited computational backgrounds. Overall, FastEI combined with a million-scale in-silico library facilitates compound identification as an accurate and ultra-fast tool.

Construction of a web-based dynamic nomogram for predicting the prognosis in acute heart failure.

AIMS: The early identification and appropriate management may provide clinically meaningful and substained benefits in patients with acute heart failure (AHF). This study aimed to develop an integrative nomogram with myocardial perfusion imaging (MPI) for predicting the risk of all-cause mortality in AHF patients. METHODS AND RESULTS: Prospective study of 147 patients with AHF who received gated MPI (59.0 [47.5, 68.0] years; 78.2% males) were enrolled and followed for the primary endpoint of all-cause mortality. We analysed the demographic information, laboratory tests, electrocardiogram, and transthoracic echocardiogram by the least absolute shrinkage and selection operator (LASSO) regression for selection of key features. A multivariate stepwise Cox analysis was performed to identify independent risk factors and construct a nomogram. The predictive values of the constructed model were compared by Kaplan-Meier curve, area under the curves (AUCs), calibration plots, continuous net reclassification improvement, integrated discrimination improvement, and decision curve analysis. The 1, 3, and 5 year cumulative rates of death were 10%, 22%, and 29%, respectively. Diastolic blood pressure [hazard ratio (HR) 0.96, 95% confidence interval (CI) 0.93-0.99; P = 0.017], valvular heart disease (HR 3.05, 95% CI 1.36-6.83; P = 0.007), cardiac resynchronization therapy (HR 0.37, 95% CI 0.17-0.82; P = 0.014), N-terminal pro-B-type natriuretic peptide (per 100 pg/mL; HR 1.02, 95% CI 1.01-1.03; P < 0.001), and rest scar burden (HR 1.03, 95% CI 1.01-1.06; P = 0.008) were independent risk factors for patients with AHF. The cross-validated AUCs (95% CI) of nomogram constructed by diastolic blood pressure, valvular heart disease, cardiac resynchronization therapy, N-terminal pro-B-type natriuretic peptide, and rest scar burden were 0.88 (0.73-1.00), 0.83 (0.70-0.97), and 0.79 (0.62-0.95) at 1, 3, and 5 years, respectively. Continuous net reclassification improvement and integrated discrimination improvement were also observed, and the decision curve analysis identified the greater net benefit of the nomogram across a wide range of threshold probabilities (0-100% at 1 and 3 years; 0-61% and 62-100% at 5 years) compared with dismissing the included factors or using either factor alone. CONCLUSIONS: A predictive nomogram for the risk of all-cause mortality in patients with AHF was developed and validated in this study. The nomogram incorporated the rest scar burden by MPI is highly predictive, and may help to better stratify clinical risk and guide treatment decisions in patients with AHF.

Monocyte-to-lymphocyte ratio predicts mortality and cardiovascular mortality in the general population.

BACKGROUND: Systemic chronic inflammation (SCI) is closely involved in the pathogenesis of many diseases. This study aims to investigate the association between MLR with mortality and cardiovascular disease (CVD) mortality in US adults. METHODS: 35,813 adults were enrolled from the 1999-2014 National Health and Nutrition Examination Survey (NHANES) cycle. Individuals were categorized according to MLR tertiles and followed until 31 December 2019. Kaplan-Meier plots and log-rank tests were utilized to explore survival differences among the MLR tertiles. Adjusted multivariable Cox analysis was employed to investigate the relationship of MLR with mortality and CVD mortality. Restricted cubic spline and subgroup analysis were further used to discern non-linear relationship and the relationship in categories. RESULTS: During a median follow-up of 134 months, 5865 (16.4%) all-cause deaths and 1602 (4.5%) cardiovascular deaths occurred. Kaplan-Meier plots revealed significant differences in all-cause and cardiovascular mortality among the MLR tertiles. In the fully-adjusted Cox regression model, individuals in the highest tertile of MLR had higher risk of mortality (HR = 1.26, 95% CI: 1.17-1.35) and CVD mortality (HR = 1.41, HR, 95% CI: 1.23-1.62) than those in the lowest tertile. The restricted cubic spline exhibited a J-shaped relationship between MLR with mortality and CVD mortality (P for non-linearity <0.001). The further subgroup analysis demonstrated a robust trend across categories. CONCLUSION: Our study demonstrated that increased baseline MLR was positively associated with a higher risk of death in US adults. MLR was a strong independent predictor of mortality and CVD mortality in the general population.

Obesity, malnutrition, and the prevalence and outcome of hypertension: Evidence from the National Health and Nutrition Examination Survey.

Background: Nutritionally unhealthy obesity is a newly introduced phenotype characterized by a combined condition of malnutrition and obesity. This study aims to explore the combined influence of obesity and nutritional status on the prevalence and outcome of hypertension. Methods: Participants collected from the National Health and Nutrition Examination Survey (NHANES) database were divided into four subgroups according to their obesity and nutritional conditions, as defined by waist circumference and serum albumin concentration. The lean-well-nourished was set as the reference group. Logistic regression models were applied to evaluate the hypertension risk. Kaplan-Meier analysis and Cox proportional hazard regression models were used to assess the survival curve and outcome risk of participants with hypertension. Results: A total of 28,554 participants with 10,625 hypertension patients were included in the analysis. The lean-malnourished group showed a lower hypertension risk (odds ratio [OR] 0.85, 95% confidence interval [CI]: 0.77-0.94), while the obese-well-nourished condition elevated the risk (OR 1.47, 95% CI: 1.3-1.67). Two malnourished groups had higher mortality risks (HR 1.42, 95% CI: 1.12-1.80 and HR 1.31, 95% CI: 1.03-1.69 for the lean and obese, respectively) than the reference group. The outcome risk of the obese-well-nourished group (HR 1.02, 95% CI: 0.76-1.36) was similar to the lean-well-nourished. Conclusion: Malnutrition was associated with a lower risk of developing hypertension in both lean and obese participants, but it was associated with a worse outcome once the hypertension is present. The lean-malnourished hypertension patients had the highest all-cause mortality risk followed by the obese-malnourished. The obese-well-nourished hypertension patients showed a similar mortality risk to the lean-well-nourished hypertension patients.

Fusion of Quality Evaluation Metrics and Convolutional Neural Network Representations for ROI Filtering in LC-MS.

Region of interest (ROI) extraction is a fundamental step in analyzing metabolomic datasets acquired by liquid chromatography-mass spectrometry (LC-MS). However, noises and backgrounds in LC-MS data often affect the quality of extracted ROIs. Therefore, developing effective ROI evaluation algorithms is necessary to eliminate false positives meanwhile keep the false-negative rate as low as possible. In this study, a deep fused filter of ROIs (dffROI) was proposed to improve the accuracy of ROI extraction by combining the handcrafted evaluation metrics with convolutional neural network (CNN)-learned representations. To evaluate the performance of dffROI, dffROI was compared with peakonly (CNN-learned representation) and five handcrafted metrics on three LC-MS datasets and a gas chromatography-mass spectrometry (GC-MS) dataset. Results show that dffROI can achieve higher accuracy, better true-positive rate, and lower false-positive rate. Its accuracy, true-positive rate, and false-positive rate are 0.9841, 0.9869, and 0.0186 on the test set, respectively. The classification error rate of dffROI (1.59%) is significantly reduced compared with peakonly (2.73%). The model-agnostic feature importance demonstrates the necessity of fusing handcrafted evaluation metrics with the convolutional neural network representations. dffROI is an automatic, robust, and universal method for ROI filtering by virtue of information fusion and end-to-end learning. It is implemented in Python programming language and open-sourced at https://github.com/zhanghailiangcsu/dffROI under BSD License. Furthermore, it has been integrated into the KPIC2 framework previously proposed by our group to facilitate real metabolomic LC-MS dataset analysis.