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.

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.

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.

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.

The Association Between Vitamin D Levels and the 10-Year Risk of Atherosclerotic Cardiovascular Disease: A Population-Based Study.

BACKGROUND: The association between vitamin D levels and atherosclerotic cardiovascular disease (ASCVD) risk remains unclear. In this study, the association between serum 25(OH)D and 10-year ASCVD risk was examined in a national sample of middle-aged and older adults. METHODS: Cross-sectional data from the 2009-2014 National Health and Nutrition Examination Survey were analyzed. The Pooled Cohort Equations were used to estimate the risk of a first ASCVD event in 10 years. An adjusted multiple linear regression model was used to investigate the association between serum 25(OH)D and ASCVD risk. In addition, we performed sensitivity analysis and interactive analysis to assess the robustness of associations across different subgroups. RESULTS: A total of 3354 participants were included in this study. The linear regression model indicated that the risk of ASCVD decreased with the increase in serum 25(OH)D. When analyzed as a continuous variable, serum 25(OH)D was significantly associated with the estimated 10-year risk of ASCVD. In the fully adjusted model, each 10-nmol/L increase in serum 25(OH)D reduced the estimated 10-year ASCVD risk by 0.172% ( P < .001). Individuals in the moderate, insufficient, and sufficient vitamin D deficiency groups had a 0.449% ( P = .362), 0.957% ( P = .046), 1.475% ( P = .003) decrease in ASCVD risk, respectively, when a severe vitamin D deficiency group was set as a reference in the fully adjusted model. CONCLUSION: Our data suggest a negative association between vitamin D levels and the predicted 10-year risk of ASCVD. Further studies are required to investigate whether vitamin D supplements could reduce the risk of ASCVD.

An overview: Management of patients with advanced hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has constituted a significant health burden worldwide, and patients with advanced HCC, which is stage C as defined by the Barcelona Clinic Liver Cancer staging system, have a poor overall survival of 6-8 months. Studies have indicated the significant survival benefit of treatment based on sorafenib, lenvatinib, or atezolizumab-bevacizumab with reliable safety. In addition, the combination of two or more molecularly targeted therapies (first- plus second-line) has become a hot topic recently and is now being extensively investigated in patients with advanced HCC. In addition, a few biomarkers have been investigated and found to predict drug susceptibility and prognosis, which provides an opportunity to evaluate the clinical benefits of current therapies. In addition, many therapies other than tyrosine kinase inhibitors that might have additional survival benefits when combined with other therapeutic modalities, including immunotherapy, transarterial chemoembolization, radiofrequency ablation, hepatectomy, and chemotherapy, have also been examined. This review provides an overview on the current understanding of disease management and summarizes current challenges with and future perspectives on advanced HCC.

Trends in general and abdominal obesity in US adults: Evidence from the National Health and Nutrition Examination Survey (2001-2018).

Aim: This study investigates the trend in general obesity and abdominal obesity in US adults from 2001 to 2018. Methods: We included 44,184 adults from the nine cycles of the continuous NHANES (2001-2002, 2003-2004, 2005-2006, 2007-2008, 2009-2010, 2011-2012, 2013-2014, 2015-2016, and 2017-2018). The age-adjusted mean body mass index and waist circumference were calculated, and the sex-specific annual change was estimated by the survey cycle. We used the weighted sex-specific logistic regression models to analyze the prevalence of general obesity and abdominal obesity from 2001 to 2018. The weighted adjusted odds ratio (OR) with a 95% confidence interval (CI) was calculated. Results: Our study showed that general obesity and abdominal obesity account for about 35.48 and 53.13% of the US population. From 2001-2002 to 2017-2018, the age-adjusted prevalence of general obesity increased from 33.09 to 41.36% in females and from 26.88 to 42.43% in males. During 2001-2018, the age-adjusted prevalence of abdominal obesity increased from 57.58 to 67.33% in females and from 39.07 to 49.73% in males. A significant time-dependent increase was observed in the prevalence of general obesity (adjusted OR, 1.007; 95% CI 1.005-1.009, P < 0.001) and abdominal obesity (adjusted OR, 1.006; 95% CI, 1.004-1.008; P < 0.001). Conclusion: General obesity and abdominal obesity are a heavy health burden among US adults, and the increasing trend remains in both males and females from 2001 to 2018.

Integrated identification of key immune related genes and patterns of immune infiltration in calcified aortic valvular disease: A network based meta-analysis.

Background: As the most prevalent valvular heart disease, calcific aortic valve disease (CAVD) has become a primary cause of aortic valve stenosis and insufficiency. We aim to illustrate the roles of immune related genes (IRGs) and immune cells infiltration in the occurrence of CAVD. Methods: Integrative meta-analysis of expression data (INMEX) was adopted to incorporate multiple gene expression datasets of CAVD from Gene Expression Omnibus (GEO) database. By matching the differentially expressed genes (DEGs) to IRGs from "ImmPort" database, differentially expressed immune related genes (DEIRGs) were screened out. We performed enrichment analysis and found that DEIRGs in CAVD were closely related to inflammatory response and immune cells infiltration. We also constructed protein-protein interaction (PPI) network of DEIRGs and identified 5 key DEIRGs in CAVD according to the mixed character calculation results. Moreover, CIBERSORT algorithm was used to explore the profile of infiltrating immune cells in CAVD. Based on Spearman's rank correlation method, correlation analysis between key DEIRGs and infiltrating immune cells was performed. Results: A total of 220 DEIRGs were identified and the enrichment analysis of DEIRGs showed that they were significantly enriched in inflammatory responses. PPI network was constructed and PTPN11, GRB2, SYK, PTPN6 and SHC1 were identified as key DEIRGs. Compared with normal aortic valve tissue samples, the proportion of neutrophils, T cells CD4 memory activated and macrophages M0 was elevated in calcified aortic valves tissue samples, as well as reduced infiltration of macrophages M2 and NK cells activated. Furthermore, key DEIRGs identified in the present study, including PTPN11, GRB2, PTPN6, SYK, and SHC1, were all significantly correlated with infiltration of various immune cells. Conclusion: This meta-analysis suggested that PTPN11, GRB2, PTPN6, SYK, and SHC1 might be key DEIRGs associated with immune cells infiltration, which play a pivotal role in pathogenesis of CAVD.

Prediction of drug-likeness using graph convolutional attention network.

MOTIVATION: The drug-likeness has been widely used as a criterion to distinguish drug-like molecules from non-drugs. Developing reliable computational methods to predict the drug-likeness of compounds is crucial to triage unpromising molecules and accelerate the drug discovery process. RESULTS: In this study, a deep learning method was developed to predict the drug-likeness based on the graph convolutional attention network (D-GCAN) directly from molecular structures. Results showed that the D-GCAN model outperformed other state-of-the-art models for drug-likeness prediction. The combination of graph convolution and attention mechanism made an important contribution to the performance of the model. Specifically, the application of the attention mechanism improved accuracy by 4.0%. The utilization of graph convolution improved the accuracy by 6.1%. Results on the dataset beyond Lipinski's rule of five space and the non-US dataset showed that the model had good versatility. Then, the billion-scale GDB-13 database was used as a case study to screen SARS-CoV-2 3C-like protease inhibitors. Sixty-five drug candidates were screened out, most substructures of which are similar to these of existing oral drugs. Candidates screened from S-GDB13 have higher similarity to existing drugs and better molecular docking performance than those from the rest of GDB-13. The screening speed on S-GDB13 is significantly faster than screening directly on GDB-13. In general, D-GCAN is a promising tool to predict the drug-likeness for selecting potential candidates and accelerating drug discovery by excluding unpromising candidates and avoiding unnecessary biological and clinical testing. AVAILABILITY AND IMPLEMENTATION: The source code, model and tutorials are available at https://github.com/JinYSun/D-GCAN. The S-GDB13 database is available at https://doi.org/10.5281/zenodo.7054367. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Circulating Tumor Cells and Breast Cancer Metastasis: From Enumeration to Somatic Mutational Profile.

Aims: This study investigates the association between circulating tumor cells (CTCs) and breast cancer metastasis. Methods: A retrospective study was conducted using patients with histologically confirmed breast cancer recruited from the First Affiliated Hospital of Nanjing Medical University during the period of August 2017−October 2020. We used adjusted logistic regression, the random forest algorithm, and sensitivity analysis to study the association between CTC enumeration and tumor metastasis. Further, we performed next-generation sequencing (NGS) on the CTCs obtained from two patients with breast cancer brain metastasis. Results: A total of 41 out of 116 enrolled patients were identified with tumor metastasis. CTC enumeration was significantly higher in patients with liver metastasis than in those without liver metastasis. Patients with CTCs ≥ 5 exhibited a higher risk of tumor metastasis than those with CTCs < 5 in the adjusted model (odds ratios (OR) = 6.25, 95% confidence interval (CI) = 2.63−15.58). The random forest model identified CTC enumeration as a significant metastasis-related variable with the highest mean decrease accuracy and mean decrease Gini score. No significant association was found between CTCs and visceral metastasis with an OR of 1.29 (95% CI = 0.98−2.05, p = 0.232). Upon further investigating organ-specific metastasis, we found that patients with high CTC levels were more likely to develop liver metastasis (OR = 4.87, 95% CI = 1.34−20.17, p = 0.021). The NGS study of CTCs identified a total of 120 indel mutations (e.g., CNGB1, NTSR1, ZG16). The enriched biological processes were mechanoreceptor differentiation and macrophage activation involved in the immune response. The enriched KEGG pathways included focal adhesion, the PI3K-Akt signaling pathway, and microRNAs involved in cancer. Conclusions: Our study revealed that CTCs ≥ 5 are a risk factor for tumor metastasis in breast cancer patients. In addition, we reported that CTCs ≥ 5 might be associated with a higher risk of liver metastasis in patients with metastatic breast cancer. We have provided the mutational profiles of CTCs based on next-generation sequencing.

Deep-Learning-Based Detection of Paroxysmal Supraventricular Tachycardia Using Sinus-Rhythm Electrocardiograms.

BACKGROUND: Paroxysmal supraventricular tachycardia (PSVT) is a common arrhythmia associated with palpitation and a decline in quality of life. However, it is undetectable with sinus-rhythmic ECGs when patients are not in the symptomatic onset stage. METHODS: In the current study, a convolution neural network (CNN) was trained with normal-sinus-rhythm standard 12-lead electrocardiographs (ECGs) of negative control patients and PSVT patients to identify patients with unrecognized PSVT. PSVT refers to atrioventricular nodal reentry tachycardia or atrioventricular reentry tachycardia based on a concealed accessory pathway as confirmed by electrophysiological procedure. Negative control group data were obtained from 5107 patients with at least one normal sinus-rhythmic ECG without any palpitation symptoms. All ECGs were randomly allocated to the training, validation and testing datasets in a 7:1:2 ratio. Model performance was evaluated on the testing dataset through F1 score, overall accuracy, area under the curve, sensitivity, specificity and precision. RESULTS: We retrospectively enrolled 407 sinus-rhythm ECGs of PSVT procedural patients and 1794 ECGs of control patients. A total of 2201 ECGs were randomly divided into training (n = 1541), validation (n = 220) and testing (n = 440) datasets. In the testing dataset, the CNN algorithm showed an overall accuracy of 95.5%, sensitivity of 90.2%, specificity of 96.6% and precision of 86.0%. CONCLUSION: Our study reveals that a well-trained CNN algorithm may be a rapid, effective, inexpensive and reliable method to contribute to the detection of PSVT.