Stress-strain characteristics of FRP-PVC confined spontaneous combustion gangue concrete columns.

A total of 40 fiber reinforced polymer (FRP) and polyvinyl chloride (PVC) confined spontaneous combustion gangue coarse-aggregate concrete (SAC) specimens were subjected to axial compression tests and theoretical studies. The main analysis focused on the impact of the replacement rate of spontaneous combustion gangue (SCG), the type of CFRP confinement, and the number of CFRP layers on the axial compression performance of CFRP-PVC confined SAC (CFRP-PVC-SAC). The results show that CFRP-PVC confinement can effectively enhance the axial compressive capacity, axial deformation, and lateral deformation of the components. The increase in strength ranges from 1.68 to 3.48 times, while the increase in strain ranges from 5.21 to 11.98 times. The crack patterns and expansive behavior of the coal gangue concrete under confinement exhibit significant differences compared to ordinary concrete. In addition, based on the framework of the existing FRP-confined plain concrete model, a modified model is established to facilitate prediction of stress-strain relationships for short columns of CFRP-PVC-SAC, with the calculated results in good agreement with experimental values.

Escitalopram-induced QTc prolongation and its relationship with KCNQ1, KCNE1, and KCNH2 gene polymorphisms.

BACKGROUND: Escitalopram can cause prolongation of the QT interval on the electrocardiogram (ECG). However, only some patients get pathological QTc prolongation in clinic. We investigated the influence of KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors on escitalopram-induced QTc prolongation. METHODS: A total of 713 patients prescribed escitalopram were identified and had at least one ECG recording in this retrospective study. 472 patients with two or more ECG data were divided into QTc prolongation (n = 119) and non-prolongation (n = 353) groups depending on the threshold change in QTc of 30 ms above baseline value (∆QTc ≥ 30 ms). 45 patients in the QTc prolongation group and 90 patients in the QTc non-prolongation group were genotyped for 43 single nucleotide polymorphisms (SNPs) of KCNQ1, KCNE1, and KCNH2 genes. RESULTS: Patients with QTc prolongation (∆QTc ≥ 30 ms) got higher escitalopram dose (10.3 mg) than patients without QTc prolongation (9.4 mg), although no significant relationship was found between QTc interval and escitalopram dose in the linear mixed model. Patients who were older/coronary disease/hypertension or carried with KCNE1 rs1805127 C allele, KCNE1 rs4817668 C allele, KCNH2 rs3807372 AG/GG genotype were significantly at risk for QTc prolongation (∆QTc ≥ 30 ms). Concomitant antipsychotic treatment was associated with a longer QTc interval. LIMITATIONS: A relatively small sample size and lack of the blood concentration of escitalopram restricted the accurate relationship between escitalopram dose and QTc interval. CONCLUSION: Our study revealed that KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors provide a complementary effect in escitalopram-induced QTc prolongation.

Association between the upper instrumented vertebra screw angles and proximal junctional complications in patients with de novo degenerative lumbar scoliosis.

OBJECTIVE: The aim of this study was to investigate the impact of upper instrumented vertebra (UIV) screw angles on proximal junctional complications in patients with de novo degenerative lumbar scoliosis (DNDLS). METHODS: A total of 120 patients with DNDLS who underwent posterior long-segment instrumentation and fusion were included. Patients were divided into a proximal junctional kyphosis/failure (PJK/PJF) group and a non-PJK/PJF group. Radiographic parameters were measured, including UIV screw angle, UIV slope, UIV screw slope, fixed segmental angle (FSA), and spinopelvic parameters. Clinical and radiographic data were compared between the two groups. Multivariate logistic regression was used to analyze the independent risk factors of PJK/PJF. Receiver operating characteristic (ROC) curve analysis was used to determine the threshold value to predict PJK/PJF. RESULTS: Thirty-six patients (30.0%) developed PJK or PJF during follow-up. Patients in the PJK/PJF group had a larger postoperative UIV screw angle, a larger postoperative UIV screw slope, and a larger postoperative PJA. A significant increase was observed in UIV screw angle from immediately postoperative assessment to the final follow-up in two groups (p < 0.001). Multivariate logistic analysis indicated that a larger positive postoperative UIV screw angle was an independent risk factor for PJK/PJF (OR 1.546, 95% CI 1.274-1.877). ROC curve analysis indicated that a UIV screw angle ≥ 1° is more likely to develop PJK/PJF. Compared with group A patients (UIV screw angle < 1°), group B patients (UIV screw angle ≥ 1°) had a higher incidence of PJK, PJF, UIV screw loosening, and worse functional scores at the final follow-up. CONCLUSIONS: Avoiding insertion of cranially directed UIV pedicle screws may help prevent the development of PJK and PJF in patients with DNDLS.

The Role of Thoracic Tilt in Identifying Thoracic Compensation and Predicting Proximal Junctional Kyphosis in Degenerative Lumbar Scoliosis.

STUDY DESIGN: A retrospective cohort study of consecutive patients. OBJECTIVE: To investigate the clinical value of thoracic tilt (TT) in characterizing thoracic compensation and predicting proximal junctional kyphosis (PJK) in degenerative lumbar scoliosis (DLS). SUMMARY OF BACKGROUND DATA: Thoracic compensation has been shown to be associated with the development of PJK, while thoracic shape and morphology in patients with DLS remain understudied. METHODS: Patients with DLS who underwent long-segment fusion were divided into a PJK group and a non-PJK group. Asymptomatic elderly volunteers were recruited as healthy controls. Thoracic parameters were measured in both cohorts, including the TT, T1-L1 pelvic angle (TLPA), T12 slope, thoracic kyphosis (TK, T4-T12), global thoracic kyphosis (GTK, T1-T12), and thoracolumbar kyphosis (TLK, T10-L2). Multivariate logistic regression was used to assess the association between TT and the development of PJK, adjusting for confounders. Multivariate linear regression was used to establish the predictive formula for TT. RESULTS: A total of 126 patients with DLS were enrolled, of which 37 (29.4%) developed PJK. Compared with 110 healthy controls, DLS patients had significantly greater TT, TLPA, T12 slope, and TLK as well as smaller TK and GTK (all P <0.001). Preoperatively, the PJK group showed significantly greater TT ( P =0.013), TLPA ( P <0.001), and TLK ( P =0.034) than the non-PJK group. No significant differences were found in TK and GTK before surgery. Postoperatively, the PJK group showed significantly greater TT ( P <0.001), TLPA ( P <0.001), TLK ( P <0.001), and proximal junctional angle ( P <0.001). Multivariate logistic regression analysis showed that greater postoperative TT was associated with the development of PJK. Multivariate linear regression analysis suggested that the regression formula was postoperative TT=0.675×T12slope+0.412×TK+0.158×TLK-4.808 ( R2 =0.643, P <0.001). CONCLUSIONS: The novel sagittal parameter TT can be used for the evaluation of thoracic compensation. Greater preoperative TT might represent a decompensated state of TK. Rebalancing the TT in a sagittal neutral position might help to prevent PJK in patients with DLS.

Interface slip of steel-concrete composite beams reinforced with CFRP sheet under creep effect.

Under the creep action of composite steel and concrete beams reinforced by carbon-fiber-reinforced polymer (CFRP) sheet, the face of the CFRP sheet, steel beam, and concrete slab beam produce relative slip. This slip affects the interface interaction, reduces the bearing capacity and stiffness of the members, and increases the deformation. In this paper, elastic and energy methods are used to analyze the interface forces between steel beams and concrete slabs reinforced by CFRP sheeting under the action of concrete creep. The calculation formulas for interface slip, axial force, and incremental deformation are established. The influence of design parameters on the mechanical properties of the interface is analyzed. Results show that the increments in interface slip, axial force, and deformation are zero on the 28th day. With increasing age, the increments in interface slip, axial force, and deformation gradually increase, and the increase is large in the first 100 days; it basically remains unchanged during the time interval from 100 to 1028 days. When the load increases by 5 N/mm (5 kN), the slip increments increase by approximately 0.004 mm, 0.002 mm, and 0.002 mm. The increments in axial force are approximately 19.4 kN, 15.9 kN, and 16.1 kN. The deformation increments increase by approximately 1.7 mm, 1.1 mm, and 0.6 mm.

Axial Compression Property Test of GFRP Tube-Confined Coal Gangue Steel Fiber Short Concrete Column.

In order to study the axial compression property of a GFRP (glass fiber-reinforced polymer) tube-confined coal gangue steel fiber short concrete column, a test was carried out. The whole process of deformation and failure of the specimen under axial compression load was observed, and the whole process of the stress-strain curve of the specimen was obtained. The results show that the thickness of the GFRP tube has the most significant effect on the mechanical properties. The thickness of the 7 mm tube is 4.3 times the axial ultimate stress and 21.5 times the ultimate strain of the unconstrained short column. Under a certain volume fraction, the ultimate axial strain of the wave fiber is 10.1% higher than that of the hook fiber short column, and the ductility coefficient is 9.6% higher. The fiber volume fraction significantly increases the strain of the short column, and the 3% fiber content is 50.1% higher than that of the non-fiber short column. Finally, three classical strength models of confined concrete were selected for comparative calculation, and a new stress correction model was proposed.

Effective length correction factor of disc-buckle type scaffolding by considering joint bending stiffness and geometrical size.

Based on the theory of sway frame column, the equation of the effective length factor was derived in this paper. Combined with the characteristics of semi-rigid joints, the linear stiffness correction factor of horizontal bar was introduced, and the equation of effective length correction factor was obtained. By using MATLAB programming method, the three-dimensional relationship between the effective length correction factor and the influencing factors was obtained, and the entire process of the stability bearing capacity of the disc-buckle type high support system was described in detail, which improves the stability calculation theory of the high support system. The influence of setting parameters, joint bending stiffness, geometrical size, and material properties on the effective length correction factor is studied. Simultaneously, the joint bending stiffness of semi-rigid joints is determined. The area of the effective length correction factor is analyzed to optimize the design of the setting scheme using horizontal bars and vertical poles of different sizes. The results show that the lift height significantly affects the effective length correction factor during the load bearing process; the factor decreases with increasing lift height. Large transverse and longitudinal distances influence this rule during the initial load bearing. When the joint bending stiffness is less than 100 (kN·m)/rad, the effective length correction factor decreases rapidly with an increase in joint bending stiffness. When the joint bending stiffness is greater than 100 (kN·m)/rad, the effective length correction factor is unaffected by the joint bending stiffness. When the joint bending stiffness is large at initiation of loading, the effective length correction factor decreases with an increase in the outer diameter of the horizontal bar. When the joint bending stiffness is small, the effective length correction factor increases with an increase in the section size of the vertical pole. Therefore, the outer diameter of the horizontal bar significantly affects the effective length correction factor, and a larger diameter is more conducive to the overall stability. Furthermore, the elastic modulus effects the effective length correction factor for the unstable support system.

Combined HTR1A/1B methylation and human functional connectome to recognize patients with MDD.

OBJECTIVES: This study aimed to use a machine-learning method to identify HTR1A/1B methylation and resting-state functional connectivity (rsFC) related to the diagnosis of MDD, then try to build classification models for MDD diagnosis based on the identified features. METHODS: Peripheral blood samples were collected from all recruited participants, and part of the participants underwent the resting-state fMRI scan. Features including HTR1A/1B methylation and rsFC were calculated. Then, the initial feature sets of epigenetics and neuroimaging were separately input into an all-relevant feature selection to generate significant discriminative power for MDD diagnosis. Random forest classifiers were constructed and evaluated based on identified features. In addition, the SHapley Additive exPlanations (SHAP) method was adapted to interpret the diagnostic model. RESULTS: A combination of selected HTR1A/1B methylation and rsFC feature sets achieved better performance than using either one alone - a distinction between MDD and healthy control groups was achieved at 81.78% classification accuracy and 0.8948 AUC. CONCLUSION: A high classification accuracy can be achieved by combining multidimensional information from epigenetics and cerebral radiomic features in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD and further exploring the pathogenesis of MDD.

A Predictive Model of Risk Factors for Conversion From Major Depressive Disorder to Bipolar Disorder Based on Clinical Characteristics and Circadian Rhythm Gene Polymorphisms.

Background: Bipolar disorder (BD) is easy to be misdiagnosed as major depressive disorder (MDD), which may contribute to a delay in treatment and affect prognosis. Circadian rhythm dysfunction is significantly associated with conversion from MDD to BD. So far, there has been no study that has revealed a relationship between circadian rhythm gene polymorphism and MDD-to-BD conversion. Furthermore, the prediction of MDD-to-BD conversion has not been made by integrating multidimensional data. The study combined clinical and genetic factors to establish a predictive model through machine learning (ML) for MDD-to-BD conversion. Method: By following up for 5 years, 70 patients with MDD and 68 patients with BD were included in this study at last. Single nucleotide polymorphisms (SNPs) of the circadian rhythm genes were selected for detection. The R software was used to operate feature screening and establish a predictive model. The predictive model was established by logistic regression, which was performed by four evaluation methods. Results: It was found that age of onset was a risk factor for MDD-to-BD conversion. The younger the age of onset, the higher the risk of BD. Furthermore, suicide attempts and the number of hospitalizations were associated with MDD-to-BD conversion. Eleven circadian rhythm gene polymorphisms were associated with MDD-to-BD conversion by feature screening. These factors were used to establish two models, and 4 evaluation methods proved that the model with clinical characteristics and SNPs had the better predictive ability. Conclusion: The risk factors for MDD-to-BD conversion have been found, and a predictive model has been established, with a specific guiding significance for clinical diagnosis.

Influence and interaction of resting state functional magnetic resonance and tryptophan hydroxylase-2 methylation on short-term antidepressant drug response.

BACKGROUND: Most antidepressants have been developed on the basis of the monoamine deficiency hypothesis of depression, in which neuronal serotonin (5-HT) plays a key role. 5-HT biosynthesis is regulated by the rate-limiting enzyme tryptophan hydroxylase-2 (TPH2). TPH2 methylation is correlated with antidepressant effects. Resting-state functional MRI (rs-fMRI) is applied for detecting abnormal brain functional activity in patients with different antidepressant effects. We will investigate the effect of the interaction between rs-fMRI and TPH2 DNA methylation on the early antidepressant effects. METHODS: A total of 300 patients with major depressive disorder (MDD) and 100 healthy controls (HCs) were enrolled, of which 60 patients with MDD were subjected to rs-fMRI. Antidepressant responses was assessed by a 50% reduction in 17-item Hamilton Rating Scale for Depression (HAMD-17) scores at baseline and after two weeks of medication. The RESTPlus software in MATLAB was used to analyze the rs-fMRI data. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), fractional ALFF (fALFF), and functional connectivity (FC) were used, and the above results were used as regions of interest (ROIs) to extract the average value of brain ROIs regions in the RESTPlus software. Generalized linear model analysis was performed to analyze the association between abnormal activity found in rs-fMRI and the effect of TPH2 DNA methylation on antidepressant responses. RESULTS: Two hundred ninety-one patients with MDD and 100 HCs were included in the methylation statistical analysis, of which 57 patients were included in the further rs-fMRI analysis (3 patients were excluded due to excessive head movement). 57 patients were divided into the responder group (n = 36) and the non-responder group (n = 21). Rs-fMRI results showed that the ALFF of the left inferior frontal gyrus (IFG) was significantly different between the two groups. The results showed that TPH2-1-43 methylation interacted with ALFF of left IFG to affect the antidepressant responses (p = 0.041, false discovery rate (FDR) corrected p = 0.149). CONCLUSIONS: Our study demonstrated that the differences in the ALFF of left IFG between the two groups and its association with TPH2 methylation affect short-term antidepressant drug responses.

Combination of spontaneous regional brain activity and HTR1A/1B DNA methylation to predict early responses to antidepressant treatments in MDD.

BACKGROUND: Antidepressant medications are suggested as the first-line treatment in patients with major depressive disorder (MDD). However, the drug therapy outcomes vary from person to person. The functional activity of the brain and DNA methylation levels correlate with the antidepressant efficacy. To predict the early antidepressant responses in MDD and establish the prediction framework, we aimed to apply multidimensional data based on the resting-state activity of the brain and HTR1A/1B methylation. METHODS: The values of Amplitude of Low-Frequency Fluctuations (ALFF) and regional homogeneity (ReHo) were measured as variables in 116 brain regions along with 181 CpG sites in the promoter region of HTR1A/1B and 11 clinical characteristics. After performing the feature reduction step using the least absolute shrinkage and selection operator (LASSO) method, the selected variables were put into Support Vector Machines (SVM), Random Forest (RF), Naïve Bayes (NB), and logistic regression (LR), consecutively, to construct the prediction models. The models' performance was evaluated by the Leave-One-Out Cross-Validation. RESULTS: The LR model composed of the selected multidimensional features reached a maximum performance of 78.57% accuracy and 0.8340 area under the ROC curve (AUC). The prediction accuracies based on multidimensional datasets were found to be higher than those obtained from the data based only on fMRI or methylation. LIMITATIONS: A relatively small sample size potentially restricted the usage of our prediction framework in clinical applications. CONCLUSION: Our study revealed that combining the data of brain imaging and DNA methylation could provide a complementary effect in predicting early-stage antidepressant outcomes.

The impact of HTR1A and HTR1B methylation combined with stress/genotype on early antidepressant efficacy.

AIMS: Antidepressants are effective in the treatment of major depressive disorder (MDD), while many patients fail to respond to antidepressants. Both 5-HT1A (HTR1A) and 5-HT1B (HTR1B) receptors play an important role in antidepressant activity. Meanwhile, DNA methylation is associated with MDD and antidepressant efficacy. In this study we investigate the influence of HTR1A and HTR1B methylation combined with stress/genotype on antidepressant efficacy. METHODS: A total of 291 MDD patients and 100 healthy controls received the Life Events Scale (LES) and the Childhood Trauma Questionnaire (CTQ) as stress assessment. Eight single nucleotide polymorphisms (SNPs) of HTR1A and HTR1B involved in antidepressant mechanisms were tested. Methylation status in 181 cytosine-phosphate-guanine (CpG) sites of HTR1A and HTR1B were assessed. All MDD patients were divided into response (RES) and non-response (NRES) after 2 weeks of antidepressant treatment. Logistic regression was conducted for interactions between methylation, NLES/CTQ score and genotype. RESULTS: Low HTR1A-2-143 methylation is connected with better antidepressant efficacy in subgroup. Low HTR1A-2-143 methylation combined with low CTQ score is related to better antidepressant efficacy. The interaction between high HTR1B methylation with the rs6298 AA/AG genotype affects better antidepressant efficacy. CONCLUSIONS: HTR1A and HTR1B methylation combined with stress/genotype is associated with antidepressant efficacy.

The relationship of tryptophan hydroxylase-2 methylation to early-life stress and its impact on short-term antidepressant treatment response.

INTRODUCTION: The gene tryptophan hydroxylase 2 (TPH2) encodes the associated rate-limiting enzyme in the biosynthesis 5-HT (serotonin). Early life stress and adult variability in TPH2 can correspond with diminished response to antidepressants for patients with major depressive disorder (MDD). DNA methylation is an epigenetic mechanism mediating gene expression, often tempered by environmental factors. Here, we investigate the influence of TPH2 methylation combined with stress on response to antidepressants within the first two weeks of treatment initiation. METHODS: 291 Han Chinese patients with major depressive disorder and 100 healthy controls comprised the study population. The Life Events Scale (LES) and the Childhood Trauma Questionnaire (CTQ) rated recent and early-life stress. The primary outcome equaled a reduction by ≥ 50% from the Hamilton Depression Rating Scale-17 (HAMD-17) after 2 weeks of treatment. The Illumina HiSeq platform assessed methylation status in 38 CpG sites located upstream and downstream of 11 TPH2 polymorphism sites. RESULTS: In 291 patients and 100 healthy controls, 3 CpG sites predict antidepressant treatment response per sex (TPH2-7-142, p=0.012; TPH2-1-43, p=0.033; TPH2-5-203, p=0.036). High-level CTQ scores relate significantly to DNA hypomethylation at CpG-site TPH2-8-237 in males (false discovery rate [FDR]-corrected p=0.038). Additionally, the interaction of hypermethylation in two CpG sites and elevated early-life stress may reduce antidepressant response (TPH2-5-203, FDR corrected p=0.010; TPH2-10-60, FDR corrected p=0.001). CONCLUSIONS: Our study suggests that TPH2 methylation and its interaction with early-life stress may impair antidepressant response, suggesting that pharmaco-epigenetic studies could identify epigenetic biomarkers for antidepressant response.

Sequential adaptive variables and subject selection for GEE methods.

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process-such as the active-learning methods found in the machine-learning literature-will always be beneficial. In this study, we integrate adaptive sampling and variable selection features into a sequential procedure for modeling correlated response data. Besides reporting the statistical properties of the proposed procedure, we also use both synthesized and real data sets to demonstrate the usefulness of our method.

Positron imaging for verification of irradiation field during radiotherapy.

AIM OF STUDY: The present study was designed to investigate the application of positron images from photonuclear reactions to verify the location of targeted radiation in vivo. MATERIALS AND METHODS: The phantom study was conducted with distilled water, porcine muscle, porcine adipose tissue, and graphite; these subjects were irradiated separately with 50 MV photons generated by an MM50 Racetrack Microtron. The positron emission activity was measured using a Geiger counter, and the radioactive decay curves for each of the irradiated materials were then established. The positron emission tomography (PET) images of the three tissue models were also achieved using the same radiation conditions. The in vivo PET imaging study was also conducted in tumor-bearing rabbits. RESULTS: Our results demonstrated that the PET imaging could be used to verify the position of the irradiation field in vivo. The dose distribution images of photonuclear reactions of 11 C and 15 O were uniform, using 2-Gy 50 MV photons. CONCLUSIONS: The factors influencing the half-life of radiation activity in various tissues were different from the first order kinetic reaction in physics.

Mixing of collinear plane wave pulses in elastic solids with quadratic nonlinearity.

This paper derives a set of necessary and sufficient conditions for generating resonant waves by two propagating time-harmonic plane waves. It is shown that in collinear mixing, a resonant wave can be generated either by a pair of longitudinal waves, in which case the resonant mixing wave is also a longitudinal wave, or by a pair of longitudinal and transverse waves, in which case the resonant wave is a transverse wave. In addition, the paper obtains closed-form analytical solutions to the resonant waves generated by two collinearly propagating sinusoidal pulses. The results show that amplitude of the resonant pulse is proportional to the mixing zone size, which is determined by the spatial lengths of the input pulses. Finally, numerical simulations based on the finite element method and experimental measurements using one-way mixing are conducted. It is shown that both numerical and experimental results agree well with the analytical solutions.