KbhbXG: A Machine learning architecture based on XGBoost for prediction of lysine ß-Hydroxybutyrylation (Kbhb) modification sites.

Lysine ß-hydroxybutyrylation is an important post-translational modification (PTM) involved in various physiological and biological processes. In this research, we introduce a novel predictor KbhbXG, which utilizes XGBoost to identify ß-hydroxybutyrylation modification sites based on protein sequence information. The traditional experimental methods employed for the identification of ß-hydroxybutyrylated sites using proteomic techniques are both costly and time-consuming. Thus, the development of computational methods and predictors can play a crucial role in facilitating the rapid identification of ß-hydroxybutyrylation sites. Our proposed KbhbXG model first utilizes machine learning algorithm XGBoost to predict ß-hydroxybutyrylation modification sites. On the independent test set, KbhbXG achieves an accuracy of 0.7457, specificity of 0.7771, and an impressive area under the curve (AUC) score of 0.8172. The high AUC score achieved by our method demonstrates its potential for effectively identifying novel ß-hydroxybutyrylation sites, thereby facilitating further research and exploration of the ß-hydroxybutyrylation process. Also, functional analyses have revealed that different organisms preferentially engage in distinct biological processes and pathways, which can provide valuable insights for understanding the mechanism of ß-hydroxybutyrylation and guide experimental verification. To promote transparency and reproducibility, we have made both the codes and dataset of KbhbXG publicly available. Researchers interested in utilizing our proposed model can access these resources at https://github.com/Lab-Xu/KbhbXG.

Leveraging machine learning for prediction of antibiotic resistance genes post thermal hydrolysis-anaerobic digestion in dairy waste.

Anaerobic digestion holds promise as a method for removing antibiotic resistance genes (ARGs) from dairy waste. However, accurately predicting the efficiency of ARG removal remains a challenge. This study introduces a novel appproach utilizing machine learning to forecast changes in ARG abundances following thermal hydrolysis-anaerobic digestion (TH-AD) treatment. Through network analysis and redundancy analyses, key determinants of affect ARG fluctuations were identified, facilitating the development of machine learning models capable of accurately predicting ARG changes during TH-AD processes. The decision tree model demonstrated impressive predictive power, achieving an impessive R2 value of 87% against validation data. Feature analysis revealed that the genes intI2 and intI1 had a critical impact on the absolute abundance of ARGs. The predictive model developed in this study offers valuable insights for improving operational and managerial practices in dairy waste treatment facilities, with the ultimate goal of mitigating the spread of antibiotic resistance.

Altered gray matter volume in children with newly diagnosed type 1 diabetes mellitus.

BACKGROUND: Type 1 diabetes mellitus (T1DM) affects the development of cognitive function in children, which may be due to deficits in brain structures or functions. It is unclear whether children with T1DM experience alterations in the gray matter (GM) structure at the initial stages of the disease. This study investigated GM structure alterations in children with newly diagnosed T1DM. METHODS: Based on 3D T1-weighted MR images, we investigated the gray matter volume (GMV) of 35 newly diagnosed T1DM children and 35 age- and sex-matched healthy controls using voxel-based morphometry. The brain regions with significant differences in GMV between the newly diagnosed T1DM children and the controls were extracted and the correlation with clinical data was assessed. RESULTS: Compared with the control group, children with newly diagnosed T1DM had a lower GMV in the right inferior and middle temporal gyri, right lingual gyrus, and left superior frontal gyrus. In T1DM subjects, the GMV of the right middle temporal gyrus was positively correlated with IQ but was negatively correlated with HbA1c. CONCLUSIONS: Our findings provide compelling evidence that GM abnormalities occur during early disease stages in T1DM children, which may be a potential neurobiological mechanism underlying cognitive deficits. IMPACT: Using an efficient method to analyze gray matter changes in T1DM is very important. The anterior, posterior, and temporal brain regions are susceptible to T1DM in children. Recent glucose variability may affect regional gray matter volume in children with newly diagnosed T1DM. Structural changes were documented in the gray matter of the brain even at the early stages of the disease in children with T1DM.

Penalty Virtual Element Method for the 3D Incompressible Flow on Polyhedron Mesh.

In this paper, a penalty virtual element method (VEM) on polyhedral mesh for solving the 3D incompressible flow is proposed and analyzed. The remarkable feature of VEM is that it does not require an explicit computation of the trial and test space, thereby bypassing the obstacle of standard finite element discretizations on arbitrary mesh. The velocity and pressure are approximated by the practical significative lowest equal-order virtual element space pair (Xh,Qh) which does not satisfy the discrete inf-sup condition. Combined with the penalty method, the error estimation is proved rigorously. Numerical results on the 3D polygonal mesh illustrate the theoretical results and effectiveness of the proposed method.

Linear Full Decoupling, Velocity Correction Method for Unsteady Thermally Coupled Incompressible Magneto-Hydrodynamic Equations.

We propose and analyze an effective decoupling algorithm for unsteady thermally coupled magneto-hydrodynamic equations in this paper. The proposed method is a first-order velocity correction projection algorithms in time marching, including standard velocity correction and rotation velocity correction, which can completely decouple all variables in the model. Meanwhile, the schemes are not only linear and only need to solve a series of linear partial differential equations with constant coefficients at each time step, but also the standard velocity correction algorithm can produce the Neumann boundary condition for the pressure field, but the rotational velocity correction algorithm can produce the consistent boundary which improve the accuracy of the pressure field. Thus, improving our computational efficiency. Then, we give the energy stability of the algorithms and give a detailed proofs. The key idea to establish the stability results of the rotation velocity correction algorithm is to transform the rotation term into a telescopic symmetric form by means of the Gauge-Uzawa formula. Finally, numerical experiments show that the rotation velocity correction projection algorithm is efficient to solve the thermally coupled magneto-hydrodynamic equations.

Can lymphovascular invasion be predicted by contrast-enhanced CT imaging features in patients with esophageal squamous cell carcinoma? A preliminary retrospective study.

BACKGROUND: To investigate the value of contrast-enhanced CT (CECT)-derived imaging features in predicting lymphovascular invasion (LVI) status in esophageal squamous cell carcinoma (ESCC) patients. METHODS: One hundred and ninety-seven patients with postoperative pathologically confirmed esophageal squamous cell carcinoma treated in our hospital between January 2017 and January 2019 were enrolled in our study, including fifty-nine patients with LVI and one hundred and thirty-eight patients without LVI. The CECT-derived imaging features of all patients were analyzed. The CECT-derived imaging features were divided into quantitative features and qualitative features. The quantitative features consisted of the CT attenuation value of the tumor (CTVTumor), the CT attenuation value of the normal esophageal wall (CTVNormal), the CT attenuation value ratio of the tumor-to-normal esophageal wall (TNR), the CT attenuation value difference between the tumor and normal esophageal wall (ΔTN), the maximum thickness of the tumor measured by CECT (Thickness), the maximum length of the tumor measured by CECT (Length), and the gross tumor volume measured by CECT (GTV). The qualitative features consisted of an enhancement pattern, tumor margin, enlarged blood supply or drainage vessels to the tumor (EVFDT), and tumor necrosis. For the clinicopathological characteristics and CECT-derived imaging feature analysis, the chi-squared test was used for categorical variables, the Mann-Whitney U test was used for continuous variables with a nonnormal distribution, and the independent sample t-test was used for the continuous variables with a normal distribution. The trend test was used for ordinal variables. The association between LVI status and CECT-derived imaging features was analyzed by univariable logistic analysis, followed by multivariable logistic regression and receiver operating characteristic (ROC) curve analysis. RESULTS: The CTVTumor, TNR, ΔTN, Thickness, Length, and GTV in the group with LVI were higher than those in the group without LVI (P < 0.05). A higher proportion of patients with heterogeneous enhancement pattern, irregular tumor margin, EVFDT, and tumor necrosis were present in the group with LVI (P < 0.05). As revealed by the univariable logistic analysis, the CECT-derived imaging features, including CTVTumor, TNR, ΔTN and enhancement pattern, Thickness, Length, GTV, tumor margin, EVFDT, and tumor necrosis were associated with LVI status (P < 0.05). Only the TNR (OR 8.655; 95% CI 2.125-37.776), Thickness (OR 6.531; 95% CI 2.410-20.608), and tumor margin (OR 4.384; 95% CI 2.004-9.717) were independent risk factors for LVI in the multivariable logistic regression analysis. The ROC curve analysis incorporating the above three CECT-derived imaging features showed that the area under the curve obtained by the multivariable logistic regression model was 0.820 (95% CI 0.754-0.885). CONCLUSION: The CECT-derived imaging features, including TNR, Thickness, tumor margin, and their combination, can be used as predictors of LVI status for patients with ESCC.

Optimal Convergence Analysis of Two-Level Nonconforming Finite Element Iterative Methods for 2D/3D MHD Equations.

Several two-level iterative methods based on nonconforming finite element methods are applied for solving numerically the 2D/3D stationary incompressible MHD equations under different uniqueness conditions. These two-level algorithms are motivated by applying the m iterations on a coarse grid and correction once on a fine grid. A one-level Oseen iterative method on a fine mesh is further studied under a weak uniqueness condition. Moreover, the stability and error estimate are rigorously carried out, which prove that the proposed methods are stable and effective. Finally, some numerical examples corroborate the effectiveness of our theoretical analysis and the proposed methods.

Recovery-Based Error Estimator for Natural Convection Equations Based on Defect-Correction Methods.

In this paper, we propose an adaptive defect-correction method for natural convection (NC) equations. A defect-correction method (DCM) is proposed for solving NC equations to overcome the convection dominance problem caused by a high Rayleigh number. To solve the large amount of computation and the discontinuity of the gradient of the numerical solution, we combine a new recovery-type posteriori estimator in view of the gradient recovery and superconvergent theory. The presented reliability and efficiency analysis shows that the true error can be effectively bounded by the recovery-based error estimator. Finally, the stability, accuracy and efficiency of the proposed method are confirmed by several numerical investigations.

Finding Key Factors for Efficient Water and Methanol Activation at Metals, Oxides, MXenes, and Metal/Oxide Interfaces.

Activating water and methanol is crucial in numerous catalytic, electrocatalytic, and photocatalytic reactions. Despite extensive research, the optimal active sites for water/methanol activation are yet to be unequivocally elucidated. Here, we combine transition-state searches and electronic charge analyses on various structurally different materials to identify two features of favorable O-H bond cleavage in H2O, CH3OH, and hydroxyl: (1) low barriers appear when the charge of H moieties remains approximately constant during the dissociation process, as observed on metal oxides, MXenes, and metal/oxide interfaces. Such favorable kinetics is closely related to adsorbate/substrate hydrogen bonding and is enhanced by nearly linear O-H-O angles and short O-H distances. (2) Fast dissociation is observed when the rotation of O-H bonds is facile, which is favored by weak adsorbate binding and effective orbital overlap. Interestingly, we find that the two features are energetically proportional. Finally, we find conspicuous differences between H2O/CH3OH and OH activation, which hints toward the use of carefully engineered interfaces.

A Modular Grad-Div Stabilization Method for Time-Dependent Thermally Coupled MHD Equations.

In this paper, we consider a fully discrete modular grad-div stabilization algorithm for time-dependent thermally coupled magnetohydrodynamic (MHD) equations. The main idea of the proposed algorithm is to add an extra minimally intrusive module to penalize the divergence errors of velocity and improve the computational efficiency for increasing values of the Reynolds number and grad-div stabilization parameters. In addition, we provide the unconditional stability and optimal convergence analysis of this algorithm. Finally, several numerical experiments are performed and further indicated these advantages over the algorithm without grad-div stabilization.

Error Analysis of a PFEM Based on the Euler Semi-Implicit Scheme for the Unsteady MHD Equations.

In this article, we mainly consider a first order penalty finite element method (PFEM) for the 2D/3D unsteady incompressible magnetohydrodynamic (MHD) equations. The penalty method applies a penalty term to relax the constraint "∇·u=0", which allows us to transform the saddle point problem into two smaller problems to solve. The Euler semi-implicit scheme is based on a first order backward difference formula for time discretization and semi-implicit treatments for nonlinear terms. It is worth mentioning that the error estimates of the fully discrete PFEM are rigorously derived, which depend on the penalty parameter ϵ, the time-step size τ, and the mesh size h. Finally, two numerical tests show that our scheme is effective.

Serum uric acid and its change with the risk of type 2 diabetes: A prospective study in China.

OBJECTIVE: To assess the association of baseline uric acid levels and their changes from baseline to Year 1 with the risk of type 2 diabetes. RESEARCH DESIGN AND METHODS: This study cohort included 9471 subjects without a history of diabetes at baseline. The incident diabetes was diagnosed according to the American Diabetes Association standard. RESULTS: During a mean follow-up of 2.9 years, we identified 762 type 2 diabetes cases. Multivariate-adjusted hazard ratios (HRs) of diabetes across baseline tertiles of serum uric acid were 1.00, 1.15, and 1.32 (P for trend = 0.018), respectively. Participants with hyperuricemia compared with those without had a 1.20-fold (95% confidence interval [CI] 1.01-1.44) risk of diabetes. When uric acid was examined as a continuous variable, multivariable-adjusted HR of diabetes for each 1 mg/dL (60 µmol/L) increase in serum uric acid was 1.09 (95% CI 1.03-1.15). Compared with subjects with stable serum uric acid from baseline to Year 1 (±10%), those with uric acid gain ≥30% had a 30% (95% CI 1.01-1.79) increased risk of diabetes and those with uric acid loss ≥10% had a 21% (95% 0.62-0.99) decreased risk of diabetes. This positive association between baseline serum uric acid and diabetes risk was consistent among subjects younger and older than 45 years, non-obese and obese participants, and men. CONCLUSIONS: High level of baseline serum uric acid and serum uric acid gain from baseline to Year 1 are associated with an increased risk of type 2 diabetes among Chinese adults.

Copper-catalyzed chemoselective C-H functionalization of quinoxalin-2(1H)-ones with hexafluoroisopropanol.

An unexpected three-component reaction of quinoxalin-2(1H)-ones, tert-butyl peroxybenzoate (TBPB), and hexafluoroisopropanol (HFIP) is described. Under CuBr-catalyzed and TBPB-oxidized conditions, a variety of hydroxyhexafluoroisobutylated quinoxalin-2(1H)-ones were formed. Furthermore, the first hexafluoroisopropoxylation of the quinoxalin-2(1H)-ones with HFIP is also demonstrated with Cu2O as the catalyst and PhI(OAc)2 as the oxidant. These new transformations of HFIP furnish previously unknown and potentially useful fluorinated quinoxalin-2(1H)-one derivatives.

Disrupted Regional Cerebral Blood Flow in Children With Newly-Diagnosed Type 1 Diabetes Mellitus: An Arterial Spin Labeling Perfusion Magnetic Resonance Imaging Study.

Object: Diabetes is associated with cerebral vascular dysfunction and increased vascular cognitive impairment. The objective of this study was to use arterial spin labeling (ASL) perfusion-weighted magnetic resonance imaging to investigate whether cerebral perfusion was changed in newly-diagnosed children with type 1 diabetes mellitus (T1DM) and the possible relationship between aberrant cerebral blood flow (CBF) with cognitive as well as clinical variables. Methods: Between January 2017 and February 2018, 34 children with newly-diagnosed T1DM and 34 age, gender, and education-matched healthy controls were included. Three dimensional pseudo-continuous ASL perfusion MRI was used to evaluate CBF. A conventional T2WI sequence was added to exclude intracranial disease. Regions with CBF differences between T1DM children and the controls were detected via voxel-wise comparisons in REST software. Associations among the result of neuropsychological test, clinical variables, and CBF values of different brains were investigated by using partial correlation analysis. Results: Compared with the controls, T1DM children show decreased CBF in the left calcarine and postcentral gyrus, and right precentral gyrus. The perfusion in the postcentral gyrus was positively correlated with IQ performance. No significant correlations were found between CBF and HbA1c, blood glucose level before imaging and IQ in other brain regions in T1DM children. Conclusion: There is an abnormal cerebral perfusion in children with newly diagnosed T1DM. The visual and sensorimotor areas are brain areas where perfusion is prone to change at the beginning of T1DM. Our study provided clues for cerebral pathophysiological changes in the initial stage of T1DM.

Trends in C-O and N-O bond scission on rutile oxides described using oxygen vacancy formation energies.

Reactivity trends on transition metals can generally be understood through the d-band model, but no analogous theory exists for transition metal oxides. This limits the generality of analyses in oxide-based catalysis and surface chemistry and has motivated the appearance of numerous descriptors. Here we show that oxygen vacancy formation energy (ΔE Vac) is an inexpensive yet accurate and general descriptor for trends in transition-state energies, which are usually difficult to assess. For rutile-type oxides (MO2 with M = 3d metals from Ti to Ni), we show that ΔE Vac captures the trends in C-O and N-O bond scission of CO2, CH3OH, N2O, and NH2OH at oxygen vacancies. The proportionality between ΔE Vac and transition-state energies is rationalized by analyzing the oxygen-metal bonds, which change from ionic to covalent from TiO2 to NiO2. ΔE Vac may be used to design oxide catalysts, in particular those where lattice oxygen and/or oxygen vacancies participate in the catalytic cycles.

Highly Selective Production of Ethylene by the Electroreduction of Carbon Monoxide.

Conversion of carbon monoxide to high value-added ethylene with high selectivity by traditional syngas conversion process is challenging because of the limitation of Anderson-Schulz-Flory distribution. Herein we report a direct electrocatalytic process for highly selective ethylene production from CO reduction with water over Cu catalysts at room temperature and ambient pressure. An unprecedented 52.7 % Faradaic efficiency of ethylene formation is achieved through optimization of cathode structure to facilitate CO diffusion at the surface of the electrode and Cu catalysts to enhance the C-C bond coupling. The highly selective ethylene production is almost without other carbon-based byproducts (e.g. C1 -C4 hydrocarbons and CO2 ) and avoids the drawbacks of the traditional Fischer-Tropsch process that always delivers undesired products. This study provides a new and promising strategy for highly selective production of ethylene from the abundant industrial CO.

[Expression of MiR101 and EZH2 in Patients with Mantle Cell Lymphoma and Its Clinical Significance].

OBJECTIVE: To investigate the expression of miR-101 and EZH2 in patients with mantle cell lymphoma(MCL) and to analyze its correlation with clinical prognosis of MCL patients. METHODS: RQ-PCR and S-P immunohistochemistry were used to detect the expressions of miR-101 and EZH2 in tissue of MCL patients. CCK-8 was used to assay the effect of miR-100 minics on the proliferation of Jeko-1 and Mino cells; the flow cytometry with Annexin V/PI double staining was used to assay the apoptosis; Western blot was used to assay the effect of miR-101 minics on the expression of EZH2 protein in Jeko-1 and Mino cells. RESULTS: Compared with control group, miR-101 lowly expressed, and EZH2 protein highly expressed in MCL group, with very statistically significant difference(P<0.01).There was negative correlation between miR-101 and EZH2 expression(r=-0.638，P<0.05). The expression of miR-101 and EZH2 significantly correlated with B symptoms, International Prognostic Index(IPI) and Ann Arbor stage, respectively. Survival analysis showed that the overall survival(OS) rate of patients with low expression of miR-101 were significantly lower than that of patients with high miR-101 expression (P=0.0014), the OS rate of patients with EZH2 high expression were significantly lower than that of patients with EZH2 low expression (P=0.0093). The miR-100 minics could inhibit the proliferation of Jeko-1 and Mino cells, and increase the apoptotic rate. The expression of EZH2 protein was markedly suppressed by the miR-100 minics. CONCLUSION: The expression of miR-101 and EZH2 is different in MCL patients with different clinical stage and prognosis. The miR-101 can inhibit the cell proliferation and induce cell apoptosis of mantle cell lymphoma by targeting EZH2.

Ramipril and resveratrol co-treatment attenuates RhoA/ROCK pathway-regulated early-stage diabetic nephropathy-associated glomerulosclerosis in streptozotocin-induced diabetic rats.

Clinical studies have shown that hyperglycemia can induce early-stage diabetic nephropathy (DN). Furthermore, oxidative stress, tubular epithelial-mesenchymal transition and extracellular matrix accumulation promote the progression of DN to chronic kidney disease and tubulointerstitial fibrosis. It is necessary to initiate treatment at the early stages of DN or even during the early stages of diabetes. In this work, rats with streptozotocin (STZ)-induced diabetes mellitus (DM) presented early DN symptoms within 45 days, and collagen accumulation in the glomerulus of the rats was primarily mediated through the RhoA/ROCK pathway instead of the TGF-ß signaling pathway. Resveratrol (15 mg/kg/day) and ramipril (10 mg/kg/day) co-treatment of STZ-induced DN rats showed that glomerulosclerosis in early-stage DN was reversible (P < .05 compared with that in STZ-induced DM rats). The results of this study support early intervention in diabetes or DN as a more efficient therapeutic strategy.

Room-temperature electrochemical water-gas shift reaction for high purity hydrogen production.

Traditional water-gas shift reaction provides one primary route for industrial production of clean-energy hydrogen. However, this process operates at high temperatures and pressures, and requires additional separation of H2 from products containing CO2, CH4 and residual CO. Herein, we report a room-temperature electrochemical water-gas shift process for direct production of high purity hydrogen (over 99.99%) with a faradaic efficiency of approximately 100%. Through rational design of anode structure to facilitate CO diffusion and PtCu catalyst to optimize CO adsorption, the anodic onset potential is lowered to almost 0 volts versus the reversible hydrogen electrode at room temperature and atmospheric pressure. The optimized PtCu catalyst achieves a current density of 70.0 mA cm-2 at 0.6 volts which is over 12 times that of commercial Pt/C (40 wt.%) catalyst, and remains stable for even more than 475 h. This study opens a new and promising route of producing high purity hydrogen.

Relationship between high-sensitivity C-reactive protein and subclinical carotid atherosclerosis stratified by glucose metabolic status in Chinese adults.

BACKGROUND: Atherosclerosis is an inflammatory disease. Many studies demonstrated that hyperglycemia is not only increased inflammatory response, but also is a cause of atherosclerosis, implying that glucose metabolic status may be an important stratification factor when analyzing the relationship between inflammatory levels and subclinical carotid atherosclerosis. The aim of the present study is to assess the relationship between inflammatory levels and subclinical carotid atherosclerosis, stratified by different glucose metabolic status in a general population. METHODS: An assessment was performed in 7975 participants living in Tianjin, China. In the present study, we examined subclinical carotid atherosclerosis, as defined by increased carotid intima-media thickness [IMT] and plaques. Measurements were performed using a carotid artery B-mode ultrasound system. The glucose metabolic status was defined by the criteria of the American Diabetes Association, and high-sensitivity C-reactive protein (hs-CRP) as an inflammatory indicator, was measured by immunoturbidimetric assay. Multiple logistic models were used to assess a stratified relationship between hs-CRP levels and subclinical carotid atherosclerosis. Strata were defined according to glucose metabolic status. RESULTS: The prevalence of increased IMT and plaques were 27.3% and 21.3%, respectively. The adjusted odds ratios (95% confidence interval) for IMT across hs-CRP quartiles were as follows: 1.00 (reference), 1.10(0.88-1.38), 1.08(0.86-1.35) and 1.32(1.06-1.66) in blood glucose-normal subjects; 1.00 (reference), 1.33(0.92-1.91), 1.33(0.93-1.91), and 1.59(1.10-2.30) in prediabetic subjects; 1.00 (reference), 0.94(0.54-1.62), 1.17(0.65-2.12) and 0.98(0.55-1.76) in diabetic subjects, respectively. Similar results were observed for plaques. CONCLUSIONS: Our results suggest that inflammatory levels are differently related to subclinical carotid atherosclerosis by the different glucose metabolic status.