Geometric and Electronic Structure Modulation to Optimize the Charge Transfer of TiO2 for Ultrasensitive and Stable SERS Sensing.

Exploring the relationship between semiconductor structure and surface-enhanced Raman scattering (SERS) activity was essential for the development of ultrasensitive SERS substrates. Herein, we report an ytterbium atomic doping strategy to render TiO2 (Yb-TiO2) highly SERS sensitive superior to pure TiO2, with a detection limit as low as 1 × 10-9 M for 4-mercaptobenzoic acid. First-principles density functional theory calculations reveal that ytterbium doping leads to high electrostatic properties, allowing for significant charge transfer from molecules to semiconductors. Theoretical and experimental results indicate that Yb-TiO2 has a smaller band gap and higher density of states, which effectively enhance charge transfer between molecules and substrates, resulting in significant SERS activity. More importantly, Yb-TiO2 was particularly stable in air and acid solution and can be used for trace molecule detection in extreme environments. We demonstrate a promising approach to construct ultrasensitive SERS by optimizing the electronic structure induced by geometric structures.

Elucidating the association of obstructive sleep apnea with brain structure and cognitive performance.

BACKGROUND: Obstructive sleep apnea (OSA) is a pervasive, chronic sleep-related respiratory condition that causes brain structural alterations and cognitive impairments. However, the causal association of OSA with brain morphology and cognitive performance has not been determined. METHODS: We conducted a two-sample bidirectional Mendelian randomization (MR) analysis to investigate the causal relationship between OSA and a range of neurocognitive characteristics, including brain cortical structure, brain subcortical structure, brain structural change across the lifespan, and cognitive performance. Summary-level GWAS data for OSA from the FinnGen consortium was used to identify genetically predicted OSA. Data regarding neurocognitive characteristics were obtained from published meta-analysis studies. Linkage disequilibrium score regression analysis was employed to reveal genetic correlations between OSA and related traits. RESULTS: Our MR study provided evidence that OSA was found to significantly increase the volume of the hippocampus (IVW ß (95% CI) = 158.997 (76.768 to 241.227), P = 1.51e-04), with no heterogeneity and pleiotropy detected. Nominally causal effects of OSA on brain structures, such as the thickness of the temporal pole with or without global weighted, amygdala structure change, and cerebellum white matter change covering lifespan, were observed. Bidirectional causal links were also detected between brain cortical structure, brain subcortical, cognitive performance, and OSA risk. LDSC regression analysis showed no significant correlation between OSA and hippocampus volume. CONCLUSIONS: Overall, we observed a positive association between genetically predicted OSA and hippocampus volume. These findings may provide new insights into the bidirectional links between OSA and neurocognitive features, including brain morphology and cognitive performance.

A hybrid model for tuberculosis forecasting based on empirical mode decomposition in China.

BACKGROUND: Pulmonary Tuberculosis is a major public health problem endangering people's health, a scientifically accurate predictive model is of great practical significance for the prevention and treatment of pulmonary tuberculosis. METHODS: The reported incidence data of pulmonary tuberculosis were from the National Public Health Science Data Center ( https://www.phsciencedata.cn/ ). The ARIMA, LSTM, EMD-SARIMA, EMD-LSTM, EMD-ARMA-LSTM models were established using the reported monthly incidence of tuberculosis reported in China from January 2008 to December 2018. The MSE, MAE, RMSE and MAPE were used to evaluate the performance of the models to determine the best model. RESULTS: Comparing decomposition-based single model with undecomposed single model, it was found that: when predicting the incidence trend in the next year, compared with SARIMA model, the MSE, MAE, RMSE and MAPE of EMD-SARIMA decreased by 39.3%, 19.0%, 22.1% and 19.8%, respectively. The MSE, MAE, RMSE and MAPE of EMD-LSTM were reduced by 40.5%, 12.8%, 22.9% and 12.7%, respectively, compared with the LSTM model; Comparing the decomposition-based hybrid model with the decomposition-based single model, it was found that: when predicting the incidence trend in the next year, compared with EMD-SARIMA model, the MSE, MAE, RMSE and MAPE of EMD-ARMA-LSTM model decreased by 21.7%, 10.6%, 11.5% and 11.2%, respectively. The MSE, MAE, RMSE and MAPE of EMD-ARMA-LSTM were reduced by 16.7%, 9.6%, 8.7% and 12.3%, respectively, compared with EMD-LSTM model. Furthermore, the performance of the model were consistent when predicting the incidence trend in the next 3 months, 6 months and 9 months. CONCLUSION: The prediction performance of the decomposition-based single model is better than that of the undecomposed single model, and the prediction performance of the combined model using the advantages of different models is better than that of the decomposition-based single model, so the EMD-ARMA-LSTM combination model can improve the prediction accuracy better than other models, which can provide a theoretical basis for predicting the epidemic trend of pulmonary tuberculosis and formulating prevention and control policies.

Study on the prediction effect of a combined model of SARIMA and LSTM based on SSA for influenza in Shanxi Province, China.

BACKGROUND: Influenza is an acute respiratory infectious disease that is highly infectious and seriously damages human health. Reasonable prediction is of great significance to control the epidemic of influenza. METHODS: Our Influenza data were extracted from Shanxi Provincial Center for Disease Control and Prevention. Seasonal-trend decomposition using Loess (STL) was adopted to analyze the season characteristics of the influenza in Shanxi Province, China, from the 1st week in 2010 to the 52nd week in 2019. To handle the insufficient prediction performance of the seasonal autoregressive integrated moving average (SARIMA) model in predicting the nonlinear parts and the poor accuracy of directly predicting the original sequence, this study established the SARIMA model, the combination model of SARIMA and Long-Short Term Memory neural network (SARIMA-LSTM) and the combination model of SARIMA-LSTM based on Singular spectrum analysis (SSA-SARIMA-LSTM) to make predictions and identify the best model. Additionally, the Mean Squared Error (MSE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) were used to evaluate the performance of the models. RESULTS: The influenza time series in Shanxi Province from the 1st week in 2010 to the 52nd week in 2019 showed a year-by-year decrease with obvious seasonal characteristics. The peak period of the disease mainly concentrated from the end of the year to the beginning of the next year. The best fitting and prediction performance was the SSA-SARIMA-LSTM model. Compared with the SARIMA model, the MSE, MAE and RMSE of the SSA-SARIMA-LSTM model decreased by 38.12, 17.39 and 21.34%, respectively, in fitting performance; the MSE, MAE and RMSE decreased by 42.41, 18.69 and 24.11%, respectively, in prediction performances. Furthermore, compared with the SARIMA-LSTM model, the MSE, MAE and RMSE of the SSA-SARIMA-LSTM model decreased by 28.26, 14.61 and 15.30%, respectively, in fitting performance; the MSE, MAE and RMSE decreased by 36.99, 7.22 and 20.62%, respectively, in prediction performances. CONCLUSIONS: The fitting and prediction performances of the SSA-SARIMA-LSTM model were better than those of the SARIMA and the SARIMA-LSTM models. Generally speaking, we can apply the SSA-SARIMA-LSTM model to the prediction of influenza, and offer a leg-up for public policy.

An explainable artificial intelligence framework for risk prediction of COPD in smokers.

BACKGROUND: Since the inconspicuous nature of early signs associated with Chronic Obstructive Pulmonary Disease (COPD), individuals often remain unidentified, leading to suboptimal opportunities for timely prevention and treatment. The purpose of this study was to create an explainable artificial intelligence framework combining data preprocessing methods, machine learning methods, and model interpretability methods to identify people at high risk of COPD in the smoking population and to provide a reasonable interpretation of model predictions. METHODS: The data comprised questionnaire information, physical examination data and results of pulmonary function tests before and after bronchodilatation. First, the factorial analysis for mixed data (FAMD), Boruta and NRSBoundary-SMOTE resampling methods were used to solve the missing data, high dimensionality and category imbalance problems. Then, seven classification models (CatBoost, NGBoost, XGBoost, LightGBM, random forest, SVM and logistic regression) were applied to model the risk level, and the best machine learning (ML) model's decisions were explained using the Shapley additive explanations (SHAP) method and partial dependence plot (PDP). RESULTS: In the smoking population, age and 14 other variables were significant factors for predicting COPD. The CatBoost, random forest, and logistic regression models performed reasonably well in unbalanced datasets. CatBoost with NRSBoundary-SMOTE had the best classification performance in balanced datasets when composite indicators (the AUC, F1-score, and G-mean) were used as model comparison criteria. Age, COPD Assessment Test (CAT) score, gross annual income, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), anhelation, respiratory disease, central obesity, use of polluting fuel for household heating, region, use of polluting fuel for household cooking, and wheezing were important factors for predicting COPD in the smoking population. CONCLUSION: This study combined feature screening methods, unbalanced data processing methods, and advanced machine learning methods to enable early identification of COPD risk groups in the smoking population. COPD risk factors in the smoking population were identified using SHAP and PDP, with the goal of providing theoretical support for targeted screening strategies and smoking population self-management strategies.

Three-dimensional printed titanium mesh combined with iliac cancellous bone in the reconstruction of mandibular defects secondary to ameloblastoma resection.

BACKGROUND: The reconstruction of large mandibular defects is a challenge, and free vascularized bone flaps are most commonly used. However, the precision and symmetry of this repair are deficient, and patients have a risk of vascular embolism, flap necrosis, and donor site complications. Therefore, to explore an ideal alternative in mandibular reconstruction with high surgical accuracy and low complications is indispensable. METHODS: Seven patients with recurrent or large-scope ameloblastoma were enrolled in this study. All patients were provided with a fully digital treatment plan, including the design of osteotomy lines, surgical guides, and three-dimensional printed titanium mesh for implantation. With the assistance of surgical guide, ameloblastomas were resected, and custom 3D printed titanium mesh combined with posterior iliac bone harvest was used in mandibular reconstruction. A comparison was made between the discrepant surgical outcomes and the intended surgical plan, as well as the average three-dimensional deviation of the mandible before and after the surgery. At the same time, the resorption rate of the implanted bone was evaluated. RESULTS: All patients completed the fully digital treatment process successfully without severe complications. Image fusion showed that the postoperative contour of the mandible was basically consistent with surgical planning, except for a slight increase in the inferior border of the affected side. The mean three-dimensional deviation of the mandible between the preoperative and postoperative periods was 0.78 ± 0.41 mm. The mean error between the intraoperative bone volume and the digital planning bone volume was 2.44%±2.10%. Furthermore, the bone resorption rates of the harvested graft 6 months later were 32.15%±6.95%. CONCLUSIONS: The use of digital surgical planning and 3D-printed templates can assist surgeons in performing surgery precisely, and the 3D-printed titanium mesh implant can improve the patient's facial symmetry. 3D printed titanium mesh combined with posterior iliac cancellous bone graft can be regarded as an ideal alternative in extensive mandibular reconstruction.

The application of a fully digital approach in the treatment of skeletal class III malocclusion: a preliminary study.

BACKGROUND: Skeletal malocclusion patients have facial malformations and occlusal dysfunctions that require orthodontic-orthognathic joint treatment, while the combination treatment takes time and requires close communication between surgeons and orthodontists. Thus, improving the efficiency and effectiveness of the combination treatment is necessary, and it is still a challenge. Now, digital technology provides us with an excellent alternative. Despite the widespread use of digital technology in orthognathic surgery simulation and clear aligner orthodontic therapy, it has not been fully integrated into the combined orthognathic and orthodontic treatment process, and the components remain independent. METHODS: A fully digital approach to seamlessly integrating various parts of the combined treatment through digital technology was investigated in this study in order to achieve an efficient transition. Five patients with skeletal Class III malocclusion were enrolled, and all made fully digital treatment plans at the beginning of actual implementation, which included the design of pre-surgical orthodontic, orthognathic surgery, and post-surgical orthodontic. Then, every aspect of the clinical operation was carried out in accordance with the fully digital routine. After the entire treatment process was completed, the skeleton and dentition discrepancy between virtual planning and the actual result was evaluated. RESULTS: All participants completed the fully digital treatment process, and no complication was observed. The linear deviation of the skeletal anatomy was less than 1 mm, and the angular deviation was less than 1 degree. Except in one case in the lower dentition, the deviation of the virtual dental design from the real alignment was less than 2 mm. Furthermore, with one exception of maxillary anterior-posterior dimension, the linear deviations of the skeleton were not statistically significant. Therefore, the simulation accuracy of the fully digital approach was clinically acceptable. CONCLUSIONS: The digital treatment approach is clinically feasible and has achieved satisfactory results. The discrepancy between virtual design of the entire digital process and actual post-treatment situation was acceptable in clinic. A fully digital approach was proved effective in the treatment of skeletal Class III malocclusion, with which the efficient transition of treatment procedures was realized.

Metabolism of bioconjugate therapeutics: why, when, and how?

Bioconjugation of therapeutic agents has been used as a selective drug delivery platform for many therapeutic areas. Bioconjugates are prepared by the covalent linkage of active compounds (small or large molecule) to a carrier molecule (lipids, proteins, peptides, carbohydrates, and polymers) through a chemical linker. The linkage of the active component to a carrier molecule enhances the therapeutic window through a targeted delivery and by reducing toxicity. Bioconjugates also possess improved pharmacokinetic properties such as a long half-life, increased stability, and cleavage by intracellular enzymes/environment. However, premature cleavage of the bioconjugates and the resulting metabolites/catabolites may produce undesirable toxic effects and, hence, it is critical to understand cleavage mechanisms, metabolism of bioconjugates, and translatability to human in the discovery stages. This article provides a comprehensive overview of linker cleavage pathways and catabolism/metabolism of antibody-drug conjugates, glycoconjugates, polymer-drug conjugates, lipid-drug conjugates, folate-targeted small molecule-drug conjugates, and drug-drug conjugates.

Shape Memory of Microscale and Nanoscale Imprinted Patterns on a Supramolecular Polymer Compound.

Surface memory effects for micropattern and nanopattern are demonstrated for shape memory compounds composed of mixtures of the zinc salt of a sulfonated poly(ethylene-co-propylene-co-ethylidene norbornene) ionomer and three different low molar mass fatty acids (FAs): lauric acid (LA), stearic acid (SA), and zinc stearate (ZnSt). This work shows the ability to tune the surface pattern switching temperature (Tc ) by simply varying the FA melting point. The melting point of the FA in the ionomer compound is depressed from that of the pure FA due to strong dipolar interactions between the ionomer and the FAs. Surface pattern memory and recovery are shown for compounds with 20 wt% LA, SA, or ZnSt, where Tc = 50, 80, and 100 °C, respectively. Recovery efficiencies for micropatterns are better than 92% for all three compounds and 73% for a nanopattern for the ionomer/ZnSt compound.

Species difference in glucuronidation formation kinetics with a selective mTOR inhibitor.

The mammalian target of rapamycin (mTOR) is a protein kinase that shows key involvement in age-related disease and promises to be a target for treatment of cancer. In the present study, the elimination of potent ATP-competitive mTOR inhibitor 3-(6-amino-2-methylpyrimidin-4-yl)-N-(1H-pyrazol-3-yl)imidazo[1,2-b]pyridazin-2-amine (compound 1) is studied in bile duct-cannulated rats, and the metabolism of compound 1 in liver microsomes is compared across species. Compound 1 was shown to undergo extensive N-glucuronidation in bile duct-catheterized rats. N-glucuronides were detected on positions N1 (M2) and N2 (M1) of the pyrazole moiety as well as on the primary amine (M3). All three N-glucuronide metabolites were detected in liver microsomes of the rat, dog, and human, while primary amine glucuronidation was not detected in cynomolgus monkey. In addition, N1- and N2-glucuronidation showed strong species selectivity in vitro, with rat, dog, and human favoring N2-glucuronidation and monkey favoring N1-glucuronide formation. Formation of M1 in monkey liver microsomes also followed sigmoidal kinetics, singling out monkey as unique among the species with regard to compound 1 N-glucuronidation. In this respect, monkeys might not always be the best animal model for N-glucuronidation of uridine diphosphate glucuronosyltransferase (UGT) 1A9 or UGT1A1 substrates in humans. The impact of N-glucuronidation of compound 1 could be more pronounced in higher species such as monkey and human, leading to high clearance in these species. While compound 1 shows promise as a candidate for investigating the impact of pan-mTOR inhibition in vivo, opportunities may exist through medicinal chemistry efforts to reduce metabolic liability with the goal of improving systemic exposure.

Whole-body tissue distribution study of drugs in neonate mice using desorption electrospray ionization mass spectrometry imaging.

RATIONALE: Although Desorption Electrospray Ionization (DESI) Mass Spectrometry Imaging (MSI) is uniquely suited for whole-body (WB) tissue distribution study of drugs, success in this area has been difficult. Here, we present WB tissue distribution studies using DESI-MSI and a new histological tissue-friendly solvent system. METHODS: Neonate pups were dosed subcutaneously (SC) with clozapine, compound 1, compound 2, or compound 3. Following euthanization by hypothermia, neonates underwent a transcardiac perfusion (saline) to remove blood. After cryosectioning, DESI-MSI was conducted for the WB tissue slides, followed sequentially by histological staining. RESULTS: Whole-body tissue imaging showed that clozapine and its N-oxide metabolite were distributed in significant amounts in the brain, spinal cord, liver, heart (ventricle), and lungs. Compound 1 was distributed mainly in the liver and muscle, and its mono-oxygenated metabolite was detected by DESI-MSI exclusively in the liver. Compound 2 was distributed mainly in the muscle and fatty tissue. Compound 3 was distributed mainly in fatty tissue and its metabolites were also mainly detected in the same tissue. CONCLUSIONS: The results demonstrate the successful application of DESI-MSI in whole-body tissue distribution studies of drugs and metabolites in combination with sequential histology staining for anatomy. The results also identified lipophilicity as the driving force in the tissue distribution of the three Amgen compounds.

A novel IRF6 gene mutation impacting the regulation of TGFß2-AS1 in the TGFß pathway: A mechanism in the development of Van der Woude syndrome.

Several mutations in the IRF6 gene have been identified as a causative link to VWS. In this investigation, whole-exome sequencing (WES) and Sanger sequencing of a three-generation pedigree with an autosomal-dominant inheritance pattern affected by VWS identified a unique stop-gain mutation-c.748C>T:p.R250X-in the IRF6 gene that co-segregated exclusively with the disease phenotype. Immunofluorescence analysis revealed that the IRF6-p.R250X mutation predominantly shifted its localization from the nucleus to the cytoplasm. WES and protein interaction analyses were conducted to understand this mutation's role in the pathogenesis of VWS. Using LC-MS/MS, we found that this mutation led to a reduction in the binding of IRF6 to histone modification-associated proteins (NAA10, SNRPN, NAP1L1). Furthermore, RNA-seq results show that the mutation resulted in a downregulation of TGFß2-AS1 expression. The findings highlight the mutation's influence on TGFß2-AS1 and its subsequent effects on the phosphorylation of SMAD2/3, which are critical in maxillofacial development, particularly the palate. These insights contribute to a deeper understanding of VWS's molecular underpinnings and might inform future therapeutic strategies.

Application of improved harmonic Poisson segmented regression model in evaluating the effectiveness of Kala-Azar intervention in Yangquan City, China.

Background: The Centre for Disease Control and Prevention in Yangquan, China, has taken a series of preventive and control measures in response to the increasing trend of Kala-Azar. In response, we propose a new model to more scientifically evaluate the effectiveness of these interventions. Methods: We obtained the incidence data of Kala-Azar from 2017 to 2021 from the Centre for Disease Control and Prevention (CDC) in Yangquan. We constructed Poisson segmented regression model, harmonic Poisson segmental regression model, and improved harmonic Poisson segmented regression model, and used the three models to explain the intervention effect, respectively. Finally, we selected the optimal model by comparing the fitting effects of the three models. Results: The primary analysis showed an underlying upward trend of Kala-Azar before intervention [incidence rate ratio (IRR): 1.045, 95% confidence interval (CI): 1.027-1.063, p < 0.001]. In terms of long-term effects, the rise of Kala-Azar slowed down significantly after the intervention (IRR:0.960, 95%CI:0.927-0.995, p = 0.026), and the risk of Kala-Azar increased by 0.3% for each additional month after intervention (ß1 + ß3 = 0.003, IRR = 1.003). The results of the model fitting effect showed that the improved harmonic Poisson segmental regression model had the best fitting effect, and the values of MSE, MAE, and RMSE were the lowest, which were 0.017, 0.101, and 0.130, respectively. Conclusion: In the long term, the intervention measures taken by the Yangquan CDC can well curb the upward trend of Kala-Azar. The improved harmonic Poisson segmented regression model has higher fitting performance, which can provide a certain scientific reference for the evaluation of the intervention effect of seasonal infectious diseases.

Ultralight M5 aerogels with superior thermal stability and inherent flame retardancy.

Ultra-lightweight materials often face the formidable challenge of balancing their low density, high porosity, high mechanical stiffness, high thermal and environmental stability, and low thermal conductivity. This study introduces an innovative method for synthesizing high-performance polymer aerogels to address the challenge. Specifically, we detail the production of poly (2,5-dihydroxy-1,4-phenylene pyridine diimidazole) (PIPD or M5) aerogels. This process involves chemically stripping M5 "super" fibers into nanofibers, undergoing a Sol-Gel transition, followed by freeze-drying and subsequent thermal annealing. The M5 aerogels excel beyond existing polymer aerogels, boasting an ultralight density of 6.03 mg cm-3, superior thermal insulation with thermal conductivity at 32 mW m-1 K-1, inherent flame retardancy (LOI = 50.3%), 80% compression resilience, a high specific surface area of 462.1 m2 g-1, and outstanding thermal stability up to 463 °C. These multi-faceted properties position the M5 aerogel as a front-runner in lightweight insulation materials, demonstrating the strategic use of high-performance polymer assembly units in aerogel design.

Dynamic modeling of cytochrome P450 inhibition in vitro: impact of inhibitor depletion on IC50 shift.

The impact of inhibitor depletion on the determination of shifted IC50 (IC50 determined after 30 minutes of preincubation with inhibitor) is examined. In addition, IC50-shift data are analyzed using a mechanistic model that incorporates the processes of inhibitor depletion, as well as reversible and time-dependent inhibition. Anomalies such as a smaller-than-expected shift in IC50 and even increases in IC50 with preincubation were explained by the depletion of inhibitor during the preincubation. The IC50-shift assay remains a viable approach to characterizing a wide range of reversible and time-dependent inhibitors. However, as with more traditional time-dependent inactivation methods, it is recommended that IC50-shift experimental data be interpreted with some knowledge of the magnitude of inhibitor depletion. For the most realistic classification of time-dependent inhibitors using IC50-shift methods, shifted IC50 should be calculated using observed inhibitor concentrations at the end of the incubation rather than nominal inhibitor concentrations. Finally, a mechanistic model that includes key processes, such as competitive inhibition, enzyme inactivation, and inhibitor depletion, can be used to describe accurately the observed IC50 and shifted IC50 curves. For compounds showing an IC50 fold shift >1.5 based on the observed inhibitor concentrations, reanalyzing the IC50-shift data using the mechanistic model appeared to allow for reasonable estimation of Ki, KI, and kinact directly from the IC50 shift experiments.

Impact of hydrolysis-mediated clearance on the pharmacokinetics of novel anaplastic lymphoma kinase inhibitors.

Compound 1 [(E)-4-fluoro-N-(6-((4-(2-hydroxypropan-2-yl)piperidin-1-yl)methyl)-1-((1S,4S)-4-(isopropylcarbamoyl)cyclohexyl)-1H-benzo[d]imidazol-2(3H)-ylidene)benzamide], a new, potent, selective anaplastic lymphoma kinase (ALK) inhibitor with potential application for the treatment of cancer, was selected as candidate to advance into efficacy studies in mice. However, the compound underwent mouse-specific enzymatic hydrolysis in plasma to a primary amine product (M1). Subsequent i.v. pharmacokinetics studies in mice showed that compound 1 had high clearance (CL) and a short half-life. Oral dose escalation studies in mice indicated that elimination of compound 1 was saturable, with higher doses achieving sufficient exposures above in vitro IC(50). Chemistry efforts to minimize hydrolysis resulted in the discovery of several analogs that were stable in mouse plasma. Three were taken in vivo into mice and showed decreased CL corresponding to increased in vitro stability in plasma. However, the more stable compounds also showed reduced potency against ALK. Kinetic studies in NADPH-fortified and unfortified microsomes and plasma produced submicromolar K(m) values and could help explain the saturation of elimination observed in vivo. Predictions of CL based on kinetics from hydrolysis and NADPH-dependent pathways produced predicted hepatic CL values of 3.8, 3.0, 1.6, and 1.2 l/h⋅kg for compound 1, compound 2 [(E)-3,5-difluoro-N-(6-((4-(2-hydroxypropan-2-yl)piperidin-1-yl)methyl)-1-((1s,4s)-4-(isopropylcarbamoyl)cyclohexyl)-1H-benzo[d]imidazol-2(3H)-ylidene)benzamide], compound 3 [(E)-3-chloro-5-fluoro-N-(6-((4-(2-hydroxypropan-2-yl)piperidin-1-yl)methyl)-1-((1s,4s)-4-(isopropylcarbamoyl)cyclohexyl)-1H-benzo[d]imidazol-2(3H)-ylidene)benzamide], and compound 4 [(E)-N-(6-((4-(2-hydroxypropan-2-yl)piperidin-1-yl)methyl)-1-((1s,4s)-4-(isopropylcarbamoyl)cyclohexyl)-1H-benzo[d]imidazol-2(3H)-ylidene)-3-(trifluoromethyl)benzamide], respectively. The in vivo observed CLs for compounds 1, 2, 3, and 4 were 5.52, 3.51, 2.14, and 2.66 l/h⋅kg, respectively. These results indicate that in vitro metabolism kinetic data, incorporating contributions from both hydrolysis and NADPH-dependent metabolism, could be used to predict the systemic CL of compounds cleared via hydrolytic pathways provided that the in vitro assays thoroughly investigate the processes, including the contribution of other metabolic pathways and the possibility of saturation kinetics.

Ratios of biliary glutathione disulfide (GSSG) to glutathione (GSH): a potential index to screen drug-induced hepatic oxidative stress in rats and mice.

Hepatotoxicity of drug candidates is one of the major concerns in drug screening in early drug discovery. Detection of hepatic oxidative stress can be an early indicator of hepatotoxicity and benefits drug selection. The glutathione (GSH) and glutathione disulfide (GSSG) pair, as one of the major intracellular redox regulating couples, plays an important role in protecting cells from oxidative stress that is caused by imbalance between prooxidants and antioxidants. The quantitative determination of the GSSG/GSH ratios and the concentrations of GSH and GSSG have been used to indicate oxidative stress in cells and tissues. In this study, we tested the possibility of using the biliary GSSG/GSH ratios as a biomarker to reflect hepatic oxidative stress and drug toxicity. Four compounds that are known to alter GSH and GSSG levels were tested in this study. Diquat (diquat dibromide monohydrate) and acetaminophen were administered to rats. Paraquat and tert-butyl hydroperoxide were administered to mice to induce changes of biliary GSH and GSSG. The biliary GSH and GSSG were quantified using calibration curves prepared with artificial bile to account for any bile matrix effect in the LC-MS analysis and to avoid the interference of endogenous GSH and GSSG. With four examples (in rats and mice) of drug-induced changes in the kinetics of the biliary GSSG/GSH ratios, this study showed the potential for developing an exposure response index based on biliary GSSG/GSH ratios for predicting hepatic oxidative stress.

Integrating Virtual Surgical Planning and 3D-Printed Tools with Iliac Bone Grafts for Orbital and Zygomatic Reconstruction in Hemifacial Microsomia Patients.

Hemifacial Microsomia (HFM) is the second most common congenital craniofacial malformation syndrome, and the complexity of HFM makes its treatment challenging. The present study aimed to introduce a new approach of utilization of virtual surgical planning (VSP) and 3D-printed surgical adjuncts for maxillofacial reconstruction. Five HFM patients were included in this study. All participants were provided with a full VSP, including the design of osteotomy lines, the design and fabrication of 3D-printed cutting guides, fixation plates, and titanium mesh for implantation. With the assistance of 3D-printed cutting guides and fixation plates, the orbital deformities were corrected, and a 3D-printed titanium mesh combined with iliac cancellous bone graft was applied to reconstruct the zygomatic arch. The surgical accuracy, effectiveness, and bone absorption rate were evaluated. All patients completed the entirely digital treatment process without experiencing severe complications. The surgical adjuncts were effective in aligning the movement of the bone segments with the surgical plan, resulting in mean 3D deviations (1.0681 ± 0.15 mm) and maximum 3D deviations (3.1127 ± 0.44 mm). The image fusion results showed that the patients' postoperative position of the maxilla, zygoma, and orbital rim was consistent with the virtual surgical plan, with only a slight increase in the area of bone grafting. The postoperative measurements showed significant improvement in the asymmetry indices of Er (AI of Er: from 17.91 ± 3.732 to 5.427 ± 1.389 mm, p = 0.0001) and FZ (AI of FZ: from 7.581 ± 1.435 to 4.070 ± 1.028 mm, p = 0.0009) points. In addition, the observed bone resorption rate at the 6-month follow-up across the five patients was 45.24% ± 3.13%. In conclusion, the application of VSP and 3D-printed surgical adjuncts demonstrates significant value in enhancing the precision and effectiveness of surgical treatments for HFM. A 3D-printed titanium mesh combined with iliac cancellous bone graft can be considered an ideal alternative for the reconstruction of the zygomatic arch.

Magnetic Domains and Their Power Spectral Densities in Non-Oriented Electrical Steel after Thermal Compression at Different Rates.

The magnetic domains of non-oriented electrical steel bearing cumulative thermal compressions made by a Gleeble 3500 Thermal System were observed using an atomic force microscope (AFM). The component forces, comprising the magnetic forces between the AFM probe and magnetic domains of the samples, along the freedom direction of the probe, were measured, and they formed the value fluctuation of the magnetic domains. The fluctuations of the magnetic domains were analyzed by examining the power spectral density (PSD) curves. The hysteresis curves of the samples were measured using a highly sensitive magnetic measurement system. An analysis of the magnetic force microscope (MFM) maps suggested that some magnetic domains were compressed into crushed and fragmented shapes, similar to the microstructure of deformed grains. Meanwhile, some were reconstructed within the thermal compressions, like dynamic recrystallization microstructures. Meaningfully, the MFM probe moved and deformed the proximal magnetic domains of tested samples within the region of its weak magnetic field. The peak positions of the magnetic domains with a high deformation rate were shifted and moved during the measuring processes by the weakly polarized probe. Both windward and leeward sides simultaneously expressed a slope towards each co-adjacent valley in the MFM maps and induced a statistical throbbing within a narrow band in the PSD curves. Thus, the MFM scanning mode was also analyzed and improved to obtain accurate MFM maps with low disturbances from the weak magnetic field of the probe. Swapping the order positions of the middle processes in the MFM scanning and adding a gliding step between them could offset the peak skewing of magnetic domains caused by the weakly polarized probe during MFM measurement process without incurring excessive replacement costs. Accumulative compression at a high rate (10 s-1) would crush magnetic domains into irregularly decreasing sizes with messy boundaries. This investigation provides an example of the complete relationships among deformations, magnetic domains, and magnetic properties.

Facile Synthesis of Polymer-Reinforced Silica Aerogel Microspheres as Robust, Hydrophobic and Recyclable Sorbents for Oil Removal from Water.

With the rapid development of industry and the acceleration of urbanization, oil pollution has caused serious damage to water, and its treatment has always been a research hotspot. Compared with traditional adsorption materials, aerogel has the advantages of light weight, large adsorption capacity and high selective adsorption, features that render it ideal as a high-performance sorbent for water treatment. The objective of this research was to develop novel hydrophobic polymer-reinforced silica aerogel microspheres (RSAMs) with water glass as the precursor, aminopropyltriethoxysilane as the modifier, and styrene as the crosslinker for oil removal from water. The effects of drying method and polymerization time on the structure and oil adsorption capacity were investigated. The drying method influenced the microstructure and pore structure in a noteworthy manner, and it also significantly depended on the polymerization time. More crosslinking time led to more volume shrinkage, thus resulting in a larger apparent density, lower pore volume, narrower pore size distribution and more compact network. Notably, the hydrophobicity increased with the increase in crosslinking time. After polymerization for 24 h, the RSAMs possessed the highest water contact angle of 126°. Owing to their excellent hydrophobicity, the RSAMs via supercritical CO2 drying exhibited significant oil and organic liquid adsorption capabilities ranging from 6.3 to 18.6 g/g, higher than their state-of-the-art counterparts. Moreover, their robust mechanical properties ensured excellent reusability and recyclability, allowing for multiple adsorption-desorption cycles without significant degradation in performance. The novel sorbent preparation method is facile and inspiring, and the resulting RSAMs are exceptional in capacity, efficiency, stability and regenerability.