Artificial Surface Electron Network Prompted Energy Band Structure Tuning: Boosting Solar-to-Hydrogen Evolution Performance.

The energy gap and conduction band position of catalysts play crucial roles in solar-to-hydrogen (STH) transformation technology. Unfortunately, although an increase in the conduction band position can effectively promote the photoreduction capacity of the photocatalyst, it will inevitably widen the band gap, thus reducing the light-absorption scale. It seems that there is a contradiction between the reduction of band gap and the improvement of conduction band position, which is that "You can't have your cake and eat it too." Herein, an ultrasimple molecular adsorption strategy was engineered by adsorbing hydrazine hydrate on the surface of TiO2. The theoretical and experimental results indicated that the strong electron-donating effect of amino groups in hydrazine hydrate can promote the redistribution of photogenerated electrons and form surface electron networks on the surface of TiO2 photocatalysts, which can bend the conduction band upward and significantly improve its photoreduction ability. Besides, the adsorption of -NH2 can narrow the band gap width of TiO2 and promote the separation efficiency of photogenerated carriers. More interestingly, it can also effectively enhance the adsorption of H2O and H+, thus greatly elevating the STH efficiency. The STH rate of the as-prepared T-N-3 can be increased by ≈530%. This work sheds light on a new approach for resolving the contradiction between photoreduction and light absorption capabilities to effectively enhance photocatalytic performance.

Machine Learning Supported the Modified Gustafson's Criteria for Dental Age Estimation in Southwest China.

Adult age estimation is one of the most challenging problems in forensic science and physical anthropology. In this study, we aimed to develop and evaluate machine learning (ML) methods based on the modified Gustafson's criteria for dental age estimation. In this retrospective study, a total of 851 orthopantomograms were collected from patients aged 15 to 40 years old. The secondary dentin formation (SE), periodontal recession (PE), and attrition (AT) of four mandibular premolars were analyzed according to the modified Gustafson's criteria. Ten ML models were generated and compared for age estimation. The partial least squares regressor outperformed other models in males with a mean absolute error (MAE) of 4.151 years. The support vector regressor (MAE = 3.806 years) showed good performance in females. The accuracy of ML models is better than the single-tooth model provided in the previous studies (MAE = 4.747 years in males and MAE = 4.957 years in females). The Shapley additive explanations method was used to reveal the importance of the 12 features in ML models and found that AT and PE are the most influential in age estimation. The findings suggest that the modified Gustafson method can be effectively employed for adult age estimation in the southwest Chinese population. Furthermore, this study highlights the potential of machine learning models to assist experts in achieving accurate and interpretable age estimation.

Machine learning and deep learning enabled age estimation on medial clavicle CT images.

The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the performance on normal and variant clavicles. This study retrospectively collected 1049 patients (mean± SD: 22.50±4.34 years) and split them into normal training and test sets, and variant training and test sets. An additional 53 variant clavicles were incorporated into the variant test set. The development stages of normal MCE were used to build a linear model and support vector machine (SVM) for BAE. The CT slices of MCE were automatically segmented and used to train DL models for automated BAE. Comparisons were performed by linear versus ML versus DL, and normal versus variant clavicles. Mean absolute error (MAE) and classification accuracy was the primary parameter of comparison. For BAE, the SVM had the best MAE of 1.73 years, followed by the commonly-used CNNs (1.77-1.93 years), the linear model (1.94 years), and the hybrid neural network CoAt Net (2.01 years). In DL models, SE Net 18 was the best-performing DL model with similar results to SVM in the normal test set and achieved an MAE of 2.08 years in the external variant test. For age classification, all the models exhibit superior performance in the classification of 18-, 20-, 21-, and 22-year thresholds with limited value in the 16-year threshold. Both ML and DL models produce desirable performance in BAE based on medial clavicle CT.

Forensic age estimation in adults by pubic bone mineral density using multidetector computed tomography.

Radiology plays a crucial role in forensic anthropology for age estimation. However, most studies rely on morphological methods. This study aims to investigate the feasibility of using pubic bone mineral density (BMD) as a new age estimation method in the Chinese population. 468 pubic bone CT scans from living individuals in a Chinese hospital aged 18 to 87 years old were used to measure pubic BMD. The BMD of the bilateral pubic bone was measured using the Mimics software on cross-sectional CT images and the mean BMD of the bilateral pubic bone was also calculated. Regression analysis was performed to assess the correlation between pubic BMD and chronological age and to develop mathematical models for age estimation. We evaluated the accuracy of the best regression model using an independent validation sample by calculating the mean absolute error (MAE). Among all established models, the cubic regression model had the highest R2 value in both genders, with R2 = 0.550 for males and R2 = 0.634 for females. The results of the best model test showed that the MAE for predicting age using pubic BMD was 8.66 years in males and 7.69 years in females. This study highlights the potential of pubic BMD as a useful objective indicator for adult age estimation and could be used as an alternative in forensic practice when other better indicators are lacking.

Hybrid nanoarchitectonics of coal-derived carbon with oxidation-induced morphology-selectivity for high-performance supercapacitor.

Coal-derived porous carbon with a large specific surface area is a common electrode material for supercapacitors. Its deep and branched micropores, dense bulk morphology and amorphous structure have greatly limited its practical applications. Herein, hybrid carbon materials were obtained from coal through oxidation followed by activation. The method allows tuning the morphology, porosity, structure, and the degree of graphitization. The pre-oxidation with KMnO4 can break raw coal into small hydrocarbon fragments, which deposit and grow on the surface of generated MnO during pyrolysis leading to hybrid carbon with mesoporous and graphitic nanostructures. Meanwhile, homogeneous etching of the carbon skeleton by the reaction intermediate of K2CO3 led to the formation of abundant active sites. Hence, the optimized sample exhibited a high capacitance of 333 F g-1 at 1 A g-1, an excellent rate capability with 58% capacitance retention at 100 A g-1 and superior cycle durability in a three-electrode system. Besides, an assembled symmetric two-electrode device displayed a high energy density of 8.9 Wh·kg-1 at 250 W·kg-1. This work proposed a facile and rational synthesis strategy by balancing the tradeoff between active sites and intrinsic conductivity and thus provided a new avenue for the value-added utilization of coal.

Protective effect of omega-3 polyunsaturated fatty acids on sepsis via the AMPK/mTOR pathway.

CONTEXT: Sepsis is a systemic inflammatory response caused by infection, with high morbidity and mortality. Omega-3 polyunsaturated fatty acids (ω-3 PUFAs) have reported biological activities. OBJECTIVE: This study explored the signaling pathways through which ω-3 PUFAs protect against sepsis-induced multiorgan failure. MATERIALS AND METHODS: Septic Sprague-Dawley (SD) rat model was established by the cecum ligation perforation (CLP) method. Rats were divided into control, sham, model, parenteral ω-3 PUFAs (0.5 g/kg) treatment, ω-3 PUFAs (0.5 g/kg) + AMPK inhibitor Compound C (30 mg/kg) treatment, and ω-3 PUFAs (0.5 g/kg) + mTOR activator MHY1485 (10 mg/kg) treatment groups. The serum inflammatory cytokines were measured using ELISA. Organ damage-related markers cTnI, CK, CK-MB, Cr, BUN, ALT, and AST were measured using an automated chemical analyzer. The AMPK/mTOR pathway in liver, kidney, and myocardial tissues was detected using western blot and qRT-PCR methods. RESULTS: CLP treatment enhanced the secretion of pro-inflammatory cytokines and multi-organ related markers, along with increased p-AMPK/AMPK ratio (from 0.47 to 0.87) and decreased p-mTOR/mTOR ratio (from 0.33 to 0.12) in rats. The inflammation response and multi-organ injury induced by CLP treatment could be partially counteracted by 0.5 g/kg parenteral ω-3 PUFA treatment. The activated AMPK/mTOR pathway in CLP-induced rats was further promoted. Finally, Compound C and MHY1485 could reverse the effects of parenteral ω-3 PUFA treatment on sepsis rats. DISCUSSION AND CONCLUSION: ω-3 PUFAs ameliorated sepsis development by activating the AMPK/mTOR pathway, serving as a potent therapeutic agent for sepsis. Further in vivo studies may validate potential clinical use.

Interfacial modification and band modulation for dramatically boosted photocatalytic hydrogen evolution.

Interfacial modification and band modulation to narrow the band gap and improve light-harvesting ability of TiO2 are promising strategies to dramatically promote photocatalytic activity. Herein, efficient Co(OH)2-TiO2 nanocomposites were reasonably designed and constructed by a facile room temperature solid-state synthetic strategy for interfacial modification and matched band gap to achieve the conversion of solar energy to hydrogen. Modifying transition metal hydroxide Co(OH)2 on commercial TiO2 can effectively narrow the band gap and accelerate the separation and migration of photo-induced carriers, which will extend light absorption range and facilitate more electrons transferring to the surface of photocatalyst, therefore the reducibility of photocatalysts is enhanced. The modified photocatalyst exhibits high photocatalytic hydrogen evolution activity and stability. Specifically, the obtained TCO-0.6 shows excellent photocatalytic hydrogen evolution rate of 21343.01 µmol g-1 and is 23 times superior to commercial TiO2. This work not only emphasizes a facile strategy for interfacial modification and band modulation under mild condition, but also provides a novel avenue for improving the performance of photocatalytic hydrogen evolution.

Graphene Quantum Dot Reinforced Electrospun Carbon Nanofiber Fabrics with High Surface Area for Ultrahigh Rate Supercapacitors.

High surface area, good conductivity, and high mechanical strength are important for carbon nanofiber fabrics (CNFs) as high-performance supercapacitor electrodes. However, it remains a big challenge because of the trade-off between the strong and continuous conductive network and a well-developed porous structure. Herein, we report a simple strategy to integrate these properties into the electrospun CNFs by adding graphene quantum dots (GQDs). The uniformly embedded GQDs play a crucial bifunctional role in constructing an entire reinforcing phase and conductive network. Compared with the pure CNF, the GQD-reinforced activated CNF exhibits a greatly enlarged surface area from 140 to 2032 m2 g-1 as well as a significantly improved conductivity and strength of 5.5 and 2.5 times, respectively. The mechanism of the robust reinforcing effect is deeply investigated. As a freestanding supercapacitor electrode, the fabric performs a high capacitance of 335 F g-1 at 1 A g-1 and extremely high capacitance retentions of 77% at 100 A g-1 and 45% at 500 A g-1. Importantly, the symmetric device can be charged to 80% capacitance within only 2.2 s, showing great potential for high-power startup supplies.

Iron carbide/nitrogen-doped carbon core-shell nanostrctures: Solution-free synthesis and superior oxygen reduction performance.

Core-shell Fe3C@NC nanostructures constructed by Fe3C core encapsulated in N-doped carbon nanotubes (FFCN-MP4000) is designed and readily prepared via a facile and economical solid-state chemical route. By controlling the proportion of C and N in the starting materials, the composition of FeNC core-shell nanotubes was optimized, then provided more possible active sites as electrocatalysts, exhibited superior oxygen reduction performance. Onset potential (Eonset) of 0.96 V versus reversible hydrogen electrode (RHE) and half-wave potential (E1/2) of 0.83 V vs RHE was obtained in 0.1 M KOH, which are comparable to those of the commercial Pt/C catalyst (Eonset = 0.98 V, E1/2 = 0.84 V vs RHE). Notably, the limited current density for FFCN-MP4000 can reach to 6.6 mA cm-2, and it efficiently catalyzes 4-electron reduction of oxygen (n = 3.98) with a hydrogen peroxide yield of below 2.2%. In addition, the methanol tolerance and durability are even superior to commercial Pt/C catalyst. This work provides a facile and economical strategy for the feasible design of oxygen reduction reaction (ORR) electrocatalyst with high activity and low cost in alternative commercial Pt/C electrocatalyst.