Approaching Ultimate Synthesis Reaction Rate of Ni-Rich Layered Cathodes for Lithium-Ion Batteries.

Nickel-rich layered oxide LiNixCoyMnzO2 (NCM, x + y + z = 1) is the most promising cathode material for high-energy lithium-ion batteries. However, conventional synthesis methods are limited by the slow heating rate, sluggish reaction dynamics, high energy consumption, and long reaction time. To overcome these challenges, we first employed a high-temperature shock (HTS) strategy for fast synthesis of the NCM, and the approaching ultimate reaction rate of solid phase transition is deeply investigated for the first time. In the HTS process, ultrafast average reaction rate of phase transition from Ni0.6Co0.2Mn0.2(OH)2 to Li- containing oxides is 66.7 (% s-1), that is, taking only 1.5 s. An ultrahigh heating rate leads to fast reaction kinetics, which induces the rapid phase transition of NCM cathodes. The HTS-synthesized nickel-rich layered oxides perform good cycling performances (94% for NCM523, 94% for NCM622, and 80% for NCM811 after 200 cycles at 4.3 V). These findings might also assist to pave the way for preparing effectively Ni-rich layered oxides for lithium-ion batteries.

High-performance flexible p-type Ce-filled Fe3CoSb12 skutterudite thin film for medium-to-high-temperature applications.

P-type Fe3CoSb12-based skutterudite thin films are successfully fabricated, exhibiting high thermoelectric performance, stability, and flexibility at medium-to-high temperatures, based on preparing custom target materials and employing advanced pulsed laser deposition techniques to address the bonding challenge between the thin films and high-temperature flexible polyimide substrates. Through the optimization of fabrication processing and nominal doping concentration of Ce, the thin films show a power factor of >100 µW m-1 K-2 and a ZT close to 0.6 at 653 K. After >2000 bending cycle tests at a radius of 4 mm, only a 6 % change in resistivity can be observed. Additionally, the assembled p-type Fe3CoSb12-based flexible device exhibits a power density of 135.7 µW cm-2 under a temperature difference of 100 K with the hot side at 623 K. This work fills a gap in the realization of flexible thermoelectric devices in the medium-to-high-temperature range and holds significant practical application value.

Electroacupuncture improves apoptosis of nucleus pulposus cells via the IL-22/JAK2-STAT3 signaling pathway in a rat model of cervical intervertebral disk degeneration.

BACKGROUND: Cervical spondylosis (CS) is a prevalent disorder that can have a major negative impact on quality of life. Traditional conservative treatment has limited efficacy, and electroacupuncture (EA) is a novel treatment option. We investigated the application and molecular mechanism of EA treatment in a rat model of cervical intervertebral disk degeneration (CIDD). METHODS: The CIDD rat model was established, following which rats in the electroacupuncture (EA) group received EA. For overexpression of IL-22 or inhibition of JAK2-STAT3 signaling, the rats were injected intraperitoneally with recombinant IL-22 protein (p-IL-22) or the JAK2-STAT3 (Janus kinase 2-signal transducer and activator of transcription protein 3) inhibitor AG490 after model establishment. Rat nucleus pulposus (NP) cells were isolated and cultured. Cell counting kit-8 and flow cytometry were used to analyze the viability and apoptosis of the NP cells. Expression of IL-22, JAK2 and STAT3 was determined using RT-qPCR. Expression of IL-22/JAK2-STAT3 pathway and apoptosis related proteins was detected by Western blotting (WB). RESULTS: EA protected the NP tissues of CIDD rats by regulating the IL-22/JAK2-STAT3 pathway. Overexpression of IL-22 significantly promoted the expression of tumor necrosis factor (TNF)-α, IL-6, IL-1ß, matrix metalloproteinase (MMP)3 and MMP13 compared with the EA group. WB demonstrated that the expression of IL-22, p-JAK2, p-STAT3, caspase-3 and Bax in NP cells of the EA group was significantly reduced and Bcl-2 elevated compared with the model group. EA regulated cytokines and MMP through activation of IL-22/JAK2-STAT3 signaling in CIDD rat NP cells. CONCLUSION: We demonstrated that EA affected apoptosis by regulating the IL-22/JAK2-STAT3 pathway in NP cells and reducing inflammatory factors in the CIDD rat model. The results extend our knowledge of the mechanisms of action underlying the effects of EA as a potential treatment approach for CS in clinical practice.

Altered N-linked glycosylation in depression: A pre-clinical study.

BACKGROUND: Neuroimmune plays an important role in major depressive disorders (MDD). N-linked protein glycosylation (NLG) might contribute to depression by regulating the neuroinflammatory response. As microglia is the main executor of neuroimmune function in the central neural system (CNS), targeting the process of N-linked protein glycosylation of microglia in the mice used for studying depression might potentially offer new avenues for the strategy for MDD. METHODS: The chronic unpredictable mild stress (CUMS) mouse model was established for the whole brain microglia isolating. Then, RNA samples of microglia were extracted for transcriptome sequencing and mRNA analysis. Immunofluorescence (IF) was used to identify the expression level of NLG-related enzyme, B4galt1, in microglia. RESULTS: The data showed that NLG was positively related to depression. Moreover, the NLG-related gene, B4galt1 increased expression in the microglia of CUMS mice. Then, the inhibition of NLG reversed the depressive behavior in CUMS mice. The expression level of B4galt1 in CUMS mice was upregulating following the NLG-inhibitor treatment. Similar results haven't been observed in neurons. Information obtained from these experiments showed increasing expression of B4galt1 in microglia following depressive-like behaviors. CONCLUSIONS: These findings indicate that NLG in microglia is associated with MDD, and suggest that therapeutically targeting NLG might be an effective strategy for depression. LIMITATIONS: How to modulate the B4galt1 or NLG pathways in microglia efficiently and economically request new technologies.

Impacts of social deprivation on mortality and protective effects of greenness exposure in Hong Kong, 1999-2018: A spatiotemporal perspective.

Addressing health inequality is crucial for fostering healthy city development. However, there is a dearth of literature simultaneously investigating the effects of social deprivation and greenness exposure on mortality risks, as well as how greenness exposure may mitigate the adverse effect of social deprivation on mortality risks from a spatiotemporal perspective. Drawing on socioeconomic, remote sensing, and mortality record data, this study presents spatiotemporal patterns of social deprivation, population weighted greenness exposure, and all-cause and cause-specific mortality in Hong Kong. A Bayesian regression model was applied to investigate the impacts of social deprivation and greenness exposure on mortality and examine how socioeconomic inequalities in mortality may vary across areas with different greenness levels in Hong Kong from 1999 to 2018. We observed a decline in social deprivation (0.67-0.56), and an increase in greenness exposure (0.34-0.41) in Hong Kong during 1999-2018. Areas with high mortality gradually clustered in the Kowloon Peninsula and the northern regions of Hong Kong Island. Adverse impacts of social deprivation on all-cause mortality weakened in recent years (RR from 2009 to 2013: 1.103, 95%CI: 1.051-1.159, RR from 2014 to 2018: 1.041 95%CI: 0.950-1.139), while the protective impacts of greenness exposure consistently strengthened (RR from 1999 to 2003: 0.903, 95%CI: 0.827-0.984, RR from 2014 to 2018: 0.859, 95%CI: 0.763-0.965). Moreover, the adverse effects of social deprivation on mortality risks were found to be higher in areas with lower greenness exposure. These findings provide evidence of associations between social deprivation, greenness exposure, and mortality risks in Hong Kong over the past decades, and highlight the potential of greenness exposure to mitigate health inequalities. Our study provides valuable implications for policymakers to develop a healthy city.

Boosting thermoelectric performance of single-walled carbon nanotubes-based films through rational triple treatments.

Single-walled carbon nanotubes (SWCNTs)-based thermoelectric materials, valued for their flexibility, lightweight, and cost-effectiveness, show promise for wearable thermoelectric devices. However, their thermoelectric performance requires significant enhancement for practical applications. To achieve this goal, in this work, we introduce rational "triple treatments" to improve the overall performance of flexible SWCNT-based films, achieving a high power factor of 20.29 µW cm-1 K-2 at room temperature. Ultrasonic dispersion enhances the conductivity, NaBH4 treatment reduces defects and enhances the Seebeck coefficient, and cold pressing significantly densifies the SWCNT films while preserving the high Seebeck coefficient. Also, bending tests confirm structural stability and exceptional flexibility, and a six-legged flexible device demonstrates a maximum power density of 2996 µW cm-2 at a 40 K temperature difference, showing great application potential. This advancement positions SWCNT films as promising flexible thermoelectric materials, providing insights into high-performance carbon-based thermoelectrics.

Serial tissue Doppler imaging in the evaluation of bronchopulmonary dysplasia-associated pulmonary hypertension among extremely preterm infants: a prospective observational study.

Objectives: To evaluate serial tissue Doppler cardiac imaging (TDI) in the evolution of bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) among extremely preterm infants. Design: Prospective observational study. Setting: Single-center, tertiary-level neonatal intensive care unit. Patients: Infant born <28 weeks gestation. Main outcome measures: Utility of TDI in the early diagnosis and prediction of BPD-PH and optimal timing for screening of BPD-PH. Results: A total of 79 infants were included. Of them, 17 (23%) had BPD-PH. The mean gestational age was 25.9 ± 1.1 weeks, and mean birth weight was 830 ± 174 g. The BPD-PH group had a high incidence of hemodynamically significant patent ductus arteriosus (83% vs. 56%, p < 0.018), longer oxygen days (96.16 ± 68.09 vs. 59.35 ± 52.1, p < 0.008), and prolonged hospital stay (133.8 ± 45.9 vs. 106.5 ± 37.9 days, p < 0.005). The left ventricular eccentricity index (0.99 ± 0.1 vs. 1.1 ± 0.7, p < 0.01) and the ratio of acceleration time to right ventricular ejection time showed a statistically significant trend from 33 weeks (0.24 ± 0.05 vs. 0.28 ± 0.05, p < 0.05). At 33 weeks, the BPD-PH group showed prolonged isovolumetric contraction time (27.84 ± 5.5 vs. 22.77 ± 4, p < 0.001), prolonged isovolumetric relaxation time (40.3 ± 7.1 vs. 34.9 ± 5.3, p < 0.003), and abnormal myocardial performance index (0.39 ± 0.05 vs. 0.32 ± 0.03, p < 0.001). These differences persisted at 36 weeks after conceptional gestational age. Conclusions: TDI parameters are sensitive in the early evolution of BPD-PH. Diagnostic accuracy can be increased by combining the TDI parameters with conventional echocardiographic parameters. BPD-PH can be recognizable as early as 33-34 weeks of gestation.

Predictive model and risk analysis for coronary heart disease in people living with HIV using machine learning.

OBJECTIVE: This study aimed to construct a coronary heart disease (CHD) risk-prediction model in people living with human immunodeficiency virus (PLHIV) with the help of machine learning (ML) per electronic medical records (EMRs). METHODS: Sixty-one medical characteristics (including demography information, laboratory measurements, and complicating disease) readily available from EMRs were retained for clinical analysis. These characteristics further aided the development of prediction models by using seven ML algorithms [light gradient-boosting machine (LightGBM), support vector machine (SVM), eXtreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), decision tree, multilayer perceptron (MLP), and logistic regression]. The performance of this model was assessed using the area under the receiver operating characteristic curve (AUC). Shapley additive explanation (SHAP) was further applied to interpret the findings of the best-performing model. RESULTS: The LightGBM model exhibited the highest AUC (0.849; 95% CI, 0.814-0.883). Additionally, the SHAP plot per the LightGBM depicted that age, heart failure, hypertension, glucose, serum creatinine, indirect bilirubin, serum uric acid, and amylase can help identify PLHIV who were at a high or low risk of developing CHD. CONCLUSION: This study developed a CHD risk prediction model for PLHIV utilizing ML techniques and EMR data. The LightGBM model exhibited improved comprehensive performance and thus had higher reliability in assessing the risk predictors of CHD. Hence, it can potentially facilitate the development of clinical management techniques for PLHIV care in the era of EMRs.

Ionic Rectification by Dynamic Regulation of the Electric Double Layer at the Hydrogel Interface.

Hydrogels play a pivotal role in the realm of iontronics, contributing to the realization of futuristic human-machine interactions. The electric double layer (EDL) between the hydrogel and electrode provides an essential ionic-electronic coupling interface. While prior investigations primarily delved into elucidating the formation mechanism of the EDL, our study shifts the focus to showcasing the current generation through the mechanical modulation of the EDL at the hydrogel-metal interfaces. The dynamic EDL was constructed by the mechano-driven contact-separation process between the polyacrylamide (PAAm) hydrogel and Au. Influencing factors on the dynamic regulation of the EDL such as ion concentration, types of salt, contact-separation frequency, and deformation degree were investigated. Dehydration usually limits the practical applications of hydrogels, and it is a long-standing and difficult problem. However, it seemed to be able to slow the EDL formation process here, resulting in a sustained continuous direct current signal output. Such hydrogel iontronics could rectify the displacement electronic current of a triboelectric nanogenerator by the ionic current. The directional migration of ions could be further enhanced by using charge-collecting metals with different work functions, for example, Au and Al. It offers a paradigm to enable ionic rectification that could be seamlessly incorporated into electronic systems, ushering in a new era for efficient energy harvesting and biomimetic nervous systems.

A novel fluorescent probe for visualizing viscosity changes in lipid droplets during chemotherapy-induced ferroptosis.

BACKGROUND: Ferroptosis, as a novel form of cell death, is becoming one of the hot topics in cancer treatment research. It differs from necrosis and autophagy in that it involves the accumulation of lipid peroxides and is triggered by iron dependency. Recent studies have suggested that this mechanism may alter the viscosity or structure of lipid droplets (LDs). The relationship between LDs viscosity and ferroptosis remains an active area of research with limited reports at present. Additionally, there is a lack of effective anticancer drugs targeting the ferroptosis pathway to promote ferroptosis in tumour cells. Therefore, the development of tools to detect viscosity changes during ferroptosis and targeted therapeutic strategies is of great significance. RESULTS: By coupling 1,3-indandione with naphthalimide, including decamethylamine as a LDs recognition group, we designed and synthesized an environmental fluorescent probe that induces intramolecular charge transfer (TICT) effects. Notably, the diffusion and transport of intracellular substances may be affected in highly viscous environments. Under such conditions, intracellular iron ions may accumulate, leading to peroxide production and cellular damage, which can trigger ferroptosis. Therefore, WD-1 achieved excellent in situ bioimaging of LDs targeting and its viscosity during ferroptosis in HeLa cells and zebrafish. Furthermore, it was observed that WD-1 effectively differentiated between malignant and normal cells during this process, highlighting its potential significance in distinguishing cellular states. In addition, we used the antitumour drug paclitaxel to study ferroptosis in cancer cells. These findings not only provide an excellent tool for the development of the ferroptosis response, but also are crucial for understanding the biological properties of LDs during the ferroptosis response. SIGNIFICANCE AND NOVELTY: Based on a powerful tool of fluorescent probe with in vivo bioimaging, we developed WD-1 to track the impact of paclitaxel on the process of ferroptosis in living cells. Therefore, we preliminarily believe that paclitaxel may affect the occurrence of ferroptosis and control apoptosis in cancer cells. These findings not only serve as an exceptional tool for advancing our understanding of the ferroptosis response, but furthermore play a vital role in comprehending the biological characteristics of LDs in relation to ferroptosis.

Decoupling Carrier-Phonon Scattering Boosts the Thermoelectric Performance of n-Type GeTe-Based Materials.

The coupled relationship between carrier and phonon scattering severely limits the thermoelectric performance of n-type GeTe materials. Here, we provide an efficient strategy to enlarge grains and induce vacancy clusters for decoupling carrier-phonon scattering through the annealing optimization of n-type GeTe-based materials. Specifically, boundary migration is used to enlarge grains by optimizing the annealing time, while vacancy clusters are induced through the aggregation of Ge vacancies during annealing. Such enlarged grains can weaken carrier scattering, while vacancy clusters can strengthen phonon scattering, leading to decoupled carrier-phonon scattering. As a result, a ratio between carrier mobility and lattice thermal conductivity of ∼492.8 cm3 V-1 s-1 W-1 K and a peak ZT of ∼0.4 at 473 K are achieved in Ge0.67Pb0.13Bi0.2Te. This work reveals the critical roles of enlarged grains and induced vacancy clusters in decoupling carrier-phonon scattering and demonstrates the viability of fabricating high-performance n-type GeTe materials via annealing optimization.

Simultaneously Boosting Thermoelectric and Mechanical Properties of n-Type Mg3Sb1.5Bi0.5-Based Zintls through Energy-Band and Defect Engineering.

Incorporating donor doping into Mg3Sb1.5Bi0.5 to achieve n-type conductivity is one of the crucial strategies for performance enhancement. In pursuit of higher thermoelectric performance, we herein report co-doping with Te and Y to optimize the thermoelectric properties of Mg3Sb1.5Bi0.5, achieving a peak ZT exceeding 1.7 at 703 K in Y0.01Mg3.19Sb1.5Bi0.47Te0.03. Guided by first-principles calculations for compositional design, we find that Te-doping shifts the Fermi level into the conduction band, resulting in n-type semiconductor behavior, while Y-doping further shifts the Fermi level into the conduction band and reduces the bandgap, leading to enhanced thermoelectric performance with a power factor as high as >20 µW cm-1 K-2. Additionally, through detailed micro/nanostructure characterizations, we discover that Te and Y co-doping induces dense crystal and lattice defects, including local lattice distortions and strains caused by point defects, and densely distributed grain boundaries between nanocrystalline domains. These defects efficiently scatter phonons of various wavelengths, resulting in a low thermal conductivity of 0.83 W m-1 K-1 and ultimately achieving a high ZT. Furthermore, the dense lattice defects induced by co-doping can further strengthen the mechanical performance, which is crucial for its service in devices. This work provides guidance for the composition and structure design of thermoelectric materials.

RBM10 regulates the tumorigenic potential of human cancer cells by modulating PPM1B and YBX1 activities.

RNA binding protein RBM10 participates in various RNA metabolism, and its decreased expression or loss of function by mutation has been identified in many human cancers. However, how its dysregulation contributes to human cancer pathogenesis remains to be determined. Here, we found that RBM10 expression was decreased in breast tumors, and breast cancer patients with low RBM10 expression presented poorer survival rates. RBM10 depletion in breast cancer cells significantly promotes the cellular proliferation and migration. We further demonstrated that RBM10 forms a triple complex with YBX1 and phosphatase 1B (PPM1B), in which PPM1B serves as the phosphatase of YBX1. RBM10 knock-down markedly attenuated association between YBX1 and PPM1B, leading to elevated levels of YBX1 phosphorylation and its nuclear translocation. Furthermore, cancer cells with RBM10 depletion had a significantly accelerated tumor growth in nude mice. Importantly, these enhanced tumorigenic phenotypes can be reversed by overexpression of PPM1B. Our findings provide the mechanistic bases for functional loss of RBM10 in promoting tumorigenicity, and are potentially useful in the development of combined therapeutic strategies for cancer patients with defective RBM10.

Synergizing Machine Learning Algorithm with Triboelectric Nanogenerators for Advanced Self-Powered Sensing Systems.

The advancement of the Internet of Things (IoT) has increased the demand for large-scale intelligent sensing systems. The periodic replacement of power sources for ubiquitous sensing systems leads to significant resource waste and environmental pollution. Human staffing costs associated with replacement also increase the economic burden. The triboelectric nanogenerators (TENGs) provide both an energy harvesting scheme and the possibility of self-powered sensing. Based on contact electrification from different materials, TENGs provide a rich material selection to collect complex and diverse data. As the data collected by TENGs become increasingly numerous and complex, different approaches to machine learning (ML) and deep learning (DL) algorithms have been proposed to efficiently process output signals. In this paper, the latest advances in ML algorithms assisting solid-solid TENG and liquid-solid TENG sensors are reviewed based on the sample size and complexity of the data. The pros and cons of various algorithms are analyzed and application scenarios of various TENG sensing systems are presented. The prospects of synergizing hardware (TENG sensors) with software (ML algorithms) in a complex environment and their main challenges for future developments are discussed.

Site-selective sulfur anchoring produces sintering-resistant intermetallic ORR electrocatalysts for membrane electrode assemblies.

Intermetallic compounds are emerging as promising oxygen reduction reaction (ORR) catalysts for fuel cells due to their typically higher activity and durability compared to disordered alloys. However, the preparation of intermetallic catalysts often requires high-temperature annealing, which unfortunately leads to adverse sintering of the metal nanoparticles. Herein, we develop a scalable site-selective sulfur anchoring strategy that effectively suppresses alloy sintering, ensuring the formation of efficient intermetallic electrocatalysts with small sizes and high ordering degrees. The alloy-support interactions are precisely modulated by selectively modifying the alloy-support interfaces with oxidized sulfur species, thus simultaneously blocking both the nanoparticle migration and Oswald ripening pathways for sintering. Using this strategy, sub-5 nm PtCo intermetallic electrocatalysts enclosed by two atomic layers of Pt shells have been successfully prepared even at a metal loading higher than 30 wt%. The intermetallic catalysts exhibit excellent ORR performances in both rotating disk electrode and membrane electrode assembly conditions with a mass activity of 1.28 A mgPt-1 at 0.9 V (vs. RHE) and a power density of 1.0 W cm-2 at a current density of 1.5 A cm-2. The improved performances result from the enhanced Pt-Co electronic interactions and compressive surface strain generated by the highly ordering structure, while the atomic Pt shells prevent the dissolution of Co under highly acidic conditions. This work provides new insights to inhibit the sintering of nanoalloys and would promote the scalable synthesis and applications of platinum-based intermetallic catalysts.

Arthroscopy-assisted reduction and simultaneous robotic-assisted screw placement in the treatment of fractures of the posterior talar process.

PURPOSE: A fracture of the posterior talar process is easily missed because of its hidden position. Inappropriate treatment is likely to result in complications, such as nonunion of the fracture and traumatic arthritis. This study evaluated the outcomes of arthroscopy-assisted reduction combined with robotic-assisted screw placement in the treatment of fractures of the posterior talar process. METHODS: The clinical data for nine patients who underwent surgical treatment of a fracture of the posterior talar process at our institution between September 2017 and January 2021 were retrospectively reviewed. Arthroscopy-assisted reduction of the fracture was performed, and a cannulated screw was placed using three-dimensional orthopedic robotic-assisted navigation. RESULTS: The patients (seven men, two women) had a mean age of 36.33 ± 9.77 years and were followed up for 21 ± 5.43 months. The operation time was 106.67 ± 24.5 min with blood loss of 47.78 ± 9.05 ml. Primary healing was obtained in all cases, and no patient sustained a nerve or tendon injury, had fracture nonunion, or developed talar osteonecrosis. One patient developed subtalar arthritis, for which subtalar joint fusion was performed; pain was markedly less severe after cleaning. CONCLUSION: Arthroscopy-assisted reduction and robotic-assisted screw placement have the advantages of visualization of fracture reduction, minimal injury, and precise screw placement in the treatment of fractures of the posterior talar process.

Quantitative health risk assessment of microbial hazards from water sources for community and self-supply drinking water systems.

In low and medium income countries (LMIC) drinking water sources (wells and boreholes) often contain a high number of pathogenic microorganisms, that can pose significant human and environmental health risks. In this study, a quantitative microbial risk assessment approach based on existing literature was conducted to evaluate and compare the quantitative health risks associated with different age groups using various drinking water supply systems. Results showed that both community-supply and self-supply modes exhibit similar levels of risk. However, the self-supply water source consistently showed higher risks compared to the community-supply one. Borehole water was found to be a more suitable option than well water, consistently showing between 5 and 8 lower health risks for E. coli and fecal coliform levels, respectively. The sensitivity analysis further showed the importance of prioritizing the reduction of E. coli concentration in well water and fecal coliform concentration in borehole water. This study offers a fresh perception on quantifying the impact of exposure concentration and age groups, shedding light on how they affect environmental health risks. These findings provide valuable insights for stakeholders involved in the management and protection of water sources.

Piezocatalysis for Chemical-Mechanical Polishing of SiC: Dual Roles of t-BaTiO3 as a Piezocatalyst and an Abrasive.

Chemical mechanical polishing (CMP) offers a promising pathway to smooth third-generation semiconductors. However, it is still a challenge to reduce the use of additional oxidants or/and energy in current CMP processes. Here, a new and green atomically smoothing method: Piezocatalytic-CMP (Piezo-CMP) is reported. Investigation shows that the Piezo-CMP based on tetragonal BaTiO3 (t-BT) can polish the rough surface of a reaction sintering SiC (RS-SiC) to the ultra-smooth surface with an average surface roughness (Ra) of 0.45 nm and the rough surface of a single-crystal 4H-SiC to the atomic planarization Si and C surfaces with Ra of 0.120 and 0.157 nm, respectively. In these processes, t-BT plays a dual role of piezocatalyst and abrasive. That is, it piezo-catalytically generates in-situ active oxygen species to selectively oxidize protruding sites of SiC surface, yielding soft SiO2, and subsequently, it acts as a usual abrasive to mechanically remove these SiO2. This mechanism is further confirmed by density functional theory (DFT) calculation and molecular simulation. In this process, piezocatalytic oxidation is driven only by the original pressure and friction force of a conventional polishing process, thus, the piezo-CMP process do not require any additional oxidant and energy, being a green and effective polishing method.

Direct Capturing and Regulating Key Intermediates for High-Efficiency Oxygen Evolution Reactions.

Developing efficient oxygen evolution reaction (OER) electrocatalysts can greatly advance the commercialization of proton exchange membrane (PEM) water electrolysis. However, the unclear and disputed reaction mechanism and structure-activity relationship of OER pose significant obstacles. Herein, the active site and intermediate for OER on AuIr nanoalloys are simultaneously identified and correlated with the activity, through the integration of in situ shell-isolated nanoparticle-enhanced Raman spectroscopy and X-ray absorption spectroscopy. The AuIr nanoalloys display excellent OER performance with an overpotential of only 246 mV to achieve 10 mA cm-2 and long-term stability under strong acidic conditions. Direct spectroscopic evidence demonstrates that * OO adsorbed on IrOx sites is the key intermediate for OER, and it is generated through the O-O coupling of adsorbed oxygen species directly from water, providing clear support for the adsorbate evolution mechanism. Moreover, the Raman information of the * OO intermediate can serve as a universal "in situ descriptor" that can be obtained both experimentally and theoretically to accelerate the catalyst design. It unveils that weakening the interactions of * OO on the catalysts and facilitating its desorption would boost the OER performance. This work deepens the mechanistic understandings on OER and provides insightful guidance for the design of more efficient OER catalysts.

Transcriptomic and metabolomic differences between banana varieties which are resistant or susceptible to Fusarium wilt.

Background: Fusarium wilt, caused by Fusarium oxysporum f. sp. cubense race 4 (Foc4), is the most lethal disease of bananas in Asia. Methods: To better understand the defense response of banana to Fusarium wilt, the transcriptome and metabolome profiles of the roots from resistant and susceptible bananas inoculated with Foc4 were compared. Results: After Foc4 inoculation, there were 172 and 1,856 differentially expressed genes (DEGs) in the Foc4-susceptible variety (G1) and Foc4-resistant variety (G9), respectively. In addition, a total of 800 DEGs were identified between G1 and G9, which were mainly involved in the oxidation-reduction process, cell wall organization, phenylpropanoid biosynthesis, and lipid and nitrogen metabolism, especially the DEGs of Macma4_08_g22610, Macma4_11_g19760, and Macma4_03_g06480, encoding non-classical arabinogalactan protein; GDSL-like lipase; and peroxidase. In our study, G9 showed a stronger and earlier response to Foc4 than G1. As the results of metabolomics, lipids, phenylpropanoids and polyketides, organic acids, and derivatives played an important function in response to Fusarium wilt. More importantly, Macma4_11_g19760 might be one of the key genes that gave G9 more resistance to Foc4 by a lowered expression and negative regulation of lipid metabolism. This study illustrated the difference between the transcriptomic and metabolomic profiles of resistant and susceptible bananas. These results improved the current understanding of host-pathogen interactions and will contribute to the breeding of resistant banana plants.