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The emergence of bioorthogonal reactions has greatly broadened the scope of biomolecule labeling and detecting. Of all the bioorthogonal reactions that have been developed, the copper-catalyzed azide-alkyne cycloaddition (CuAAC) is the most widely applied one, mainly because of its relatively fast kinetics and high efficiency. However, the introduction of copper species to in vivo systems raises the issue of potential toxicity. In order to reduce the copper-induced toxicity and further improve the reaction kinetics and efficiency, different strategies have been adopted, including the development of diverse copper chelating ligands to assist the catalytic cycle and the development of chelating azides as reagents. Up to now, the optimization of CuAAC has facilitated its applications in labeling and identifying either specific biomolecule species or on the omics level. Herein, we mainly discuss the efforts in the development of CuAAC to better fit the bioorthogonal reaction criteria and its bioorthogonal applications both in vivo and in vitro.

Direct seawater electrolysis is promising for sustainable hydrogen gas (H 2 ) production. However, the chloride ions in seawater lead to side reactions and corrosion, which result in a low efficiency and poor stability of the electrocatalyst and hinder the use of seawater electrolysis technology. Here we report a corrosion-resistant RuMoNi electrocatalyst, in which the in situ-formed molybdate ions on its surface repel chloride ions. The electrocatalyst works stably for over 3000 h at a high current density of 500 mA cm −2 in alkaline seawater electrolytes. Using the RuMoNi catalyst in an anion exchange membrane electrolyzer, we report an energy conversion efficiency of 77.9% and a current density of 1000 mA cm −2 at 1.72 V. The calculated price per gallon of gasoline equivalent (GGE) of the H 2 produced is $ 0.85, which is lower than the 2026 technical target of $ 2.0/GGE set by the United Stated Department of Energy, thus, suggesting practicability of the technology. Direct seawater electrolysis is promising for sustainable hydrogen production but suffers severe side reactions and corrosion. Here, the authors report a corrosion-resistant electrocatalyst with in situ-formed chloride-ion-repelling cation layer for efficient and long-lasting seawater oxidation.

For improving manufacturing efficiency and minimizing costs, design for additive manufacturing (AM) has been accordingly proposed. The existing design for AM methods are mainly surrogate model based. Due to the increasingly available data nowadays, machine learning (ML) has been applied to medical diagnosis, image processing, prediction, classification, learning association, etc. A variety of studies have also been carried out to use machine learning for optimizing the process parameters of AM with corresponding objectives. In this paper, a ML integrated design for AM framework is proposed, which takes advantage of ML that can learn the complex relationships between the design and performance spaces. Furthermore, the primary advantage of ML over other surrogate modelling methods is the capability to model input–output relationships in both directions. That is, a deep neural network can model property–structure relationships, given structure–property input–output data. A case study was carried out to demonstrate the effectiveness of using ML to design a customized ankle brace that has a tunable mechanical performance with tailored stiffness.

Aims Assessing the global burden and health inequalities of Hypertension Heart Disease (HHD) during the period from 1990 to 2019. Methods Secondary analysis of the Global Burden of Disease (GBD) study in 2019, focusing on the burden of diseases, injuries, and risk factors worldwide. Disability-Adjusted Life Years (DALYs) data related to HHD are extracted from the 2019 GBD. Inequality Slope Index (SII) and Concentration Index are calculated to assess health inequalities across regions and countries. Results The total DALYs for HHD reached 21.51 million, demonstrating a substantial increase of 54.25% compared to the figures recorded in 1990, while the age-standardized DALY rates per 100,000 population for HHD in 2019 showed a notable decline to 268.19 (95% UI 204.57, 298.07), reflecting a significant decrease of 26.4% compared to the rates observed in 1990. The DALYs rate of hypertensive heart disease increases with age. Countries with moderate SDI accounted for 38.72% of the global burden of HHD in terms of DALYs. The highest age-standardized DALY rates (per 100,000) are predominantly concentrated in underdeveloped areas. In 1990 and 2019, the SII (per 100,000 population) for DALYs were − 121.6398 (95% CI -187.3729 to -55.90684) and − 1.592634 (95% CI -53.11027 to 49.925) respectively. The significant decline suggests a reduction in the inequality of age-standardized burden of HHD between high-income and low-income countries during this period. Conclusion The unequal prevalence of HHD across different populations can hinder the achievement of the “health for all” objective. Persistent disparities in HHD have been observed globally over the past thirty years. It is crucial to prioritize efforts towards reducing avoidable health inequalities associated with hypertension-related heart disease, particularly in low-income and middle-income countries.

3D point clouds deep learning is a promising field of research that allows a neural network to learn features of point clouds directly, making it a robust tool for solving 3D scene understanding tasks. While recent works show that point cloud convolutions can be invariant to translation and point permutation, investigations of the rotation invariance property for point cloud convolution has been so far scarce. Some existing methods perform point cloud convolutions with rotation-invariant features, existing methods generally do not perform as well as translation-invariant only counterpart. In this work, we argue that a key reason is that compared to point coordinates, rotation-invariant features consumed by point cloud convolution are not as distinctive. To address this problem, we propose a simple yet effective convolution operator that enhances feature distinction by designing powerful rotation invariant features from the local regions. We consider the relationship between the point of interest and its neighbors as well as the internal relationship of the neighbors to largely improve the feature descriptiveness. Our network architecture can capture both local and global context by simply tuning the neighborhood size in each convolution layer. We conduct several experiments on synthetic and real-world point cloud classifications, part segmentation, and shape retrieval to evaluate our method, which achieves the state-of-the-art accuracy under challenging rotations.

The high-throughput scalable production of cheap, efficient and durable electrocatalysts that work well at high current densities demanded by industry is a great challenge for the large-scale implementation of electrochemical technologies. Here we report the production of a two-dimensional molybdenum disulfide-based ink-type electrocatalyst by a scalable exfoliation technique followed by a thermal treatment. The catalyst delivers a high current density of 1000 mA cm −2 at an overpotential of 412 mV for the hydrogen evolution. Using the same method, we produce a cheap mineral-based catalyst possessing excellent performance for high-current-density hydrogen evolution. Noteworthy, production rate of this catalyst is one to two orders of magnitude higher than those previously reported, and price of the mineral is five orders of magnitude lower than commercial Pt electrocatalysts. These advantages indicate the huge potentials of this method and of mineral-based cheap and abundant natural resources as catalysts in the electrochemical industry. The large-scale implementation of electrochemical technologies will require the high-throughput production of high-performance, inexpensive catalysts. Here, authors demonstrate earth abundant molybdenite as raw materials to produce efficient MoS 2 catalysts for high current density H 2 evolution.

Rolling is a ubiquitous transport mode utilized by living organisms and engineered systems. However, rolling at the microscale has been constrained by the requirement of a physical boundary to break the spatial homogeneity of surrounding mediums, which limits its prospects for navigation to locations with no boundaries. Here, in the absence of real boundaries, we show that microswarms can execute rolling along virtual walls in liquids, impelled by a combination of magnetic and acoustic fields. A rotational magnetic field causes individual particles to self-assemble and rotate, while the pressure nodes of an acoustic standing wave field serve as virtual walls. The acoustic radiation force pushes the microswarms towards a virtual wall and provides the reaction force needed to break their fore-aft motion symmetry and induce rolling along arbitrary trajectories. The concept of reconfigurable virtual walls overcomes the fundamental limitation of a physical boundary being required for universal rolling movements. The application of rolling motion to microswarm navigation and cargo delivery has been constrained by the need for a physical boundary to roll along to date. Here, Zhang et al. solve this problem by introducing a reconfigurable virtual wall implemented by a combination of magnetic and acoustic fields.

Background N6-methyladenosine (m6A) RNA modification plays a critical role in various physiological and pathological conditions. However, the role of m6A modification in head and neck squamous cell carcinoma (HNSCC) remains elusive. Methods In this study, the expression of m6A demethylases was detected by HNSCC tissue microarray. m6A-RNA immunoprecipitation (MeRIP) sequencing and RNA sequencing were used to identify downstream targets of ALKBH5. Comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS) was used to explore the m6A “readers”. Tumor-infiltrating lymphocytes were analyzed in SCC7-bearing xenografts in C3H mice. Results Here, we demonstrate the downregulation of m6A status and upregulation of two demethylases in HNSCC. Silencing the m6A demethylase alkB homolog 5, RNA demethylase (ALKBH5) suppresses tumor progression in vitro and in vivo . m6A-RNA immunoprecipitation sequencing reveals that ALKBH5 downregulates the m6A modification of DDX58 mRNA. Moreover, RIG-I, encoded by the DDX58 mRNA, reverses the protumorigenic characteristics of ALKBH5. ChIRP-MS demonstrates that HNRNPC binds to the m6A sites of DDX58 mRNA to promote its maturation. ALKBH5 overexpression inhibits RIG-I-mediated IFNα secretion through the IKKε/TBK1/IRF3 pathway. The number of tumor-infiltrating lymphocytes in C3H immunocompetent mice is reduced by ALKBH5 overexpression and restored by IFNα administration. Upregulation of AKLBH5 negatively correlates with RIG-I and IFNα expression in HNSCC patients. Conclusions These findings unveil a novel mechanism of immune microenvironment regulation mediated by m6A modification through the ALKBH5/RIG-I/IFNα axis, providing a rationale for therapeutically targeting epitranscriptomic modulators in HNSCC.

Constructing stable electrodes which function over long timescales at large current density is essential for the industrial realization and implementation of water electrolysis. However, rapid gas bubble detachment at large current density usually results in peeling-off of electrocatalysts and performance degradation, especially for long term operations. Here we construct a mechanically-stable, all-metal, and highly active CuMo 6 S 8 /Cu electrode by in-situ reaction between MoS 2 and Cu. The Chevrel phase electrode exhibits strong binding at the electrocatalyst-support interface with weak adhesion at electrocatalyst-bubble interface, in addition to fast hydrogen evolution and charge transfer kinetics. These features facilitate the achievement of large current density of 2500 mA cm −2 at a small overpotential of 334 mV which operate stably at 2500 mA cm −2 for over 100 h. In-situ total internal reflection imaging at micrometer level and mechanical tests disclose the relationships of two interfacial forces and performance of electrocatalysts. This dual interfacial engineering strategy can be extended to construct stable and high-performance electrodes for other gas-involving reactions. Stable electrodes which operate at large current density are essential for industrial water electrolysis. Here, a highly active Chevrel phase electrode is reported to achieve 2500 mA/cm −2 current density for 300 hours at small overpotentials.

Background Long intergenic noncoding RNA p21 (lincRNA-p21) is considered a target of wild-type p53, but little is known about its regulation by mutant p53 and its functions during the progression of head and neck squamous cell carcinoma (HNSCC). Methods RNAscope was used to detect the expression and distribution of lincRNA-p21. Chromatin immunoprecipitation and electrophoretic mobility shift assays were performed to analyze the transcriptional regulation of lincRNA-p21 in HNSCC cells. The biological functions of lincRNA-p21 were investigated in vitro and in vivo. RNA immunoprecipitation and pull-down assays were used to detect the direct binding of lincRNA-p21. Results Lower lincRNA-p21 expression was observed in HNSCC tissues and indicated worse prognosis. Both wild and mutant type p53 transcriptionally regulated lincRNA-p21, but nuclear transcription factor Y subunit alpha (NF-YA) was essential for mutant p53 in the regulation of lincRNA-p21. Ectopic expression of lincRNA-p21 significantly inhibited cell proliferation capacity in vitro and in vivo and vice versa. Moreover, the overexpression of lincRNA-p21 induced G1 arrest and apoptosis. Knockdown NF-YA expression reversed tumor suppressor activation of lincRNA-p21 in mutant p53 cells, not wild-type p53 cells. A negative correlation was observed between lincRNA-p21 and the phosphorylation of signal transducer and activator of transcription 3 (p-STAT3) in HNSCC tissues. High lincRNA-p21 expression inhibited Janus kinase 2 (JAK2)/STAT3 signal activation and vice versa. Further, we observed direct binding to STAT3 by lincRNA-p21 in HNSCC cells, which suppressed STAT3-induced oncogenic potential. Conclusions Our results revealed the transcriptional regulation of lincRNA-p21 by the mutant p53/NF-YA complex in HNSCC. LincRNA-p21 acted as a tumor suppressor in HNSCC progression, which was attributed to direct binding to STAT3 and blocking of JAK2/STAT3 signaling.