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The discovery of the Van Allen radiation belts marked a prominent milestone in space physics. Recent advances, through the measurements of two CubeSat missions, have shed new light on the dynamics of energetic particles in the near‐Earth environment. Measurements from CSSWE, a student‐led mission, revealed that the decay of low‐energy neutrons, associated with cosmic rays impacting the atmosphere, is the primary source of relativistic electrons at the inner edge of the inner belt (Li et al., Nature, 2017, https://doi.org/10.1038/nature2464). Recently CIRBE captured striking details of energetic electron dynamics (Li et al., GRL, 2024, https://doi.org/10.1029/2023gl107521), further demonstrating high‐quality science achievable with CubeSat missions. Plain Language Summary CubeSats are small, low‐cost satellites that are becoming increasingly popular for scientific research. In this commentary, the author shares his personal experience of leading students and professionals in developing and operating two CubeSats that measure energetic particles in the near‐Earth environment. The first CubeSat was launched in 2012, operated until the end of 2014, and far exceeded expectations, producing valuable scientific results. The second CubeSat, launched in 2023, has a much more advanced instrument and revealed far more detailed dynamics of energetic particles. We believe such a commentary may be of general interest and provide encouragement to other teams involved in development of a CubeSat mission, which can be an excellent way to do high‐quality scientific research at a relatively low cost. Key Points High‐impact science can be accomplished by a student‐led CubeSat mission, with professional mentorship With continued miniaturization of spacecraft subsystems, high‐resolution and quality‐measurements from a CubeSat are achievable Synergistic team efforts, early and frequent testing, and a stroke of luck are required to be successful

Metal ‒ organic frameworks (MOFs) are widely studied molecular assemblies that have demonstrated promise for a range of potential applications. Given the unique and well-established photophysical and electrochemical properties of porphyrins, porphyrin-based MOFs are emerging as promising candidates for energy harvesting and conversion applications. Here we discuss the physical properties of porphyrin-based MOFs, highlighting the evolution of various optical and electronic features as a function of their modular framework structures and compositional variations. Porphyrins have been incorporated into metal–organic frameworks in a periodic fashion in order to exploit their unique photophysical and electrochemical properties. This article reviews progress in the field, focusing on the fundamental physical properties that arise in porphyrin-based MOFs.

When hydrogel materials with excellent biocompatibility and biodegradability are used as excellent new drug carriers in the treatment of cancer, they confer the following three advantages. First, hydrogel materials can be used as a precise and controlled drug release systems, which can continuously and sequentially release chemotherapeutic drugs, radionuclides, immunosuppressants, hyperthermia agents, phototherapy agents and other substances and are widely used in the treatment of cancer through radiotherapy, chemotherapy, immunotherapy, hyperthermia, photodynamic therapy and photothermal therapy. Second, hydrogel materials have multiple sizes and multiple delivery routes, which can be targeted to different locations and types of cancer. This greatly improves the targeting of drugs, thereby reducing the dose of drugs and improving treatment effectiveness. Finally, hydrogel can intelligently respond to environmental changes according to internal and external environmental stimuli so that anti-cancer active substances can be remotely controlled and released on demand. Combining the abovementioned advantages, hydrogel materials have transformed into a hit in the field of cancer treatment, bringing hope to further increase the survival rate and quality of life of patients with cancer.

•The proposed cross-stratified ensemble learning algorithm via three varied deep learning base learners can be used to improve the accuracy of brain age prediction, respectively.•It was demonstrated that the cross-stratified ensemble learning algorithm adapted to the age variation of the subjects in different age groups with the capability of balancing the learn differences of base learners.•The valuable biomarker of predicted age difference (PAD) presented the increased trend across the normal control (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD). As an important biomarker of neural aging, the brain age reflects the integrity and health of the human brain. Accurate prediction of brain age could help to understand the underlying mechanism of neural aging. In this study, a cross-stratified ensemble learning algorithm with staking strategy was proposed to obtain brain age and the derived predicted age difference (PAD) using T1-weighted magnetic resonance imaging (MRI) data. The approach was characterized as by implementing two modules: one was three base learners of 3D-DenseNet, 3D-ResNeXt, 3D-Inception-v4; another was 14 secondary learners of liner regressions. To evaluate performance, our method was compared with single base learners, regular ensemble learning algorithms, and state-of-the-art (SOTA) methods. The results demonstrated that our proposed model outperformed others models, with three metrics of mean absolute error (MAE), root mean-squared error (RMSE), and coefficient of determination (R2) of 2.9405 years, 3.9458 years, and 0.9597, respectively. Furthermore, there existed significant differences in PAD among the three groups of normal control (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD), with an increased trend across NC, MCI, and AD. It was concluded that the proposed algorithm could be effectively used in computing brain aging and PAD, and offering potential for early diagnosis and assessment of normal brain aging and AD.

Fungal chemical ecology is largely mediated by the metabolite(s) produced by individual biosynthetic gene clusters (BGCs) with antibiotic activities. We report a supercluster containing three BGCs that are jointly controlled by an embedded master regulator in the insect pathogen Metarhizium robertsii . Fungal secondary metabolites with antibiotic activities can promote fungal adaptation to diverse environments. Besides the global regulator, individual biosynthetic gene clusters (BGCs) usually contain a pathway-specific transcription factor for the tight regulation of fungal secondary metabolism. Here, we report the chemical biology mediated by a supercluster containing three BGCs in the entomopathogenic fungus Metarhizium robertsii . These clusters are jointly controlled by an embedded transcription factor that orchestrates the collective production of four classes of chemicals: ustilaginoidin, indigotide, pseurotin, and hydroxyl-ovalicin. The ustilaginoidin BGC is implicated as a late-acquired cluster in Metarhizium to produce both the bis-naphtho-γ-pyrones and the monomeric naphtho-γ-pyrone glycosides (i.e., indigotides). We found that the biosynthesis of indigotides additionally requires the functions of paired methylglucosylation genes located outside the supercluster. The pseurotin/ovalicin BGCs are blended and mesosyntenically conserved to the intertwined pseurotin/fumagillin BGCs of Aspergillus fumigatus . However, the former have lost a few genes, including a polyketide synthase gene responsible for the production of a pentaene chain used for assembly with ovalicin to form fumagillin, as observed in A. fumigatus . The collective production of chemical cocktails by this supercluster was dispensable for fungal virulence against insects and could enable the fungus to combat different bacteria better than the metabolite(s) produced by an individual BGC could. Thus, our results unveil a novel strategy employed by fungi to manage chemical ecology against diverse bacteria. IMPORTANCE Fungal chemical ecology is largely mediated by the metabolite(s) produced by individual biosynthetic gene clusters (BGCs) with antibiotic activities. We report a supercluster containing three BGCs that are jointly controlled by an embedded master regulator in the insect pathogen Metarhizium robertsii . Four classes of chemicals, namely, ustilaginoidin, indigotide, pseurotin, and hydroxyl-ovalicin, are collectively produced by these three BGCs along with the contributions of tailoring enzyme genes located outside the supercluster. The production of these metabolites is not required for the fungal infection of insect hosts, but it benefits the fungus to combat diverse bacteria. The findings reveal and advocate a “the-more-the-better” strategy employed by fungi to manage effective adaptations to diverse environments.

Tissue defects can be accompanied by functional impairments that affect the health and quality of life of patients. Hydrogels are three-dimensional (3D) hydrophilic polymer networks that can be used as bionic functional tissues to fill or repair damaged tissue as a promising therapeutic strategy in the field of tissue engineering and regenerative medicine. This paper summarises and discusses four outstanding advantages of hydrogels and their applications and advances in the repair and regeneration of tissue defects. First, hydrogels have physicochemical properties similar to the extracellular matrix of natural tissues, providing a good microenvironment for cell proliferation, migration and differentiation. Second, hydrogels have excellent shape adaptation and tissue adhesion properties, allowing them to be applied to a wide range of irregularly shaped tissue defects and to adhere well to the defect for sustained and efficient repair function. Third, the hydrogel is an intelligent delivery system capable of releasing therapeutic agents on demand. Hydrogels are capable of delivering therapeutic reagents and releasing therapeutic substances with temporal and spatial precision depending on the site and state of the defect. Fourth, hydrogels are self-healing and can maintain their integrity when damaged. We then describe the application and research progress of functional hydrogels in the repair and regeneration of defects in bone, cartilage, skin, muscle and nerve tissues. Finally, we discuss the challenges faced by hydrogels in the field of tissue regeneration and provide an outlook on their future trends.

CIRBE (Colorado Inner Radiation Belt Experiment), a 3U CubeSat, was launched on 15 April 2023 into a sun synchronous orbit (97.4° inclination and 509 km altitude). The sole science payload onboard is REPTile‐2 (Relativistic Electron and Proton Telescope integrated little experiment—2), an advanced version of REPTile which operated in space between 2012 and 2014. REPTile‐2 has 60 channels for electrons (0.25–6 MeV) and 60 channels for protons (6.5–100 MeV). It has been working well, capturing detailed dynamics of the radiation belt electrons, including several orders of magnitude enhancements of the outer belt electrons after an intense magnetic storm, multiple “wisps”‐ an electron precipitation phenomenon associated with human‐made very low frequency (VLF) waves in the inner belt, and “drift echoes” of 0.25–1.4 MeV electrons across the entire inner belt and part of the outer belt. These new observations provide opportunities to test the understanding of the physical mechanisms responsible for these features. Plain Language Summary Energetic electrons of 100s of keV (1,000 electric volt) to MeV (million electric volt) existing in the near‐Earth environment have detrimental effects on spacecraft subsystems and the bodies of astronauts during their extravehicular activity (e.g., Baker, 2002, https://doi.org/10.1126/science.1074956). Their source, loss, and variations have been a long‐standing research topic. Recent advancements in miniaturization of spacecraft and instrumentation make CubeSats (in the shape of a cube, easier for launch and deployment) a viable means to conduct space‐borne research. Colorado Inner Radiation Belt Experiment (CIRBE) is a 3U (10 cm × 10 cm × 34 cm) CubeSat with only one science instrument onboard: Relativistic Electron and Proton Telescope integrated little experiment −2 (REPTile‐2), which is an advanced version of the previously flown REPTile. REPTile‐2, thanks to its high energy and time resolution, revealed detailed dynamic features of the radiation belt electrons, which will further our understanding of and ability to predict the dynamics of these energetic electrons. Key Points Detailed variations of relativistic electrons over a wide energy range, 0.25–6 MeV, in the Earth's magnetosphere were captured Multiple “wisps,” an electron precipitation phenomenon associated with human‐made VLF waves in the inner belt, were measured “Drift echoes” or “zebra stripes” of 0.25–1.4 MeV electrons across the entire inner belt and part of the outer belt, have been observed

Ultra‐low frequency (ULF) waves in the Pc5 band are essential for the transport of electrons in the radiation belt and the transport of energy from the solar wind into the magnetosphere. Based on ∼14‐year of electric field data from Cluster satellite, the spatial distributions of power spectral densities (PSD) of electric field ULF waves in the inner magnetosphere are statistically investigated, suggesting that PSDs of electric ULF wave increase with increasing L and depend on magnetic latitude (MLAT). PSDs of electric ULF wave are greater at noon for lower |MLAT| and at midnight for higher |MLAT|. Moreover, the L and MLAT dependent empirical formulas for the ULF magnetic and electric fields are provided, enabling the latitudinal effect in the radial diffusion evaluation. The results in this paper suggest a potential shift in the contribution to radial diffusion may occur between the magnetic and electric fields at different MLATs. Plain Language Summary Ultra‐low frequency waves are fluctuations of magnetic field in the inner magnetosphere. The frequencies of the ULF waves in the Pc5 band (1.6–6.7 mHz) are close to the drift frequency of the radiation belt electrons, thus the ULF waves can drift resonant with the relativistic electrons through the radial diffusion process. Radial diffusion can be described quantitatively by radial diffusion coefficients, which are determined by the PSDs of electric and magnetic field ULF waves. However, previous studies of the spatial distribution of the electric field ULF waves have more commonly been measured at the magnetic equator. The latitudinal distribution of electric field ULF waves has not been studied. In this study, multi‐year measurements from the Cluster missions are used to present a statistical analysis of the distribution of electric field ULF wave PSDs over the MLAT. Furthermore, the empirical models for the spatial distribution of the magnetic and electric field PSDs are provided to improve the calculation of the radial diffusion coefficient. Our results may have significant implications for the study of the radial diffusion of non‐equatorial mirroring radiation belt electrons. Key Points The electric field PSDs of the ULF wave increase with growing L and |MLAT| The electric field ULF wave PSDs are greater at noon for lower |MLAT| and greater at midnight for higher |MLAT| The empirical models for the PSDs of magnetic and electric field ULF wave are provided to improve the radial diffusion coefficient

Electrons derived from cosmic rays become trapped in the radiation belts that surround Earth, but how the electrons are generated has been uncertain; new measurements confirm the involvement of neutron decay. Source of electrons in Earth's inner radiation belt When cosmic rays hit the upper atmosphere, the collisions with atoms create 'albedo neutrons' which subsequently decay to protons and electrons (and electron antineutrinos) with a half-life of about 10 minutes. This is the main source of the protons trapped in Earth's Van Allen radiation belts. In principle, this process could also be the source of the trapped electrons, but it has been difficult to clarify because the electron intensity varies greatly whereas the neutron-decay rate should be fairly constant. Xinlin Li and collaborators report measurements of the electron density near the inner edge of the inner radiation belt and demonstrate that this population of electrons indeed comes from neutron decay. The Galaxy is filled with cosmic-ray particles, mostly protons with kinetic energies greater than hundreds of megaelectronvolts. Around Earth, trapped energetic protons, electrons and other particles circulate at altitudes from about 500 to 40,000 kilometres in the Van Allen radiation belts. Soon after these radiation belts were discovered six decades ago, it was recognized that the main source of inner-belt protons (with kinetic energies of tens to hundreds of megaelectronvolts) is cosmic-ray albedo neutron decay (CRAND) 1 . In this process, cosmic rays that reach the upper atmosphere interact with neutral atoms to produce albedo neutrons, which, being prone to β-decay, are a possible source of geomagnetically trapped protons and electrons. These protons would retain most of the kinetic energy of the neutrons, while the electrons would have lower energies, mostly less than one megaelectronvolt. The viability of CRAND as an electron source has, however, been uncertain, because measurements have shown that the electron intensity in the inner Van Allen belt can vary greatly, while the neutron-decay rate should be almost constant 2 , 3 . Here we report measurements of relativistic electrons near the inner edge of the inner radiation belt. We demonstrate that the main source of these electrons is indeed CRAND, and that this process also contributes to electrons in the inner belt elsewhere. Furthermore, measurement of the intensity of electrons generated by CRAND provides an experimental determination of the neutron density in near-Earth space—2 × 10 −9 per cubic centimetre—confirming theoretical estimates 4 .

The robotic navigation task is to find a collision-free path among a mass of stationary or migratory obstacles. Various well-established algorithms have been applied to solve navigation tasks. It is necessary to test the performance of designed navigation algorithms in practice. However, it seems an extremely unwise choice to implement them in a real environment directly unless their performance is guaranteed to be acceptable. Otherwise, it takes time to test navigation algorithms because of a long training process, and imperfect performance may cause damage if the robot collides with obstacles. Hence, it is of key significance to develop a mobile robot analysis platform to simulate the real environment which has the ability to replicate the exact application scenario and be operated in a simple manner. This paper introduces a brand new analysis platform named robot navigation analysis platform (RoNAP), which is an open-source platform developed using the Python environment. A user-friendly interface supports its realization for the evaluation of various navigation algorithms. A variety of existing algorithms were able to achieve desired test results on this platform, indicating its feasibility and efficiency for navigation algorithm analysis.