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Sanhan Huashi formula (SHHS), a traditional Chinese medicine (TCM), has shown significant therapeutic effects on coronavirus disease 2019 (COVID-19) in clinical settings. However, its specific mechanism and components still require further clarification. In vitro experiments with Vero-E6 cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demonstrated that SHHS effectively inhibited viral invasion and proliferation. Complementary in vivo experiments using K18-human angiotensin converting enzyme 2 (hACE2) mice exposed to virus-like particles (VLPs) further confirmed that SHHS impeded SARS-CoV-2 entry. Although SHHS did not demonstrate direct antiviral effects in K18-hACE2 mice challenged with SARS-CoV-2, it significantly alleviated pathological damage and decreased the expression of chemokines such as C–C motif ligand (CCL)-2, CCL-3, C–X–C motif ligand (CXCL)-1, CXCL-6, CXCL-9, CXCL-10, and CXCL-11 in the lungs, suggesting that SHHS exerts immunomodulatory and anti-inflammatory effects via the CCL-2–CXCL axis. Additional research using a lipopolysaccharide (LPS)-induced acute lung injury (ALI) and RAW264.7 cell model validated the ability of SHHS to reduce the levels of inflammatory biomarkers, including interleukin (IL)-1β, IL-6, and tumor necrosis factor-α (TNF-α). Using advanced analytical techniques such as ultrahigh-performance liquid chromatography coupled with linear trap quadrupole Orbitrap mass spectrometry (UHPLC-LTQ-Orbitrap-MS) and surface plasmon resonance (SPR), nodakenin was identified as a potent antiviral component of SHHS that targets the 3C-like protease (3CLpro), a finding supported by the hydrogen–deuterium exchange mass spectrometry (HDX-MS) and molecular docking analyses. Furthermore, nodakenin demonstrated a significant antiviral effect, reducing the viral load by more than 66%. This investigation reveals that SHHS can combat COVID-19 by inhibiting viral invasion and promoting anti-inflammatory effects.

Abstract Objective To investigate the mechanism by which heterogeneity in breast cancer developed and acted in single-cell transcriptomes. Methods The composition of breast cancer based on the single-cell transcriptomes of 54,055 high-quality cells from clinical specimens of 4 malignant and 4 non-malignant patients were investigated. Results We identified six common expression programs and six subtype-specific expression programs form malignant epithelial cells. The expression program of malignant epithelial cells exhibited activated EMT (Epithelial Mesenchymal Transition) in TME, which might indicate EMT intervention have a general therapeutic effect on various subtypes. Gene set enrichment analysis (GSEA) based on the top 50 highly NMF (non-negative matrix factorization) score genes in each program depicted the distinct function of each program in breast cancer progression. Moreover, we revealed the profound cellular heterogeneity of myeloid cell lineages in breast cancer. In macrophages, two mainly tumor associated macrophages (TAMs), TAM1 and TAM2, were also detected and the highly variable genes in TAM2 were strongly enriched in IFN-α and IFN-γ. The changes of lipid metabolism pathways in macrophages are closely related to the microenvironment of breast cancer. Conclusion We constructed a comprehensive single-cell transcriptome atlas of 54,055 cells from 4 malignant and 4 nonmalignant patients, providing insights into the mechanisms underlying breast cancer progression and the development of potential therapeutic strategies in breast cancer.

Abstract Fusarium oxysporum is a destructive plant pathogen with robust survival mechanisms, complicating control efforts. This study aimed to develop nanoformulated fungicides, screen antagonistic bacteria, and evaluate their combined efficacy. A novel self-emulsifying nanoemulsion (DZW) was formulated using zein and benzaldehyde-modified wheat gluten (BgWG) as carriers for dimethachlon (DTN). The preparation process optimized material ratios and emulsification techniques. Concurrently, antagonistic bacterial strains against F. oxysporum were screened via the plate standoff method, identifying Bacillus velezensis MLY71 as both antagonistic and compatible with DTN. The DZW nanoemulsion achieved a particle size of 93.22 nm, an encapsulation efficiency (EE) of 90.57%, and a DTN loading capacity (LC) of 67.09%, with sustained release over 96 h. The combination of DTN (0.04 mg·mL⁻¹) and B. velezensis MLY71 (1 × 10⁴ CFU·mL⁻¹) achieved a 76.66% inhibition rate against F. oxysporum MLY127, 1.71 times greater than DTN alone, indicating significant synergy. At a DTN concentration of 0.20 mg·mL⁻¹, the combination of DZW and MLY71 showed a synergy coefficient of 1.33. This synergy was also observed in soil environments, indicating its adaptability for controlling soil-borne pathogens. As sustainable management continues to gain attention in agricultural disease control, this study offers a promising strategy for achieving higher efficacy with the same fungicide dose or satisfactory control with reduced fungicide application. The excellent drug-loading performance of BgWG also expanded the applications of the wheat by-product gluten.

Abstract Blockchain is considered to be a promising technology due to its decentralization, open, and non tamperation. Nevertheless, the current blockchain system cannot replace traditional financial institutions because its performance and security indicators in the consensus algorithm are not perfect. As one of the emerging capacity expansion technologies, sharding technology improves throughput by grouping users and processing transactions in parallel. This paper proposes an improved Byzantine Fault Tolerance algorithm TV‐BRAFT. TV‐BRAFT calculates a trust value for each user through an incentive mechanism. The sharding scheme based on the trust value is adopted to reduce the probability of malicious nodes being allocated to the same partition, thus improving the security of the system. In the consensus, the system selects users with qualified trust values to form a verification group to supervise the consensus process and avoid submitting error transactions to the blockchain. In order to prove that the TV‐BRAFT can resist Byzantine attacks, a recursive formula is used to prove the security of sharding and the security of consensus within one shard. Finally, the simulation results show that the TV‐BRAFT not only guarantees the fairness of incentives but is also better than the Raft and PBFT algorithms in efficiency and throughput.

Abstract The significant energy consumption within data centers is an essential contributor to global energy consumption and carbon emissions. Therefore, reducing energy consumption and carbon emissions in data centers plays a crucial role in sustainable development. Traditional cloud computing has reached a bottleneck, primarily due to high energy consumption. The emerging federated cloud approach can reduce the energy consumption and carbon emissions of cloud data centers by leveraging the geographical differences of multiple cloud data centers in a federated cloud. In this paper, we propose Eco-friendly Reinforcement Learning in Federated Cloud (ERLFC), a framework that uses reinforcement learning for task scheduling in a federated cloud environment. ERLFC aims to intelligently consider the state of each data center and effectively harness the variations in energy and carbon emission ratios across geographically distributed cloud data centers in the federated cloud. We build ERLFC using Actor-Critic algorithm, which select the appropriate data center to assign a task based on various factors such as energy consumption, cooling method, waiting time of the task, energy type, emission ratio, and total energy consumption of the current cloud data center and the details of the next task. To demonstrate the effectiveness of ERLFC, we conducted simulations based on real-world task execution data, and the results show that ERLFC can effectively reduce energy consumption and emissions during task execution. In comparison to Round Robin, Random, SO, and GJO algorithms, ERLFC achieves respective reductions of 1.09, 1.08, 1.21, and 1.26 times in terms of energy saving and emission reduction.

Plant bacterial wilt is caused by Ralstonia solanacearum, a soilborne pathogen that infects plant conduits, leading to wilt disease. It is extremely difficult to cure plants infected with Ralstonia solanacearum; however, bactericide-loaded beads with hot-/wet-responsive properties may be able to release a biocide in line with the increase in the hot-/wet-associated activity of Ralstonia solanacearum, effectively killing the pathogenic cells and providing high levels of plant protection. A biopesticide, Tetramycin, was embedded in corn kernel powder (CKP)-based cores. An oil-phase mixture was sprayed onto the core surface to form a hot-/wet-responsive intermediate shell (IMS). Subsequently, a layer of ethyl cellulose (EC) and hydroxypropyl methyl cellulose (HPMC) was coated onto the IMS to create a single wet-responsive outer shell (OTS). The ratios of the components in the cores, including the corn kernel powder (CKP), xanthan gum (XG), and Tetramycin, were optimized, as well as those of the IMS, including pentaerythrityl tetrastearate (PETS), pentaerythrityl tetraoleate (PETO), polyethylene glycol stearate (PEG400MS), and polyethylene glycol monooleate (PEG400MO), and those of the outer shell (OTS), including ethyl cellulose (EC) and hydroxypropyl methyl cellulose (HPMC). A texture performance analysis, differential scanning calorimetry (DSC) analysis, thermogravimetric analysis (TGA), temperature and humidity response performance tests, scanning electron microscope (SEM) observations, and a field effectiveness test were conducted to characterize the Tetramycin-loaded beads. The results indicated that the optimal formula for the bead cores comprised a mass ratio of CKP/Tetramycin solution/XG = 13.5:23:2. The preferred mass ratio for IMS was PETS/PETO/PEG400MO = 10:30:10, and the formula for the applicable OTS consisted of a mass ratio of EC/HPMC = 5:1. In soil with a temperature of 30–35 °C and humidity of 30%, the release period of the Tetramycin-loaded beads, with a cumulative release rate of over 95%, could last up to 35 days. Furthermore, the Tetramycin-loaded beads exhibited a gradual and multi-cyclic release process under alternating hot/wet and dry/cold environments. The relative preventive efficacy of 54.74% on tobacco was revealed at a field-testing scale. A significant reduction in the abundance of Ralstonia solanacearum was also observed under treatment with the Tetramycin-loaded beads. The early fungal community structure exhibited higher consistency compared to the control. However, in the later stage, the diversity differences between the soil layers were restored. In conclusion, Tetramycin-loaded beads that could effectively respond to temperature and humidity fluctuations were developed, resulting in enhanced disease prevention efficacy and offering broad prospects for the prevention and control of Ralstonia solanacearum in agricultural settings.

Abstract Cloud file sharing (CFS) has become one of the important tools for enterprises to reduce technology operating costs and improve their competitiveness. Due to the untrustworthy cloud service provider, access control and security issues for sensitive data have been key problems to be addressed. Current solutions to these issues are largely related to the traditional public key cryptography, access control encryption or attribute-based encryption based on the bilinear mapping. The rapid technological advances in quantum algorithms and quantum computers make us consider the transition from the tradtional cryptographic primitives to the post-quantum counterparts. In response to these problems, we propose a lattice-based Ciphertext-Policy Attribute-Based Encryption(CP-ABE) scheme, which is designed based on the ring learing with error problem, so it is more efficient than that designed based on the learing with error problem. In our scheme, the indirect revocation and binary tree-based data structure are introduced to achieve efficient user revocation and dynamic management of user groups. At the same time, in order to further improve the efficiency of the scheme and realize file sharing across enterprises, the scheme also allows multiple authorities to jointly set up system parameters and manage distribute keys. Furthermore, by re-randomizing the user’s private key and update key, we achieve decryption key exposure resistance(DKER) in the scheme. We provide a formal security model and a series of security experiments, which show that our scheme is secure under chosen-plaintext attacks. Experimental simulations and evaluation analyses demonstrate the high efficiency and practicality of our scheme.

Nowadays, the increasing number of medical diagnostic data and clinical data provide more complementary references for doctors to make diagnosis to patients. For example, with medical data, such as electrocardiography (ECG), machine learning algorithms can be used to identify and diagnose heart disease to reduce the workload of doctors. However, ECG data is always exposed to various kinds of noise and interference in reality, and medical diagnostics only based on one-dimensional ECG data is not trustable enough. By extracting new features from other types of medical data, we can implement enhanced recognition methods, called multimodal learning. Multimodal learning helps models to process data from a range of different sources, eliminate the requirement for training each single learning modality, and improve the robustness of models with the diversity of data. Growing number of articles in recent years have been devoted to investigating how to extract data from different sources and build accurate multimodal machine learning models, or deep learning models for medical diagnostics. This paper reviews and summarizes several recent papers that dealing with multimodal machine learning in disease detection, and identify topics for future research.

Methods that analyse heterogeneity and compare tissue microenvironments using spatial omics data are challenging to develop. Here, the authors present SOTIP, a method that can perform spatial heterogeneity, spatial domain, and differential microenvironment analyses across multiple spatial omics modalities.

RNA polymerase II (Pol II) transcription factories play a central role in gene expression and 3D chromatin organization. Here, the authors demonstrate that RUVBL2 directly regulates Pol II clustering at active gene promoters.

Transcriptional plasticity interacts with natural selection in complex ways and is crucial for the survival of species under rapid climate change. How 3D genome architecture affects transcriptional plasticity and its interaction with genetic adaptation are unclear. We transplanted estuarine oysters to a new environment and found that genes located in active chromatin regions exhibited greater transcriptional plasticity, and changes in these regions were negatively correlated with selective signals. This indicates a trade-off between 3D active regions and selective signals in shaping plastic responses to a new environment. Specifically, a mutation, lincRNA, and changes in the accessibility of a distal enhancer potentially affect its interaction with the ManⅡa gene, which regulates the muscle function and survival of oysters. Our findings reveal that 3D genome architecture compensates for the role of genetic adaptation in environmental response to new environments and provide insights into synergetic genetic and epigenetic interactions critical for fitness-related trait and survival in a model marine species.

Abstract The orientation of fluorophores can reveal crucial information about the structure and dynamics of their associated subcellular organelles. Despite significant progress in super-resolution, fluorescence polarization microscopy remains limited to unique samples with relatively strong polarization modulation and not applicable to the weak polarization signals in samples due to the excessive background noise. Here we apply optical lock-in detection to amplify the weak polarization modulation with super-resolution. This novel technique, termed optical lock-in detection super-resolution dipole orientation mapping (OLID-SDOM), could achieve a maximum of 100 frames per second and rapid extraction of 2D orientation, and distinguish distance up to 50 nm, making it suitable for monitoring structural dynamics concerning orientation changes in vivo. OLID-SDOM was employed to explore the universal anisotropy of a large variety of GFP-tagged subcellular organelles, including mitochondria, lysosome, Golgi, endosome, etc. We found that OUF (Orientation Uniformity Factor) of OLID-SDOM can be specific for different subcellular organelles, indicating that the anisotropy was related to the function of the organelles, and OUF can potentially be an indicator to distinguish normal and abnormal cells (even cancer cells). Furthermore, dual-color super-resolution OLID-SDOM imaging of lysosomes and actins demonstrates its potential in studying dynamic molecular interactions. The subtle anisotropy changes of expanding and shrinking dendritic spines in live neurons were observed with real-time OLID-SDOM. Revealing previously unobservable fluorescence anisotropy in various samples and indicating their underlying dynamic molecular structural changes, OLID-SDOM expands the toolkit for live cell research.

Currently, data auditing is an important means to check the integrity of the data stored on the cloud. Existing data auditing schemes have done a lot of work in terms of functionality, implementation, and security. As we can see, all of these schemes are based on the auditing framework proposed by Ateniese et al., which uses random sampling to probabilistically check whether the data is integrity or not. But multiple repeated sampling may lead to an intersection between the challenge sets selected each time, reducing the probability of detection, and the time for detecting corrupted blocks will be indefinite. If the corrupted data is not found for a long time, the data remedial measures will become invalid, resulting in permanent data loss. To address the above problem, we designed an efficient sampling verification algorithm. Based on this algorithm, the auditing scheme is further optimized, and a dynamic auditing function has been developed for the scheme to facilitate data owners to update data. Through the security analysis, our scheme is soundness. The experiment shows that our sampling verification can detect corrupted blocks faster than other auditing schemes.

Abstract Combinational therapy is used for a long time in cancer treatment to overcome drug resistance related to monotherapy. Increased pharmacological data and the rapid development of deep learning methods have enabled the construction of models to predict and screen drug pairs. However, the size of drug libraries is restricted to hundreds to thousands of compounds. The ScaffComb framework, which aims to bridge the gaps in the virtual screening of drug combinations in large‐scale databases, is proposed here. Inspired by phenotype‐based drug design, ScaffComb integrates phenotypic information into molecular scaffolds, which can be used to screen the drug library and identify potent drug combinations. First, ScaffComb is validated using the US food and drug administration dataset and known drug combinations are successfully reidentified. Then, ScaffComb is applied to screen the ZINC and ChEMBL databases, which yield novel drug combinations and reveal an ability to discover new synergistic mechanisms. To our knowledge, ScaffComb is the first method to use phenotype‐based virtual screening of drug combinations in large‐scale chemical datasets.

Fluorescence polarization microscopy (FPM) analyzes both intensity and orientation of fluorescence dipole, and reflects the structural specificity of target molecules. It has become an important tool for studying protein organization, orientational order, and structural changes in cells. However, suffering from optical diffraction limit, conventional FPM has low orientation resolution and observation accuracy, as the polarization information is averaged by multiple fluorescent molecules within a diffraction-limited volume. Recently, novel super-resolution FPMs have been developed to break the diffraction barrier. In this review, we will introduce the recent progress to achieve sub-diffraction determination of dipole orientation. Biological applications, based on polarization analysis of fluorescence dipole, are also summarized, with focus on chromophore-target molecule interaction and molecular organization.

Polarization microscopy has been combined with single-molecule localization, but it’s often limited in either speed or resolution. Here the authors present polarized Structured Illumination Microscopy (pSIM), a method that uses polarized laser excitation to measure dye orientation during fast super-resolution live cell imaging.

Methodological advances have increased our understanding of chromatin structure through chromosome conformation capture techniques and high resolution imaging, but integration of these datasets is challenging. Here the authors propose GEM-FISH, a method for reconstructing the 3D models of chromosomes through systematically integrating both Hi-C and FISH data with the prior biophysical knowledge of a polymer model.

The occurrence of crop fungal diseases is closely related to warm environmental conditions. In order to control the release of fungicides in response to warm conditions, and enhance the efficacy, a series of thermo-responsive fungicide-loaded nanoparticles were developed. The fungicide azoxystrobin, solvent DEP, emulsifier Tween 80 and thermo-responsive component TDA were combined to create thermal-response oil phases, conditions for emulsification were then optimized. LDLS, zeta potential, FTIR, DSC, TGA, XRD, SEM and antifungal efficacy assays were carried out to investigate the characteristics and forming mechanism. The results indicated that the formula with 5 g azoxystrobin, 10 mL DEP, 6 mL Tween 80 and 2.5 g TDA constructed the proposed oil phase with the ability to transform from solid at 20 °C to softerned at 31.5 °C. Both DEP and TDA played key roles in interfering with the crystallization of azoxystrobin. The optimal T3t-c12 nanoparticles had a mean particle size of 162.1 nm, thermo-responsive morphological transformation between 20 °C and 30 °C, AZO crystal reforming after drying, the ability to attach to fungal spores and satisfied antifungal efficacy against P. nicotiana PNgz07 and A. niger A1513 at 30 °C. This report provides referable technical support for the construction of smart-release nanoparticles of other agrochemicals.

High catalytic activity of cathode material is one of the key requirements for the practical application of solid oxide fuel cells (SOFC). Here we designed and evaluated a novel non-metal P-doped (Bi, Sr)FeO3−δ, i.e., Bi0.5Sr0.5Fe0.95P0.05O3−δ (BSFP) oxide, as cathode material. BSFP with a cubic structure presents excellent chemical compatibility with Ce0.9Gd0.1O1.95 (GDC) electrolyte after sintering at 1100 °C. Impedance analysis reveals its polarization resistance (Rp) is as low as 0.18 Ω cm2 at 700 °C. Further kinetics study suggests the low-frequency process is the rate-limiting step of the oxygen reduction reaction (ORR). An anode-supported single cell delivers attractive power output of 0.56 W cm−2 at 700 °C. The electroactivity is superior to undoped (Bi, Sr)FeO3−δ, indicating that BSFP perovskite could be a promising cathode for SOFC operating at intermediate temperatures.

In Bitcoin financial system, a user’s privacy is supposed to be protected by means of anonymity. However, the anonymity makes illegal trades possible because nobody is able to reveal the real identities of the illegal users. In this paper, we propose a regulation scheme based on the ciphertext-policy hierarchical attribute-based encryption (CP-HABE). In the scheme, users’ identities are encrypted by using access policy and are contained in their transaction. A type of user is defined as the dependable regulation node, which is responsible for the regulation of transactions and encrypted identities. A new signature algorithm instead of the elliptic curve signature is adopted to generate wallet key pairs, this establishes a connection between wallet addresses and encrypted identities. When a transaction is doubted to involve illegal activities, the authorized regulation nodes are capable of revealing the users’ real identities and add the illegal identities to a public blacklist. Our system is based on a new CP-HABE scheme which is proved to be secure against chosen-plaintext attack in the standard model under the Bilinear Diffie–Hellman Exponent assumption. Finally, we give a performance analysis of our system. The proposed regulation system can reveal criminals’ identities undertaking illegal activities.

Fluorescence polarization is related to the dipole orientation of chromophores, making fluorescence polarization microscopy possible to reveal structures and functions of tagged cellular organelles and biological macromolecules. Several recent super resolution techniques have been applied to fluorescence polarization microscopy, achieving dipole measurement at nanoscale. In this review, we summarize both diffraction limited and super resolution fluorescence polarization microscopy techniques, as well as their applications in biological imaging.

Kinetochores are considered to be the key structures that physically connect spindle microtubules to the chromosomes and play an important role in chromosome segregation during mitosis. Due to different mechanisms of spindle assembly between centrosome-containing mitotic cells and acentrosomal meiotic oocytes, it is unclear how a meiotic spindle generates the poleward forces to drive two rounds of meiotic chromosome segregation to achieve genome haploidization. We took advantage of the fact that DNA beads are able to induce bipolar spindle formation without kinetochores and studied the behavior of DNA beads in the induced spindle in mouse eggs during meiosis II. Interestingly, DNA beads underwent poleward movements that were similar in timing and speed to the meiotic chromosomes, although all the beads moved together to the same spindle pole. Disruption of dynein function abolished the poleward movements of DNA beads but not of the meiotic chromosomes, suggesting the existence of different dynein-dependent and dynein-independent force generation mechanisms for the chromosome poleward movement, and the latter may be dependent on the presence of kinetochores. Consistent with the observed DNA bead poleward movement, sperm haploid chromatin (which also induced bipolar spindle formation after injection to a metaphase egg without forming detectable kinetochore structures) also underwent similar poleward movement at anaphase as DNA beads. The results suggest that in the chromatin-induced meiotic spindles, kinetochore attachments to spindle microtubules are not absolutely required for chromatin poleward movements at anaphase.