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Iron-based nanozymes, recognized for their biocompatibility and peroxidase-like activities, hold promise as catalysts in tumor therapy. However, their concurrent catalase-like activity undermines therapeutic efficacy by converting hydrogen peroxide in tumor tissues into oxygen, thus diminishing hydroxyl radical production. Addressing this challenge, this study introduces the hemin–cysteine–Fe (HCFe) nanozyme, which exhibits exclusive peroxidase-like activity. Constructed through a supramolecular assembly approach involving Fmoc-l-cysteine, heme, and Fe²⁺ coordination, HCFe distinctly incorporates heme and [Fe–S] within its active center. Sulfur coordination to the central Fe atom of Hemin is crucial in modulating the catalytic preference of the HCFe nanozyme towards peroxidase-like activity. This unique mechanism distinguishes HCFe from other bifunctional iron-based nanozymes, enhancing its catalytic selectivity even beyond that of natural peroxidases. This selective activity allows HCFe to significantly elevate ROS production and exert cytotoxic effects, especially against cisplatin-resistant esophageal squamous cell carcinoma (ESCC) cells and their xenografts in female mice when combined with cisplatin. These findings underscore HCFe's potential as a crucial component in multimodal cancer therapy, notably in augmenting chemotherapy efficacy. Iron-based nanozymes are promising for tumor catalytic therapy owing to their biocompatibility and peroxidase-like activity, but the concurrent catalase-like activity undermines the therapeutic efficacy. Here, the authors address this issue by developing a hemin–cysteine–Fe nanozyme, which exhibits catalytic selectivity and exclusive peroxidase-like activity. [ABSTRACT FROM AUTHOR]

Background: Cetuximab is extensively used in the treatment of metastatic colorectal cancer (mCRC). However, resistance poses a significant challenge to successful therapy. Recently, paraptosis, a non-classical programmed cell death, has garnered increased attention for its potential application value in antitumor treatments. We aimed to identify the essential pathways and signaling molecules involved in paraptosis inhibition and select them as therapeutic targets in cetuximab resistance. Additionally, engineered exosome technology is used as a drug delivery system with both targeted and effector properties. Results: By comparing the differential expression of paraptosis-related genes between drug-resistant colon cancer cells and sensitive cells, it was observed that the paraptosis level induced by cetuximab was significantly downregulated in drug-resistant cells. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified the focal adhesion kinase (FAK) signaling pathway as a key pathway involved in the suppression of paraptosis. The biological function of FAK in cetuximab-resistant cells was investigated through cell morphology observation, CCK-8 assay, colony formation assay, RT-qPCR, Western Blot, and loss-of-function experiments. The results showed that the FAK signaling pathway was significantly upregulated in cetuximab-resistant colon cancer cells, and siRNA interference targeting FAK could notably inhibit cell proliferation while upregulating the paraptosis level. Based on this, engineered colon cancer cells targeted and FAK siRNA loaded exosomes (CT-Exo-siFAK1) were constructed. In vitro experiments, CT-Exo-siFAK1 could effectively activate paraptosis and inhibit the proliferation of drug-resistant colon cancer cells. In vivo experiments also confirmed that CT-Exo-siFAK1 significantly suppressed tumor growth and metastasis while upregulating the paraptosis level. Conclusion: This study suggests that FAK signaling pathway-mediated inhibition of paraptosis levels is crucial in the sensitivity of cetuximab targeted therapy in colon cancer, and the use of engineered exosomes to deliver FAK siRNA may be an effective strategy to reverse cetuximab resistance. [ABSTRACT FROM AUTHOR]

In this article, the shock wave propagation in an expanded duct affected by downstream throttling at different positions is investigated. Fast-response transducers and schlieren visualization with a high-speed camera were employed to capture dynamic pressures on walls and shock interaction patterns, respectively. The results demonstrate that the characteristics of shock train motion can be strongly affected by throttling position. In the long model, where throttling device is mounted downstream away from nozzle exit, shock train moved upstream nearly linearly with the increasing in throttling, while in the short model, where throttling device is mounted at the nozzle exit, the shock train experienced downstream motion and upstream motion in turn during continuously increasing throttling. The evolution of shock interaction in the long model changed smoothly, while shock interaction in the short model is characterized by RR-to-MR transition and symmetry-to-asymmetry switching. Shock polar lines indicate that the local pressure ratios in both models show the same tendency which increases with throttling increasing. Therefore, the complex propagation of shock train in the short model still holds a monotonic change of local pressure ratio to respond to downstream disturbance. [ABSTRACT FROM AUTHOR]

With the popularization of Internet of Things applications, trillions of new devices with different application requirements, such as smart wearables and smart home appliances, will be connected to the network. Hence, it is crucial to ensure the data transmission security of these low-power and multifunctional sensor nodes. In this paper, a novel lightweight block cipher, GFSPX, is proposed for resource-constrained microdevices. The proposed algorithm combines a generalized Feistel structure with the substitution permutation networks structure to design the round function, which effectively addresses the inherent problem of slow diffusion in the traditional Feistel structure. Furthermore, the introduction of Addition or AND, Rotation, XOR operations in the round function to process part of the plaintext reduces the demand for hardware resource of the algorithm. The avalanche test results indicate that the GFSPX algorithm has strong diffusion and can satisfy the avalanche effect in just six rounds. The security analysis results verify the security of the GFSPX algorithm against differential and linear cryptanalysis attacks, algebraic attacks, structural attacks and key scheduling attacks. Finally, the performance analysis results indicate that the hardware implementation cost of GFSPX algorithm is relatively low, requiring only 1715 GE based on 0.13 micron logic process. In addition, the software implementation of this algorithm works well at an encryption rate of 12.31 Mb/s. [ABSTRACT FROM AUTHOR]

The deterioration of bridge networks poses a major threat to the availability and function of transportation systems and ultimately affects social development. Deep reinforcement learning is expected to provide intelligent decision support for bridge network maintenance. However, existing studies have neglected to explicitly consider the impact of maintenance behavior on the cost-effectiveness of bridge networks. The complex traffic environment and the interconnection of bridge networks also pose unique challenges in balancing maintenance costs and benefits. It is necessary to explore how to use the specific traffic data of each bridge in the bridge network to effectively balance cost-effectiveness and rationalize maintenance decisions. Aiming at the maintenance requirements of the bridge network, a multi-agent ranking proximal policy optimization framework is proposed. The performance of the proposed framework is rigorously evaluated using a real bridge network example. The results show that the maintenance policy based on the proposed framework can maximize the cost-effectiveness of the bridge network in its life cycle, effectively reduce the excessive risk cost and achieve a harmonious balance between different costs. In addition, the proposed framework is superior to the traditional maintenance policy and provides higher performance and efficiency. [ABSTRACT FROM AUTHOR]

Few-shot Semantic Segmentation (FSS) was proposed to segment unseen classes in a query image, referring to only a few annotated examples named support images. One of the characteristics of FSS is spatial inconsistency between query and support targets, e.g., texture or appearance. This greatly challenges the generalization ability of methods for FSS, which requires to effectively exploit the dependency of the query image and the support examples. Most existing methods abstracted support features into prototype vectors and implemented the interaction with query features using cosine similarity or feature concatenation. However, this simple interaction may not capture spatial details in query features. To address this limitation, some methods utilized pixel-level support information by computing pixel-level correlations between paired query and support features implemented with the attention mechanism of Transformer. Nevertheless, these approaches suffer from heavy computation due to dot-product attention between all pixels of support and query features. In this paper, we propose a novel framework, termed ProtoFormer, built upon the Transformer architecture, to fully capture spatial details in query features. ProtoFormer treats the abstracted prototype of the target class in support features as the Query and the query features as Key and Value embeddings, which are input to the Transformer decoder. This approach enables better capture of spatial details and focuses on the semantic features of the target class in the query image. The output of the Transformer-based module can be interpreted as semantic-aware dynamic kernels that filter the segmentation mask from the enriched query features. Extensive experiments conducted on PASCAL- 5 i and COCO- 20 i datasets demonstrate that ProtoFormer significantly outperforms the state-of-the-art methods in FSS. [ABSTRACT FROM AUTHOR]

Cognitive impairment is considered to be one of the important comorbidities of diabetes, but the underlying mechanisms are widely unknown. Aquaporin-4 (AQP4) is the most abundant water channel in the central nervous system, which plays a neuroprotective role in various neurological diseases by maintaining the function of glymphatic system and synaptic plasticity. However, whether AQP4 is involved in diabetes-related cognitive impairment remains unknown. β-dystroglycan (β-DG), a key molecule for anchoring AQP4 on the plasma membrane of astrocytes and avoiding its targeting to lysosomes for degradation, can be cleaved by matrix metalloproteinase-9 (MMP-9). β-DG deficiency can cause a decline in AQP4 via regulating its endocytosis. However, whether cleavage of β-DG can affect the expression of AQP4 remains unreported. In this study, we observed that diabetes mice displayed cognitive disorder accompanied by reduction of AQP4 in prefrontal cortex. And we found that bafilomycin A1, a widely used lysosome inhibitor, could reverse the downregulation of AQP4 in diabetes, further demonstrating that the reduction of AQP4 in diabetes is a result of more endocytosis-lysosome degradation. In further experiments, we found diabetes caused the excessive activation of MMP-9/β-DG which leaded to the loss of connection between AQP4 and β-DG, further inducing the endocytosis of AQP4. Moreover, inhibition of MMP-9/β-DG restored the endocytosis-lysosome degradation of AQP4 and partially alleviated cognitive dysfunction in diabetes. Our study sheds new light on the role of AQP4 in diabetes-associated cognitive disorder. And we provide a promising therapeutic target to reverse the endocytosis-lysosome degradation of AQP4 in diabetes, such as MMP-9/β-DG. [ABSTRACT FROM AUTHOR]

In recent years, the exploration of knowledge in large-scale human mobility has gained significant attention. In order to achieve a semantic understanding of human behavior and uncover patterns in large-scale human mobility, Named Entity Recognition (NER) is a crucial technology. The rapid advancements in IoT and CPS technologies have led to the collection of massive human mobility data from various sources. Therefore, there's a need for Cross-domain NER which can transfer entity information from the source domain to automatically identify and classify entities in different target domain texts. In the situation of the data-poor, how could we transfer human mobility knowledge over time and space is particularly significant, therefore this paper proposes an Adaptive Text Sequence Enhancement Module (at-SAM) to help the model enhance the association between entities in sentences in the data-poor target domains. This paper also proposes a Predicted Label-Guided Dual Sequence Aware Information Module (Dual-SAM) to improve the transferability of label information. Experiments were conducted in domains that contain hidden knowledge about human mobility, the results show that this method can transfer task knowledge between multiple different domains in the data-poor scenarios and achieve SOTA performance. [ABSTRACT FROM AUTHOR]

Objective: Intestinal mucositis is one of the common side effects of anti-cancer chemotherapy. However, the molecular mechanisms involved in mucositis development remain incompletely understood. In this study, we investigated the function of receptor-interacting protein kinase 3 (RIP3/RIPK3) in regulating doxorubicin-induced intestinal mucositis and its potential mechanisms. Methods: Intestinal mucositis animal models were induced in mice for in vivo studies. Rat intestinal cell line IEC-6 was used for in vitro studies. RNA‑seq was used to explore the transcriptomic changes in doxorubicin-induced intestinal mucositis. Intact glycopeptide characterization using mass spectrometry was applied to identify α-1,2-fucosylated proteins associated with mucositis. Results: Doxorubicin treatment increased RIP3 expression in the intestine and caused severe intestinal mucositis in the mice, depletion of RIP3 abolished doxorubicin-induced intestinal mucositis. RIP3-mediated doxorubicin-induced mucositis did not depend on mixed lineage kinase domain-like (MLKL) but on α-1,2-fucosyltransferase 2 (FUT2)-catalyzed α-1,2-fucosylation on inflammation-related proteins. Deficiency of MLKL did not affect intestinal mucositis, whereas inhibition of α-1,2-fucosylation by 2-deoxy-D-galactose (2dGal) profoundly attenuated doxorubicin-induced inflammation and mucositis. Conclusions: RIP3-FUT2 pathway is a central node in doxorubicin-induced intestinal mucositis. Targeting intestinal RIP3 and/or FUT2-mediated α-1,2-fucosylation may provide potential targets for preventing chemotherapy-induced intestinal mucositis. [ABSTRACT FROM AUTHOR]

A mild strategy was developed for efficient preparation of acetylsalicylic acid (ASA) from the acetylation of salicylic acid (SA) and acetic anhydride (AA) assisted ultrasonic over Y-immobilized cation exchange resin (Y-CER). With this strategy, an ASA yield of 95.2% was obtained. The results showed that the increased yield was due to Lewis acidic sites (LAS) combined with ultrasonic assistance. The process reduced the AA reagent feed while lowering the reaction temperature. The characterization results showed that metal Y species were dispersedly anchored on the CER surface through S-O-Y triple-dentate bonds, resulting in abundant LAS and stable catalytic activity. Comparative experiments revealed that LAS was more favorable for the formation of ASA than Bronsted acidic sites (BAS). Furthermore, a plausible mechanism for the acetylation of SA and AA by Y-CER has been proposed. This work provided a practical protocol for improving ASA yield and reducing acid wastewater discharge, with potential application prospects. [ABSTRACT FROM AUTHOR]

Futuristic technologies such as morphing aircrafts and super-strong artificial muscles depend on metal alloys being as strong as ultrahigh-strength steel yet as flexible as a polymer1–3. However, achieving such ‘strong yet flexible’ alloys has proven challenging4–9 because of the inevitable trade-off between strength and flexibility5,8,10. Here we report a Ti–50.8 at.% Ni strain glass alloy showing a combination of ultrahigh yield strength of σy ≈ 1.8 GPa and polymer-like ultralow elastic modulus of E ≈ 10.5 GPa, together with super-large rubber-like elastic strain of approximately 8%. As a result, it possesses a high flexibility figure of merit of σy/E ≈ 0.17 compared with existing structural materials. In addition, it can maintain such properties over a wide temperature range of −80 °C to +80 °C and demonstrates excellent fatigue resistance at high strain. The alloy was fabricated by a simple three-step thermomechanical treatment that is scalable to industrial lines, which leads not only to ultrahigh strength because of deformation strengthening, but also to ultralow modulus by the formation of a unique ‘dual-seed strain glass’ microstructure, composed of a strain glass matrix embedded with a small number of aligned R and B19′ martensite ‘seeds’. In situ X-ray diffractometry shows that the polymer-like deformation behaviour of the alloy originates from a nucleation-free reversible transition between strain glass and R and B19′ martensite during loading and unloading. This exotic alloy with the potential for mass producibility may open a new horizon for many futuristic technologies, such as morphing aerospace vehicles, superman-type artificial muscles and artificial organs.A polymer-like ultrahigh-strength TiNi alloy was fabricated by a simple three-step process to give a combination of a polymer-like ultralow elastic modulus and a steel-like ultrahigh yield strength over a wide temperature range, and such exotic properties arise from a unique strain glass state. [ABSTRACT FROM AUTHOR]

Although the pathogenesis of Alzheimer's disease (AD) is still unknown, the molecular pathological phenomena is clear, mainly due to mitochondrial dysfunction and central nervous system inflammation caused by imbalanced antioxidant capacity and synaptic dysfunction, so antioxidant therapy is still the preferred treatment for AD. However, although antioxidant enzymes have high catalytic efficiency, the substrate spectrum is narrow; Antioxidants have wider range of effects, but their efficiency is low. Since the antioxidant defense system in high-grade organisms is composed of both enzymatic and non-enzymatic systems, therefore we synthesized a metal-organic framework (MOF) with superoxide dismutase activity, and depending on the interface potential effect, curcumin was loaded to construct a synergistic antioxidant treatment system. More importantly, due to the complementary surface electrostatic potential between MOF and curcumin, the system exhibited both good antioxidant activity and efficient β-amyloid plaque scavenging ability, which slowed down the cognitive dysfunction in the brain of AD mice. Although the pathogenesis of Alzheimer's disease (AD) is still unknown, imbalanced antioxidant capacity in nerve cells is a successfully targeted pathological phenomenon in clinical practice. Here, the authors show that the complementary surface electrostatic potential between a metal-organic framework and curcumin results in a complex with good antioxidant activity and efficient β-amyloid plaque scavenging ability, which slows down the cognitive dysfunction in the brain of AD mice. [ABSTRACT FROM AUTHOR]

Selenium plays a crucial role as a micronutrient, primarily exerting its biological functions through selenoproteins. It has been established that selenium deficiency adversely impacts cartilage development, leading to alterations in chondrocyte function. In regions with low selenium intake, endemic osteochondrosis has been documented, characterized by compromised growth plate and articular cartilage formation. Vascular endothelial growth factor (VEGF) stands out as a pivotal angiogenic factor, with elevated levels contributing significantly to vascular invasion into chondrocytes. This VEGF-mediated invasion serves as a key signal, prompting morphological changes in the growth plate and initiating cartilage remodeling. In animal models, the selenium deficiency group exhibited heightened levels of the cartilage damage marker matrix metalloproteinases 13 (MMP13). This resulted in articular cartilage degeneration, accompanied by a substantial increase in VEGF expression within the growth plate and articular cartilage, as compared to the normal group. In a chondrogenic progenitor cell (CPC) differentiation model, insufficient selenium induced chondrocyte damage and upregulated inflammatory factors such as inducible NO synthase (iNOS) and cyclooxygenase-2 (COX2). The selenium-deficient groups showed elevated expressions of VEGF, VEGFR2, MMP13, Collagen X, and Angiopoietin 1, accelerating the degradation of the extracellular matrix (ECM), which further promoted the development of cartilage-related diseases. Taken together, these findings provide novel insights for a better understanding of the role of low selenium in cartilage degeneration and angiogenesis. They shed light on the intricate influence of low selenium levels on the development of articular cartilage, emphasizing the interconnected pathways and processes involved. [ABSTRACT FROM AUTHOR]

Background and aims: The differences in multi-elemental concentrations among plant species provide insightful information for understanding species coexistence in forest ecosystems, known as the biogeochemical niche separation. As most of the studies focused on leaf elemental concentrations, it is unclear whether belowground fine roots exhibit biogeochemical niche separation and whether there are close linkages of elemental concentrations among leaves, fine roots and rhizosphere soils. Methods: Nine element (N, P, K, Ca, Mg, Mn, Zn, Cu, and Fe) concentrations in leaves, fine roots and rhizosphere soils were measured for three tree species, three woody shrub species, and three herbaceous species in three subtropical plantations. Results: Elemental concentrations in leaves and fine roots were significantly different between woody and herbaceous species. Notably, the elemental concentrations differed more significantly for leaves than for fine roots, which indicated that leaves, as the most metabolically active tissues, tended to maintain their unique elemental concentrations within a particular functional type. Despite the different elemental needs between leaves and fine roots, most elemental concentrations of leaves were closely associated with those of the fine roots, highlighting the relationship between leaf and root ecological processes. Elemental concentrations in leaves or fine roots were not significantly correlated with those of the rhizospheres. Conclusions: There is evidence for biogeochemical niche separation between coexisting woody and herbaceous species to avoid competition. Our results generalized the biogeochemical niche hypothesis to belowground tissues, which offered new insights into a better understanding of species evolution and coexistence in ecosystems. [ABSTRACT FROM AUTHOR]

Natural antimicrobial peptides (AMPs) and enzymes (AMEs) are promising non-antibiotic candidates against antimicrobial resistance but suffer from low efficiency and poor stability. Here, we develop peptide nanozymes which mimic the mode of action of AMPs and AMEs through de novo design and peptide assembly. Through modelling a minimal building block of IHIHICI is proposed by combining critical amino acids in AMPs and AMEs and hydrophobic isoleucine to conduct assembly. Experimental validations reveal that IHIHICI assemble into helical β-sheet nanotubes with acetate modulation and perform phospholipase C-like and peroxidase-like activities with Ni coordination, demonstrating high thermostability and resistance to enzymatic degradation. The assembled nanotubes demonstrate cascade antifungal actions including outer mannan docking, wall disruption, lipid peroxidation and subsequent ferroptotic death, synergistically killing >90% Candida albicans within 10 min on disinfection pad. These findings demonstrate an effective de novo design strategy for developing materials with multi-antimicrobial mode of actions. Natural antimicrobial peptides and enzymes are good candidates for application but suffer from low stability. Here, the authors report on biomimetic self-assembling peptides which mimic both antimicrobial peptide and enzyme functionality, demonstrating application against fungal infection. [ABSTRACT FROM AUTHOR]

Background and aims: Biological invasions have tremendous effects on soil biodiversity. Although the effects of invasive plants on soil biota have been widely investigated, how soil fauna invasion affects native soil biodiversity in island ecosystems remains unclear. Methods: Field survey in non-invaded and invaded sites was conducted to investigate the effects of the giant African snail invasion on native soil biodiversity on tropical coral islands. Results: The effects of snail invasion on native soil biodiversity were strongly dependent on sampling seasons. Fungal biomass, microbial diversity, and nematode abundance (except omnivores/predators) increased by snail invasion in the dry season but decreased in the wet season. Mite abundance and diversity increased, whereas the activities of β-1,4-glucosidase, β-D-cellobiosidase, β-N-acetyl-glucosaminidase, and alkaline phosphatase decreased by snail invasion in both dry and wet seasons. Snail invasion homogenized the seasonal community composition of nematodes, the fungi: bacteria ratio (F: B ratio), and the Gram-positive: Gram-negative bacteria ratio (GP: GN ratio). These results together indicate that snail invasion does not have greater effects on soil biota at lower trophic levels but also has great effects on those at higher trophic levels. Soil moisture, soil organic carbon, available phosphorus, and potassium were important factors explaining the variation of soil biodiversity under snail invasion. Conclusion: These results together indicate that alien snail invasion weakens the seasonal variation of native soil biodiversity by altering soil resource availability. Such information is valuable for improving our understanding of the ecological consequences of alien organism invasion on soil biodiversity in tropical coral islands. [ABSTRACT FROM AUTHOR]

Gender differences exist in eating disorders. This study hypothesizes that anxiety, depression, self-esteem, and body image mediate the relationship between masculinity and eating disorders. 789 college students completed the Self-Rating Anxiety Scale (SAS), Body Image States Scale (BISS), Eating Disorder Scale (EDS-19), Self-Esteem Scale (SES), Revised Bem Sex Role Inventory, and Self-Rating Depression Scale (SDS). Descriptive statistical correlations, circular and multidimensional scaling (MDS) networks, and Bayesian network analysis were conducted. Also, network centrality and the stability of centrality indices were calculated. The correlations between anxiety, depression, self-esteem, body image, eating disorders, masculinity, and feminization are all statistically significant. Anxiety and depression mediate the relationship between masculinity and EDS. Self-esteem plays an intermediary role between masculinity and feminization. Masculinity directly affects eating disorders by inhibiting feminization. The results indicate that anxiety and depression mediate the relationship between masculinity and EDS, while self-esteem moderates the relationship between masculinity and feminization. This provides a new approach to understanding the mechanisms of eating disorders and offers a fresh perspective for clinical intervention from the viewpoint of gender roles, particularly masculinity. [ABSTRACT FROM AUTHOR]

Introduction and hypothesis: Urinary incontinence (UI) is a widespread issue in women that severely impacts quality of life. The addition of sugar is associated with multiple adverse effects on health. This study examined the potential association between added sugar intake and UI. Methods: Adult females from the National Health and Nutrition Examination Survey database (2005–2018) were included in this study. The primary outcomes were the prevalence of stress urinary incontinence (SUI), urge urinary incontinence (UUI), and mixed urinary incontinence (MUI). Weighted logistic regression, stratified logistic regression, restricted cubic spline regression, and sensitivity analyses were utilized to determine whether added sugar was associated with UI after multivariate adjustment. Results: A total of 14,927 participants met the inclusion criteria. The results revealed a heightened prevalence of SUI, UUI, and MUI in the fourth quartile of added sugar energy percentage (OR = 1.304, 95% confidence interval [CI] = 1.105–1.539; OR = 1.464, 95% CI = 1.248–1.717; OR = 1.657, 95% CI = 1.329–2.065 respectively). The effect was more pronounced in young women and the subgroup analyses did not reveal any noteworthy interaction effects. According to the sensitivity analyses, the results for SUI and the MUI were consistent with those of the primary analyses. Conclusions: The excessive intake of added sugar among women may increase their risk of SUI and MUI. Our study highlights the negative effects of added sugar on female genitourinary health and highlights the need for universal access to healthy diets. [ABSTRACT FROM AUTHOR]

The contamination of seafood by heavy metals is a rising health issue in the context of pollution caused by increasing industrialization and urbanization. Crustaceans are particularly susceptible to heavy metal pollution in aquatic ecosystems due to their benthic and sedimentary lifestyle. Here we review crustaceans contamination by heavy metals with a focus on metal sources and dynamics, interaction of metals with other pollutants, metal analysis, bioconcentration and bioaccumulation, toxicity, and strategies to control metals. We observed that crustaceans tend to accumulate more heavy metals than other aquatic animals. Consequently, in certain regions of the world, consuming crustaceans as food may potentially threaten human health. The bioavailability, transport, and interaction of heavy metals with other pollutants depend on various factors, potentially leading to differential toxicity. Heavy metals induce multiple toxic effects on crustaceans, including metabolic dysfunction, genotoxic effects, respiratory impairments, DNA damage, sperm mobility, and quantity, and these poisonous effects will intensify with prolonged exposure time and increasing concentration. The concentration of heavy metals in crustacean samples is usually determined by inductively coupled plasma optical emission spectrometry and mass spectrometry. Approaches to reducing this potential threat include proper industrial wastewater treatment and using low-cost adsorbent materials in aquaculture. [ABSTRACT FROM AUTHOR]

With the development of information technology and cloud computing, data sharing has become an important part of scientific research. In traditional data sharing, data is stored on a third-party storage platform, which causes the owner to lose control of the data. As a result, there are issues of intentional data leakage and tampering by third parties, and the private information contained in the data may lead to more significant issues. Furthermore, data is frequently maintained on multiple storage platforms, posing significant hurdles in terms of enlisting multiple parties to engage in data sharing while maintaining consistency. In this work, we propose a new architecture for applying blockchains to data sharing and achieve efficient and reliable data sharing among heterogeneous blockchains. We design a new data sharing transaction mechanism based on the system architecture to protect the security of the raw data and the processing process. We also design and implement a hybrid concurrency control protocol to overcome issues caused by the large differences in blockchain performance in our system and to improve the success rate of data sharing transactions. We took Ethereum and Hyperledger Fabric as examples to conduct cross-blockchain data sharing experiments. The results show that our system achieves data sharing across heterogeneous blockchains with reasonable performance and has high scalability. [ABSTRACT FROM AUTHOR]

Purpose: Glucose not only provides energy for tumor cells, but also provides various biomolecules that are essential for their survival, proliferation and invasion. Therefore, it is of great clinical significance to understand the mechanism of how tumor cells adapt to metabolic stress and maintain their survival. The aim of this research was to study the critical role of OGT and TRIM29 O-GlcNAc modification driven adaptability of PDAC cells to low glucose stress, which might have important medical implications for PDAC therapy. Methods: Western blotting, mass spectrometry and WGA-immunoprecipitation were used to examined the levels of OGT and O-GlcNAc glycosylated proteins in BxPC3 and SW1990 cells in normal culture and under glucose deprivation conditions. Crystal violet assay, flow cytometry, RIP, RT-qPCR, protein stability assay, biotin pull down were used to investigate the mechanism of OGT and TRIM29-mediated adaptive response to glucose deficiency in PDAC cells. Results: The current study found that under the condition of low glucose culture, the levels of OGT and O-GlcNAc glycosylation in PDAC cells were significantly higher than those in normal culture. Moreover, the high expression of OGT has a protective effect on PDAC cells under low glucose stress. This study confirmed that there was no significant change in mRNA level and protein degradation of OGT under low glucose stress, which was mainly reflected in the increase of protein synthesis. In addition, O-GlcNAc modification at T120 site plays a critical role in the metabolic adaptive responses mediated by TRIM29. Conclusions: Taken together, our study indicated that O-GlcNAcylation of TRIM29 at T120 site and OGT translation forms a loop feedback to facilitate survival of PDAC under glucose deficiency. [ABSTRACT FROM AUTHOR]

The discovery of upstream regulatory genes of a gene of interest still remains challenging. Here we applied a scalable computational method to unbiasedly predict candidate regulatory genes of critical transcription factors by searching the whole genome. We illustrated our approach with a case study on the master regulator FOXP3 of human primary regulatory T cells (Tregs). While target genes of FOXP3 have been identified, its upstream regulatory machinery still remains elusive. Our methodology selected five top-ranked candidates that were tested via proof-of-concept experiments. Following knockdown, three out of five candidates showed significant effects on the mRNA expression of FOXP3 across multiple donors. This provides insights into the regulatory mechanisms modulating FOXP3 transcriptional expression in Tregs. Overall, at the genome level this represents a high level of accuracy in predicting upstream regulatory genes of key genes of interest. [ABSTRACT FROM AUTHOR]

Atrazine is an important herbicide that has been widely used for weed control in recent decades. However, with the extensive use of atrazine, its residue seriously pollutes the environment. Therefore, the microbial degradation and detoxification of atrazine have received extensive attention. To date, the aerobic degradation pathway of atrazine has been well studied; however, little is known about its anaerobic degradation in the environment. In this study, an anaerobic microbial consortium capable of efficiently degrading atrazine was enriched from soil collected from an herbicide-manufacturing plant. Six metabolites including hydroxyatrazine, deethylatrazine, N-isopropylammelide, deisopropylatrazine, cyanuric acid, and the novel metabolite 4-ethylamino-6-isopropylamino-1,3,5-triazine (EIPAT) were identified, and two putative anaerobic degradation pathways of atrazine were proposed: a hydrolytic dechlorination pathway is similar to that seen in aerobic degradation, and a novel pathway initiated by reductive dechlorination. During enrichment, Denitratisoma, Thiobacillus, Rhodocyclaceae_unclassified, Azospirillum, and Anaerolinea abundances significantly increased, dominating the enriched consortium, indicating that they may be involved in atrazine degradation. These findings provide valuable evidence for elucidating the anaerobic catabolism of atrazine and facilitating anaerobic remediation of residual atrazine pollution. [ABSTRACT FROM AUTHOR]

This study assesses the health benefits of better air quality by examining the causal impact of China's stringent " 2 + 26 " regional air pollution control policy on local air quality and population health. Employing a spatial regression discontinuity design that capitalizes on the policy's location-specific features, we present compelling evidence that the 2 + 26 policy results in an average reduction of 12.2 units in the local Air Quality Index (AQI) and a 47.0% decrease in per capita medical expenditure from 2014 to 2018. A one-unit reduction in AQI corresponds to a 0.88% reduction in per capita annual medical spending, equivalent to RMB 30.2 (US$4.6). These health gains stem from reduced chronic disease prevalence and improved subjective well-being. Nationally, air quality improvement during 2014–2018 could save RMB 674 billion (US$104 billion) annually in national direct medical costs, constituting 11.6% of national medical expenditure in 2018. Our findings underscore the substantial health and welfare gains achievable through pollution controls in developing countries. [ABSTRACT FROM AUTHOR]

Small interfering RNA (siRNA) is often used for function study and expression regulation of specific genes, as well as the development of small molecule drugs. Selecting siRNAs with high inhibition and low off-target effects from massive candidates is always a great challenge. Increasing experimentally-validated samples can prompt the development of machine-learning-based algorithms, including Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Graph Neural Network (GNN). However, these methods still suffer from limited accuracy and poor generalization in designing potent and specific siRNAs. In this study, we propose a novel approach for siRNA inhibition and off-target effect prediction, named AttSiOff. It combines a self-attention-based siRNA inhibition predictor with an mRNA searching package and an off-target filter. The predictor gives the inhibition score via analyzing the embedding of siRNA and local mRNA sequences, generated from the pre-trained RNA-FM model, as well as other meaningful prior-knowledge-based features. Self-attention mechanism can detect potentially decisive features, which may determine the inhibition of siRNA. It captures global and local dependencies more efficiently than normal convolutions. The tenfold cross-validation results indicate that our model outperforms all existing methods, achieving PCC of 0.81, SPCC of 0.84, and AUC of 0.886. It also reaches better performance of generalization and robustness on cross-dataset validation. In addition, the mRNA searching package could find all mature mRNAs for a given gene name from the GENOMES database, and the off-target filter can calculate the amount of unwanted off-target binding sites, which affects the specificity of siRNA. Experiments on five mature siRNA drugs, as well as a new target gene (AGT), show that AttSioff has excellent convenience and operability in practical applications. Highlights: · We utilize a pre-trained model to enrich the information of sequence embedding, and self-attention mechanism to capture global dependencies. · Our inhibition predictor achieves the best performance on both accuracy and generalization. · We construct a simple and user-friendly approach to design both potent and specific siRNAs. [ABSTRACT FROM AUTHOR]

Lysine lactylation (Kla) links metabolism and gene regulation and plays a key role in multiple biological processes. However, the regulatory mechanism and functional consequence of Kla remain to be explored. Here, we report that HBO1 functions as a lysine lactyltransferase to regulate transcription. We show that HBO1 catalyzes the addition of Kla in vitro and intracellularly, and E508 is a key site for the lactyltransferase activity of HBO1. Quantitative proteomic analysis further reveals 95 endogenous Kla sites targeted by HBO1, with the majority located on histones. Using site-specific antibodies, we find that HBO1 may preferentially catalyze histone H3K9la and scaffold proteins including JADE1 and BRPF2 can promote the enzymatic activity for histone Kla. Notably, CUT&Tag assays demonstrate that HBO1 is required for histone H3K9la on transcription start sites (TSSs). Besides, the regulated Kla can promote key signaling pathways and tumorigenesis, which is further supported by evaluating the malignant behaviors of HBO1- knockout (KO) tumor cells, as well as the level of histone H3K9la in clinical tissues. Our study reveals HBO1 serves as a lactyltransferase to mediate a histone Kla-dependent gene transcription. The regulatory mechanism and functional consequence of lysine lactylation remain to be explored. Here, the authors identify HBO1 as a lysine lactyltransferase and suggest a potential role of HBO1 in tumorigenesis through H3K9la-mediated transcription regulation. [ABSTRACT FROM AUTHOR]

Insects have a pivotal role in ecosystem function, thus the decline of more than 75% in insect biomass in protected areas over recent decades in Central Europe1 and elsewhere2,3 has alarmed the public, pushed decision-makers4 and stimulated research on insect population trends. However, the drivers of this decline are still not well understood. Here, we reanalysed 27 years of insect biomass data from Hallmann et al.1, using sample-specific information on weather conditions during sampling and weather anomalies during the insect life cycle. This model explained variation in temporal decline in insect biomass, including an observed increase in biomass in recent years, solely on the basis of these weather variables. Our finding that terrestrial insect biomass is largely driven by complex weather conditions challenges previous assumptions that climate change is more critical in the tropics5,6 or that negative consequences in the temperate zone might only occur in the future7. Despite the recent observed increase in biomass, new combinations of unfavourable multi-annual weather conditions might be expected to further threaten insect populations under continuing climate change. Our findings also highlight the need for more climate change research on physiological mechanisms affected by annual weather conditions and anomalies.Insect biomass data covering 27 years were reanalysed using sample-specific information on weather conditions during sampling and weather anomalies during the insect life cycle, finding that biomass is driven by complex weather conditions. [ABSTRACT FROM AUTHOR]

Background: Trousseau syndrome (TS) is relatively rare and easily overlooked by clinicians, causing misdiagnosis and affecting subsequent treatment. Objective: In this study, clinical features, laboratory examination, imaging features, treatment, and prognosis of patients with TS were discussed. Methods and material: From February 2018 to April 2022, cases of 21 patients with malignant tumors complicated by acute ischemic stroke (AIS) were admitted to the Neurology Department of the hospital, and were retrospectively analyzed and discussed based on the literature. Results: Twenty-one cases were included in the study. Of these, 95.23% (20/21) developed AIS 6–21 months after the onset of malignant tumors, 9.52% (2/21) had ischemic stroke as the first symptom, 4.76% (1/21) had recurrent ischemic stroke, and 14.29% (3/21) subsequently experienced venous and arterial thrombosis events; 80.95% (17/21) were pathologically confirmed to have adenocarcinoma; and 90.47% (19/21) of infarction cases involved multiple blood vessel feeding sites. MRI showed multiregional, multifocal patchy infarcts. d-dimer concentration was higher than normal in all patients. In addition, 61.90% (13/21) of the patients had poor outcomes according to mRS. Conclusion: TS is a rare clinical type. It is often associated with adenocarcinoma, and the treatment is different from that of conventional cerebral infarction and the prognosis is very poor. In clinical practice, for AIS of unknown cause, if MRI shows multiple small lesions accompanied by a significant increase in d-dimer, routine screening for latent malignant tumors is recommended. [ABSTRACT FROM AUTHOR]

Key message: Taxadiene synthase, taxadiene-5α-hydroxylase, and taxane 13α-hydroxylase genes were introduced into Nicotiana benthamiana, and the improved resistance to lepidoptera pest fall armyworm was reported. Fall armyworm (FAW) is a serious agricultural pest. Genetic engineering techniques have been used to create pest-resistant plant varieties for reducing pest damage. Paclitaxel is a diterpenoid natural metabolite with antineoplastic effects in medicine. However, the effects of taxanes on the growth and development of lepidoptera pests, such as the FAW, are unknown. Here, selected paclitaxel precursor biosynthesis pathway genes, taxadiene synthase, taxane 5α-hydroxylase, and taxane 13α-hydroxylase, were engineered in the heterologous host Nicotiana benthamiana plants. Bioassay experiments showed that the transgenic N. benthamiana plants displayed improved resistance to FAW infestation, with degeneration of gut tissues and induced expression of apoptosis-related genes. Cytotoxicity experiment showed that the paclitaxel precursor, 10-deacetylbaccatin III, is cytotoxic to Sf9 cells, causing cell cycle arrest at the G2/M phase and disorder of the cytoskeleton. Metabolome analysis showed that heterologous expression of taxane genes in N. benthamiana affected the digestive system, steroid hormone and purine metabolism pathways of FAW larvae. In summary, this study provides a candidate approach for FAW control. [ABSTRACT FROM AUTHOR]

The huge amount of graph data necessitates sampling methods to support graph-based analysis applications. Node influence is to count the influential nodes with a given node in large graphs that has wide applications including product promotion and information diffusion in social networks. However, existing sampling methods mainly consider node degree to compute the node influence while ignoring the important connections in terms of groups in which nodes participate, resulting in inaccuracy of influence estimations. To this end, this paper proposes group sampling, called GVRW, to count the groups along with node degrees to evaluate node influence in large graphs. Specifically, GVRW changes the way of random walker traversing a large graph from one node to a random neighbor node of the groups to enlarge the sampling space for the sake of characterizing the nodes and groups simultaneously. Furthermore, we carefully design the corresponding estimated method to employ the samples to estimate the specific distributions of groups and node degrees to compute the node influence. Experimental results on real-world graph datasets show that our proposed sampling and estimating methods can accurately obtain the properties and approximate the node influences closer to the real values than existing methods. [ABSTRACT FROM AUTHOR]

RNA velocity is closely related with cell fate and is an important indicator for the prediction of cell states with elegant physical explanation derived from single-cell RNA-seq data. Most existing RNA velocity models aim to extract dynamics from the phase delay between unspliced and spliced mRNA for each individual gene. However, unspliced/spliced mRNA abundance may not provide sufficient signal for dynamic modeling, leading to poor fit in phase portraits. Motivated by the idea that RNA velocity could be driven by the transcriptional regulation, we propose TFvelo, which expands RNA velocity concept to various single-cell datasets without relying on splicing information, by introducing gene regulatory information. Our experiments on synthetic data and multiple scRNA-Seq datasets show that TFvelo can accurately fit genes dynamics on phase portraits, and effectively infer cell pseudo-time and trajectory from RNA abundance data. TFvelo opens a robust and accurate avenue for modeling RNA velocity for single cell data. Most RNA velocity models extract dynamics from the phase delay between unspliced and spliced mRNA for each gene. Here, authors propose TFvelo, broadening RNA velocity beyond splicing information to include gene regulation. TFvelo accurately models genes dynamics and infers cell pseudo-time from RNA abundance data. [ABSTRACT FROM AUTHOR]

Compared with dissipative chaotic systems, conservative chaotic systems are more suitable for secure communication based on chaos. In this paper, an effective method for constructing a class of four-dimensional conservative chaotic systems is proposed by coupling four generalized Euler equations with four coupling parameters. Moreover, this method is also applicable to the construction of higher-dimensional Hamiltonian conservative systems. The chaotic and conservative properties of the system are verified in detail by relevant analytical methods, including equilibrium points, phase diagram, Lyapunov exponents, bifurcation diagram, energy, and transient quasi-periodic orbit. An interesting transient quasi-period phenomenon is observed in the new system. In addition, the Hamiltonian energy level affects the coexistence behavior of the new system. The coexistence phenomenon was analyzed from an energy perspective. With the increase in Hamiltonian energy level, the ergodicity and randomness increase. Besides, the system also has abundant coexistence orbitals at equal energy levels. Finally, the National Institute of Standards and Technology test verifies that the pseudo-random sequence based on the new system has good pseudo-randomness, and the hardware circuit of the system is realized by field programmable gate array, and the physical feasibility of the system is verified. This study demonstrates that the constructed class of Hamiltonian conservative chaotic systems is a good entropy source that can be applied to various chaotic embedded systems, including secure communication systems, cryptographic systems, and random number generators. [ABSTRACT FROM AUTHOR]

Fashion Item Captioning aims to describe fine-grained item details according to several image angles, which is an advancement of the conventional image captioning task(generating a simple sentence for a single image). Most recent researches are dedicated to describe one image, and less attention is paid to capturing item details from different angles. As a result, they commonly take advantage of formula structure in the general domain rather than taking into account the characteristics of product images in the fashion domain. In this paper, we re-define the fashion captioning task to be Fashion Item Captioning, which is aimed to describe the item angles based on a multi-branch design. Based on this thinking, fashion item captioning still face two challenges. First, existing image captioning methods simply consider the grid features as a set of visual tokens while ignoring the positional relationships among them. And these rich relationships are difficult to be established by such coarse-grained visual representations. To this end, we propose a Grid-relation Self-Attention(GSA), in which three positional relations among grid-level features are captured to strengthen the visual representations from multi perspectives. Second, the attributes of products are usually scattered in images from different angles, which means different angles contribute differently to the sentence caption. Thus, a Gated-Enhanced Decoder(GED) is introduced to dynamically measure the contribution of different views to the target word. Finally, we apply GSA and GED to the vanilla transformer model for the fashion item captioning task. Extensive experiments demonstrate the proposed GSA-GED is effective. More remarkably, GSA-GED achieves competitive performance on Fashion-Gen and FACAD datasets, with the CIDEr-D score being increased from 106.7% to 112.1%, 47.1% to 49.3%, respectively. [ABSTRACT FROM AUTHOR]

Recent research has revealed that single object tracking (SOT) is susceptible to adversarial examples, with even small perturbations added to video frames leading to tracking failure. However, most of the existing methods are online attack methods. These methods generate video-specific or target-specific perturbation to deceive the trackers through a frame-by-frame online paradigm. This method is inherently inefficient in the production of adversarial examples, rendering it less than ideal for real-time application scenarios. To address this, we propose a novel offline attack method that can achieve high-frequency attack strength by using only one frame of video, called box-spoof attack (BS-Attack). In contrast to prior methods perturb feature maps or confidence maps in a frame-by-frame manner. Our BS-Attack directs its focus towards the proposal selection stage, a relatively late stage within the tracking pipeline. Notably, our method generates perturbations by utilizing the information from the initial frame, which can achieve rapid disturbance generation and high-frequency attack strength. In addition to confidence loss, we incorporate joint intersection-over-union and shrink loss to keep the predicted bounding box away from the ground truth and shrink it. BS-Attack requires only one video to generate a perturbation that can deceive the entire dataset. The UAV123, OTB100, VOT2018, and VOT2019 datasets are used to demonstrate the effectiveness of this method in attacking popular trackers such as SiamRPN, SiamRPN++, and SiamMask. The results show that BS-Attack outperforms state-of-the-art online and offline attack methods. [ABSTRACT FROM AUTHOR]

Background: Concerns about the adverse effects of excessive oxygen have grown over the years. This study investigated the relationship between high oxygen saturation and short-term prognosis of patients with spontaneous intracerebral hemorrhage (sICH) after liberal use of oxygen. Methods: This retrospective cohort study collected data from the Medical Information Mart for Intensive Care III (MIMIC-III) database (ICU cohort) and a tertiary stroke center (general ward cohort). The data on pulse oximetry-derived oxygen saturation (SpO2) during the first 24 h in ICU and general wards were respectively extracted. Results: Overall, 1117 and 372 patients were included in the ICU and general ward cohort, respectively. Among the patients from the ICU cohort, a spoon-shaped association was observed between minimum SpO2 and the risk of in-hospital mortality (non-linear P<0.0001). In comparison with minimum SpO2 of 93–97%, the minimum SpO2>97% was associated with a significantly higher risk of in-hospital mortality after adjustment for confounders. Sensitivity analysis conducted using propensity score matching did not change this significance. The same spoon-shaped association between minimum SpO2 and the risk of in-hospital mortality was also detected for the general ward cohort. In comparison with the group with 95–97% SpO2, the group with SpO2>97% showed a stronger association with, but non-significant risk for, in-hospital mortality after adjustment for confounders. The time-weighted average SpO2>97% was associated significantly with in-hospital mortality in both cohorts. Conclusion: Higher SpO2 (especially a minimum SpO2>97%) was unrewarding after liberal use of oxygen among patients with sICH and might even be potentially detrimental. [ABSTRACT FROM AUTHOR]

In modern science and engineering disciplines, data-driven discovery methods play a fundamental role in system modeling, as data serve as the external representations of the intrinsic mechanisms within systems. However, empirical data contaminated by process and measurement noise remain a significant obstacle for this type of modeling. In this study, we have developed a data-driven method capable of directly uncovering linear dynamical systems from noisy data. This method combines the Kalman smoothing and sparse Bayesian learning to decouple process and measurement noise under the expectation-maximization framework, presenting an analytical method for alternate state estimation and system identification. Furthermore, the discovered model explicitly characterizes the probability distribution of process and measurement noise, as they are essential for filtering, smoothing, and stochastic control. We have successfully applied the proposed algorithm to several simulation systems. Experimental results demonstrate its potential to enable linear dynamical system discovery in practical applications where noise-free data are intractable to capture. [ABSTRACT FROM AUTHOR]

Fashion captioning aims to generate detailed and captivating descriptions based on a group of item images. It requires the model to precisely describe attribute details under the supervision of complex sentences. Existing image captioning methods typically focus on describing a single image and often struggle to capture fine-grained visual representations in the fashion domain. Furthermore, the presence of complex description noise and unbalanced word distribution in fashion datasets limits diverse sentence generation. To alleviate redundancy in raw images, we propose an Attribute-based Alignment Module (AAM). The AAM captures more content-related information to enhance visual representations. Based on this design, we demonstrate that fashion captioning can benefit greatly from grid features with detailed alignment, in contrast to previous success with dense features. To address the inherent word distribution imbalance, we introduce a more balanced corpus called Fashion-Style-27k, collected from various shopping websites. Additionally, we present a pre-trained Fashion Language Model (FLM) that integrates sentence-level and attribute-level language knowledge into the caption model. Experiments on the FACAD and Fashion-Gen datasets show the proposed AAM-FLM outperforms existing methods. Descriptions in the two datasets are from considerably different lengths and styles, ranging from the 21-word detailed description to the 30-word template-based sentence, demonstrating the generalization ability of the proposed model. [ABSTRACT FROM AUTHOR]

Black soldier fly larvae (BSFL) bioconversion system is emerging as an effective approach for organic waste pollution treatment. Co-digestion of different organic matters with BSFL can be an effective way to realize the innovative biowaste circular economy. In this study, organic waste mixture of chicken manure and sewage sludge was chosen as substrate for BSFL growth. The bacterial biodiversity and nutrients quality of BSFL residue were evaluated through gene sequencing and other characterizations to confirm their application potential as biofertilizers. The dominant bacteria in BSFL residue were Firmicutes (75.39%) at phylum level, Bacilli (71.61%) at class level and Pseudogracilibacillus (11.08%) at genus level. Antibiotic resistance genes (ARGs) were used to assess the harmlessness of BSFL residue. After BSFL treatment, 36.2% decrease in ARGs was observed. Taking nutrients quality into consideration, dissolved organic carbon, dissolved nitrogen, available phosphorous, and available potassium significantly increased in the co-digestion system. These results demonstrated that co-digestion of chicken manure and excess sludge in BSFL bioconversion system could improve the nutrients quality of residues. However, removal of ARGs in the bioconversion process should be further explored to eliminate environmental concerns associated with application of BSFL residue as biofertilizers. [ABSTRACT FROM AUTHOR]

Existing drug-target interaction (DTI) prediction methods generally fail to generalize well to novel (unseen) proteins and drugs. In this study, we propose a protein-specific meta-learning framework ZeroBind with subgraph matching for predicting protein-drug interactions from their structures. During the meta-training process, ZeroBind formulates training a protein-specific model, which is also considered a learning task, and each task uses graph neural networks (GNNs) to learn the protein graph embedding and the molecular graph embedding. Inspired by the fact that molecules bind to a binding pocket in proteins instead of the whole protein, ZeroBind introduces a weakly supervised subgraph information bottleneck (SIB) module to recognize the maximally informative and compressive subgraphs in protein graphs as potential binding pockets. In addition, ZeroBind trains the models of individual proteins as multiple tasks, whose importance is automatically learned with a task adaptive self-attention module to make final predictions. The results show that ZeroBind achieves superior performance on DTI prediction over existing methods, especially for those unseen proteins and drugs, and performs well after fine-tuning for those proteins or drugs with a few known binding partners. Existing drug-target interaction (DTI) prediction methods generally fail to generalize well unseen proteins and drugs. Here the authors report a protein-specific meta-learning framework, ZeroBind, with subgraph matching for predicting protein-drug interactions from their structures. [ABSTRACT FROM AUTHOR]

The introduction of deterring agents in the surface layer of nitrocellulose-based gun propellant and the addition of ablation inhibitors inside can effectively improve the combustion progressivity and extend the service life of the barrel weapon. However, deterring agents are inert with negative oxygen balance and ablation inhibitors are difficult to decompose, often resulting in ignition difficulty and aggravating the emission harmful phenomenon, reducing the battlefield survivability of weapon. In this paper, a synergistic strategy of nitrocellulose denitration and nano-ZnO loading is proposed for the first time, in which ZnO with excellent thermal conductivity is loaded on the surface of denitrated nitrocellulose to enhance thermal conductivity while improving ablation inhibition property and reducing the amount of ablation agents. Various structural characterizations confirmed the successful preparation of denitrated nitrocellulose-ZnO (DNC@ZnO) composite with structural integrity and controllable nano-ZnO loading concentration. The results of TG, DSC and TG-FTIR showed that the appropriate amount of loaded ZnO barely affected the thermal decomposition process and thermal stability of nitrocellulose. Subsequent studies confirmed the high thermal conductivity and ablation inhibition property of DNC@ZnO composite, and mechanisms for these properties were proposed. This work is of great importance for the design of gun propellant with both combustion progressivity, easy ignition, low ablation, and less emission harmful phenomena. [ABSTRACT FROM AUTHOR]

Objective: GTP cyclohydrolase 1(GCH1) was reported to protect against ferroptosis. However, it is not clear whether GCH1 reduced lipopolysaccharide (LPS)-induced macrophage polarization and inflammation by inhibition of ferroptosis. Methods: Bioinformatics analysis was used to screen differential expression genes (DEGs) and obtain the different pathways and biological features. Lasso cox regression analysis with ferroptosis related DEGs was established to screen the most relevant genes for disease risk. LPS induced Raw264.7 macrophage polarization model and GCH1-specific siRNA oligos transfection were performed to confirm the function of GCH1. Immunofluorescence staining, western blot and quantitative real-time PCR were performed to detect the expression of iNOS, CD206, GCH1, IL6, SLC2A6, F4/80, IL1β, TNFα, IL10, GPX4, ACSL4, AMPK and p-AMPK in macrophages. The levels of ROS, SOD, MDA and GSH were detected according to the instructions of the reagent kit, respectively. Results: 542 DEGs were screened from GSE40885 microarray. GO and KEGG pathway enrichment analysis showed that the upregulated DEGs induced by LPS in alveolar macrophage were closely associated with inflammatory and immune responses, the downregulated DEGs were related to lipid metabolism, insulin resistance and AMPK signal pathway. Lasso cox regression analysis screened GCH1, IL6, and SLC2A6. Our experimental results showed that the expression of GCH1 and IL6 in the LPS group was higher than that in the control group, but there was no difference in the expression of SLC2A6. Bioinformatics analysis with GSE112720 observed that ferroptosis was enriched in GCHfl/fl + LPS group compared with GCHfl/flTie2cre + LPS group and GCHfl/fl + control group. Silence of GCH1 increased the levels of IL6, TNF-α and IL-1β and decreased IL10 level. Silence of GCH1 increased iNOS level and decreased CD206 level. Moreover, silence of GCH1 raised ferroptosis induced by LPS in macrophages and suppressed the activity of AMPK pathway. Conclusions: GCH1 inhibited ferroptosis in LPS-stimulated macrophages, reduced macrophage toward to M1 polarization and inflammatory response. [ABSTRACT FROM AUTHOR]

The genomic instability (GI) /homologous recombination deficiency (HRD) score, calculated as the sum of the events of loss of heterozygosity (LOH), large-scale state transition (LST) and telomere allele imbalance (TAI), is used to guide the choice of treatment in several cancers, but its relationship with genomic features, clinicopathological characteristics and prognosis in lung cancer is poorly understood, which could lead to population bias in prospective studies. We retrospectively analyzed 1011 lung cancer patients whose tumor samples were successfully profiled by high-throughput sequencing panel including GI/HRD score. Alterations of many cancer suppressor genes were associated with higher GI/HRD scores, biallelic inactivation of TP53 was correlated with a high GI/HRD score. A combination of two gene alterations exhibited a higher GI/HRD scores than single gene alterations. The GI/HRD score was associated with advanced stages in lung adenocarcinoma but not in lung squamous cell carcinoma. Furthermore, patients with higher GI/HRD scores had significantly shorter overall survival and progression-free survival than patients with lower GI/HRD scores. Finally, patients with a combination of a higher GI/HRD scores and TP53 alteration exhibited an extremely poor prognosis compared with patients with a lower GI/HRD scores and wild-type TP53 (overall survival, training cohort, hazard ratio (HR) = 8.56, P < 0.001; validation cohort, HR = 6.47, P < 0.001; progression-free survival, HR = 4.76, P < 0.001). Our study revealed the prognostic value of the GI/HRD score in lung adenocarcinoma, but not for all lung cancer. Moreover, the combination of the GI/HRD score and TP53 status could be a promising strategy to predict the prognosis of patients with lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Highly effective and selective noble metal-free catalysts attract significant attention. Here, a single-atom iron catalyst is fabricated by saturated adsorption of trace iron onto zeolitic imidazolate framework-8 (ZIF-8) followed by pyrolysis. Its performance toward catalytic transfer hydrogenation of furfural is comparable to state-of-the-art catalysts and up to four orders higher than other Fe catalysts. Isotopic labeling experiments demonstrate an intermolecular hydride transfer mechanism. First principles simulations, spectroscopic calculations and experiments, and kinetic correlations reveal that the synthesis creates pyrrolic Fe(II)-plN3 as the active center whose flexibility manifested by being pulled out of the plane, enabled by defects, is crucial for collocating the reagents and allowing the chemistry to proceed. The catalyst catalyzes chemoselectively several substrates and possesses a unique trait whereby the chemistry is hindered for more acidic substrates than the hydrogen donors. This work paves the way toward noble-metal free single-atom catalysts for important chemical reactions. Highly effective and selective noble metal-free catalysts continue to attract significant attention but require reaction specific tuning. Here, the authors fabricate a single-atom iron catalyst at low loading, which shows excellent transfer hydrogenation performance even at low reaction temperatures. [ABSTRACT FROM AUTHOR]

Matrine is a Sophora alkaloid that exerts antitumor effects on a variety of diseases, but few studies have investigated the role of matrine in sepsis-induced myocardial injury. In the present study, we investigated the effects of matrine on septic myocardial injury and the potential mechanisms. Network pharmacology approaches were used to predict the targets of matrine in the treatment of sepsis-induced myocardial injury. A mouse sepsis-induced myocardial injury model was established to determine the effect of matrine. Mouse cardiac function was evaluated by ultrasonography, and cardiac morphology and cardiomyocyte apoptosis were evaluated by HE and TUNEL staining. Oxidative stress was assessed by measuring ROS levels and MDA and SOD activity. Bax, Bcl2, GPX4, ACSL4, PI3K, and AKT protein levels were evaluated by immunohistochemical staining and western blotting. Bioinformatics analysis identified that the potential therapeutic effect of matrine on sepsis-induced myocardial injury is closely related to ferroptosis and apoptosis regulation and showed significant involvement of the PI3K/AKT signaling pathway. In vivo, the matrine group showed improved myocardial function, morphology, and apoptosis ratio and alleviated oxidative stress compared with the LPS group, whereas 25 mg/kg matrine exerted the optimal inhibitory effect. Matrine alleviated LPS-induced cardiomyocyte ferroptosis and apoptosis, resulting in upregulation of Bax/Bcl2 and GPX4 expression and downregulation of ferroptosis marker protein (ACSL4) expression, as shown by immunohistochemistry and western blotting. Moreover, matrine increased PI3K/AKT pathway-related molecule expression and thus modulated ferroptosis and apoptosis. Matrine regulates PI3K/AKT pathway activity to inhibit apoptosis and ferroptosis and thereby alleviates sepsis-induced myocardial injury. [ABSTRACT FROM AUTHOR]

This review summarizes and examines research in the area of salpingitis animal modeling in the last 40 years, focusing primarily on Chlamydia trachomatis animal models, which are the most numerous in the literature. Early animal models are examined, followed by a discussion of study parameters and their impact on modeling success, subsequent considerations of fertility measures in modeling, explorations of treatment options, and finally exploring recent directions with a brief discussion of models using other bacterial pathogens. [ABSTRACT FROM AUTHOR]