Precise Control of Metal Active Sites of Metal-Organic Framework Nanozymes for Achieving Excellent Enzyme-Like Activity and Efficient Pancreatitis Therapy.

Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease that can lead to the development of systemic inflammatory response syndrome and its progression to severe acute pancreatitis. Hence, there is an urgent need for the rational design of highly efficient antioxidants to treat AP. Herein, an optimized Cu-based metal-organic framework (MOF) nanozyme with exceptional antioxidant activity is introduced, designed to effectively alleviate AP, by engineering the metal coordination centers in MN2Cl2 (M = Co, Ni, Cu). Specifically, the Cu MOF, which benefits from a Cu active center similar to that of natural superoxide dismutase (SOD), exhibited at least four times higher SOD-like activity than the Ni/Co MOF. Theoretical analyses further demonstrate that the CuN2Cl2 site not only has a moderate adsorption effect on the substrate molecule •OOH but also reduces the dissociation energy of the product H2O2. Additionally, the Cu MOF nanozyme possesses the excellent catalase-like activity and •OH removal ability. Consequently, the Cu MOF with broad-spectrum antioxidant activity can efficiently scavenge reactive oxygen species to alleviate arginine-induced AP. More importantly, it can also mitigate apoptosis and necrosis of acinar cells by activating the PINK1/PARK2-mediated mitophagy pathway. This study highlights the distinctive functions of tunable MOF nanozymes and their potential bio-applications.

ATP citrate lyase promotes the progression of hepatocellular carcinoma by activating the REGγ-proteasome pathway.

The search for novel tumor biomarkers and targets is of significant importance for the early clinical diagnosis and treatment of Hepatocellular Carcinoma (HCC). The mechanisms by which ATP citrate lyase (ACLY) promotes HCC progression remain unclear, and the connection between ACLY and REGγ has not been reported in the literature. In vitro, we will perform overexpression/knockdown of ACLY or overexpression/knockdown of REGγ to investigate the impact of ACLY on HCC cells and its underlying mechanisms. In vivo, we will establish mouse tumor models with overexpression/knockdown of ACLY or overexpression/knockdown of REGγ to study the effect of ACLY on mouse tumors and its mechanisms. Firstly, ACLY overexpression upregulated REGγ expression and activated the REGγ-proteasome pathway, leading to changes in the expression of downstream signaling pathway proteins. This promoted HCC cell proliferation, invasion, and migration in vitro, as well as tumor growth and metastasis in vivo. Secondly, ACLY overexpression increased acetyl-CoA production, upregulated the acetylation level of the REGγ promoter region histone H3K27ac, and subsequently induced REGγ expression. Lastly, enhanced acetylation of the REGγ promoter region histone H3K27ac resulted in upregulated REGγ expression, activation of the REGγ-proteasome pathway, changes in downstream signaling pathway protein expression, and promotion of HCC cell proliferation, invasion, and migration in vitro, as well as tumor growth and metastasis in vivo. Conversely, REGγ knockdown reversed these effects. ACLY and REGγ may serve as potential biomarkers and clinical therapeutic targets for HCC.

The impact of spiritual care on the psychological health and quality of life of adults with heart failure: a systematic review of randomized trials.

Background: Heart failure (HF) brings not only physical pain but also psychological distress. This systematic review investigated the influence of spiritual care on the psychological well-being and quality of life in adults with HF. Methods: We conducted a systematic literature review following PRISMA guidelines, searching seven electronic databases for relevant randomized controlled studies without language or temporal restrictions. The studies were assessed for quality using the Cochrane Bias Risk tool. Results: A total of 13 studies (882 participants) were reviewed, investigating interventions such as religion, meditation, mental health, cognitive interventions, and spiritual support. Key factors influencing the effectiveness of spiritual care implementation included integration into routine care, respect for diversity, patient engagement, intervention quality, and alignment with patient beliefs. The majority of the studies indicated that spiritual care has a potentially beneficial impact on the mental health and quality of life of patients with HF. Conclusion: The findings provide valuable insights for healthcare professionals, highlighting the importance of adopting a spiritual care approach to healthcare for this population.

Foreground Capture Feature Pyramid Network-Oriented Object Detection in Complex Backgrounds.

Feature pyramids are widely adopted in visual detection models for capturing multiscale features of objects. However, the utilization of feature pyramids in practical object detection tasks is prone to complex background interference, resulting in suboptimal capture of discriminative multiscale foreground semantic features. In this article, a foreground capture feature pyramid network (FCFPN) for multiscale object detection is proposed, to address the problem of inadequate feature learning in complex backgrounds. FCFPN consists of a foreground dual attention (FDA) module and a pathway aggregation (PA) structure. Specifically, the FDA mechanism activates top-down foreground channel responses and lateral spatial foreground location features, so that channel and spatial foreground features are adequately captured. Then, the PA module adaptively learns the fusion weights of multiscale features at different levels of the feature pyramid, which enhances the complementarity of semantic information between different levels of the foreground feature maps. Since the fusion weights are learned adaptively based on different pyramid levels, the detection model accordingly retains the gained information of feature sizes and suppresses the conflicting information. The evaluations on public datasets and the self-built complex background dataset demonstrate that the detection average precision (AP) and the feature learning performance of the proposed method are superior compared with other FPNs, which proves the effectiveness of the proposed FCFPN.

Machine learning models and nomogram based on clinical, laboratory profiles and skeletal muscle index to predict pancreatic fistula after pancreatoduodenectomy.

Background: Postoperative pancreatic fistula (POPF) is a perilous complication that may arise subsequent to pancreaticoduodenectomy (PD). In recent times, there has been an escalating interest in employing machine learning (ML) techniques to aid in treatment decision-making. The purpose of this research is to assess the effectiveness of ML in comparison to conventional models, while also conducting an initial evaluation of the predictive capability of skeletal muscle index (SMI) concerning POPF. Methods: This retrospective observational study was carried out at The First Affiliated Hospital of Wenzhou Medical University from January 2012 to January 2021, encompassing data from 269 patients who underwent PD. After identifying independent factors associated with the condition, a logistic regression model was employed to construct a nomogram, alongside the establishment of five ML models. To assess their effectiveness, the best-performing ML model and nomogram were evaluated on a separate test group comprising 77 additional patients. The evaluation involved comparing the area under the curve (AUC) and Brier score. Results: Among the 269 patients studied, the incidence of POPF was found to be 56.9%, with 106 patients (69.3%) experiencing clinically-relevant POPF. We identified six independent factors associated with POPF, including body mass index (BMI), SMI, pancreatic duct dilatation, tumor size, triglyceride levels, and the ratio of aspartate aminotransferase to alanine aminotransferase (AST/ALT) on the first postoperative day. When evaluated on the test set, the Gaussian Naive Bayes (GNB) model, which was the best-performing ML model, achieved an AUC of 0.824 and a Brier score of 0.175. The corresponding performance indicators for the nomogram were 0.844 for AUC and 0.165 for the Brier score. Conclusions: This study found that there is minimal difference between ML and the nomogram based on logistic regression in predicting POPF. Additionally, SMI shows promise as a potential and practical tool for assessing the risk of POPF.

Enhanced Low-Concentration Phosphate Adsorption Using Magnetic UiO-66@Fe3O4 Composite with Potential Linker Exchange.

A magnetic FenUiO-66 adsorbent was created to achieve high phosphate adsorption capacity. The incorporation of Fe3O4 facilitated the precipitation and growth of UiO-66 during crystallization, resulting in a shift towards a multilayer heterogeneous distribution of adsorption sites. The increased Fe3O4 content notably enhanced the magnetic properties of FenUiO-66, while negligibly affecting its adsorption performance. The Fe1.5UiO-66 demonstrated exceptional phosphate adsorption capacity (136.54 mg/g), outstanding selectivity, and sustained reusability, with an 80% removal efficiency after nine cycles of treating actual water. The mechanism of phosphate adsorption by FenUiO-66 involved electrostatic attraction, ligand exchange, and linker exchange. Notably, while linker exchange significantly contributed to high adsorption capacity, it resulted in irreversible damage to the FenUiO-66 crystal. These unequivocal findings will serve as a solid foundation for further research and underline the critical role of linkers in the process of phosphate adsorption.

A chemo/chemodynamic nanoparticle based on hyaluronic acid induces ferroptosis and apoptosis for triple-negative breast cancer therapy.

Triple-negative breast cancer (TNBC) poses a serious threat to women's life and health due to its high malignancy, strong invasiveness, and propensity for early recurrence and metastasis. Therefore, there is an urgent need to develop a highly effective and low-toxic TNBC treatment scheme to enhance the anti-cancer efficacy and prolong the survival of patients. In this work, we designed and synthesized a chemodynamic therapy (CDT) agent (HA-Fc-Mal). The chemo/chemodynamic (CT/CDT) nanoparticle (HCM@DOX) based on hyaluronic acid induces ferroptosis and apoptotic for TNBC therapy was constructed via self-assembled of HA-Fc-Mal and doxorubicin (DOX). HCM@DOX orderly realized the TNBC targeting, controlled DOX release, GSH depletion and induce ROS erupt. In vivo and in vitro experiments confirmed that HCM@DOX inhibited the growth of 4 T1 tumors through ferroptosis and apoptosis, and the tumor inhibition rate was as high as 81.87 %. In addition, HCM@DOX significantly inhibited lung metastasis and exhibited excellent biosafety. Overall, our findings offer a new strategy for TNBC therapy using a CT/CDT nanoparticle that induces ferroptosis and apoptosis.

PeNAC67-PeKAN2-PeSCL23 and B-class MADS-box transcription factors synergistically regulate the specialization process from petal to lip in Phalaenopsis equestris.

The molecular basis of orchid flower development involves a specific regulatory program in which MADS-box transcription factors play a central role. The recent 'perianth code' model hypothesizes that two types of higher-order heterotetrameric complexes, namely SP complex and L complex, play pivotal roles in the orchid perianth organ formation. Therefore, we explored their roles and searched for other components of the regulatory network.Through the combined analysis for transposase-accessible chromatin with high-throughput sequencing and RNA sequencing of the lip-like petal and lip from Phalaenopsis equestris var.trilip, transcription factor-(TF) genes involved in lip development were revealed. PeNAC67 encoding a NAC-type TF and PeSCL23 encoding a GRAS-type TF were differentially expressed between the lip-like petal and the lip. PeNAC67 interacted with and stabilized PeMADS3, which positively regulated the development of lip-like petal to lip. PeSCL23 and PeNAC67 competitively bound with PeKAN2 and positively regulated the development of lip-like petal to petal by affecting the level of PeMADS3. PeKAN2 as an important TF that interacts with PeMADS3 and PeMADS9 can promote lip development. These results extend the 'perianth code' model and shed light on the complex regulation of orchid flower development.

Copper-Based Composites Nanoparticles Improve Triple-Negative Breast Cancer Treatment with Induction of Apoptosis-Cuproptosis and Immune Activation.

The synergistic effect of apoptosis and cuproptosis, along with the activation of the immune system, presents a promising approach to enhance the efficacy against triple-negative breast cancer (TNBC). Here, two prodrugs are synthesized: a reactive oxygen species (ROS)-responsive prodrug PEG-TK-DOX and a glutathione (GSH)-responsive prodrug PEG-DTPA-SS-CPT. These prodrugs are self-assembled and chelated Cu2+ to prepare nanoparticle PCD@Cu that simultaneously loaded doxorubicin (DOX), camptothecin (CPT), and Cu2+. The elevated levels of ROS and GSH in TNBC cells disrupted the PCD@Cu structure, leading to the release of Cu+, DOX, and CPT and the depletion of GSH. DOX and CPT triggered apoptosis with immunogenic cell death (ICD) in TNBC cells. Simultaneously, PCD@Cu downregulated the expression of copper transporting ATPase 2 (ATP7B), causing a significant accumulation of copper ions in TNBC cells. This further induced the aggregation of lipoylated dihydrolipoamide S-acetyltransferase (DLAT) and downregulation of iron-sulfur (Fe-S) cluster proteins, ultimately leading to cuproptosis and ICD in TNBC. In vitro and in vivo experiments confirmed that PCD@Cu induced apoptosis and cuproptosis in TNBC and activated the immune system, demonstrating strong anti-tumor capabilities. Moreover, PCD@Cu exhibited an excellent biosafety profile. Overall, this study provides a promising strategy for effective TNBC therapy.

Effect and mechanism of T lymphocytes on human induced pluripotent stem cell-derived cardiomyocytes via Proteomics.

BACKGROUND: Abnormalities in T cell activation play an important role in the pathogenesis of myocarditis, and persistent T cell responses can lead to autoimmunity and chronic cardiac inflammation, as well as even dilated cardiomyopathy. Although previous work has examined the role of T cells in myocarditis in animal models, the specific mechanism for human cardiomyocytes has not been investigated. METHODS: In this study, we constructed the human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and established the T cell-mediated cardiac injury model by co-culturing with activated CD4 + T or CD8 + T cells that were isolated from peripheral mononuclear blood to elucidate the pathogenesis of myocardial cell injury caused by inflammation. RESULTS: By combination of quantitative proteomics with tissue and cell immunofluorescence examination, we established a proteome profile of inflammatory myocardia from hiPSC-CMs with obvious cardiomyocyte injury and increased levels of lactate dehydrogenase content, creatine kinase isoenzyme MB and cardiac troponin. A series of molecular dysfunctions of hiPSC-CMs was observed and indicated that CD4 + cells could produce direct cardiomyocyte injury by activating the NOD-like receptor signals pathway. CONCLUSIONS: The data presented in our study established a proteome map of inflammatory myocardial based on hiPSC-CMs injury model. These results can provide guidance in the discovery of improved clinical treatments for myocarditis.

Optimal decision-making in relieving global high temperature-related disease burden by data-driven simulation.

The rapid acceleration of global warming has led to an increased burden of high temperature-related diseases (HTDs), highlighting the need for advanced evidence-based management strategies. We have developed a conceptual framework aimed at alleviating the global burden of HTDs, grounded in the One Health concept. This framework refines the impact pathway and establishes systematic data-driven models to inform the adoption of evidence-based decision-making, tailored to distinct contexts. We collected extensive national-level data from authoritative public databases for the years 2010-2019. The burdens of five categories of disease causes - cardiovascular diseases, infectious respiratory diseases, injuries, metabolic diseases, and non-infectious respiratory diseases - were designated as intermediate outcome variables. The cumulative burden of these five categories, referred to as the total HTD burden, was the final outcome variable. We evaluated the predictive performance of eight models and subsequently introduced twelve intervention measures, allowing us to explore optimal decision-making strategies and assess their corresponding contributions. Our model selection results demonstrated the superior performance of the Graph Neural Network (GNN) model across various metrics. Utilizing simulations driven by the GNN model, we identified a set of optimal intervention strategies for reducing disease burden, specifically tailored to the seven major regions: East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa. Sectoral mitigation and adaptation measures, acting upon our categories of Infrastructure & Community, Ecosystem Resilience, and Health System Capacity, exhibited particularly strong performance for various regions and diseases. Seven out of twelve interventions were included in the optimal intervention package for each region, including raising low-carbon energy use, increasing energy intensity, improving livestock feed, expanding basic health care delivery coverage, enhancing health financing, addressing air pollution, and improving road infrastructure. The outcome of this study is a global decision-making tool, offering a systematic methodology for policymakers to develop targeted intervention strategies to address the increasingly severe challenge of HTDs in the context of global warming.

Large-Scale Proteome Profiling Identifies Biomarkers Associated with Suspected Neurosyphilis Diagnosis.

Neurosyphilis (NS) is a central nervous system (CNS) infection caused by Treponema pallidum (T. pallidum). NS can occur at any stage of syphilis and manifests as a broad spectrum of clinical symptoms. Often referred to as "the great imitator," NS can be easily overlooked or misdiagnosed due to the absence of standard diagnostic tests, potentially leading to severe and irreversible organ dysfunction. In this study, proteomic and machine learning model techniques are used to characterize 223 cerebrospinal fluid (CSF) samples to identify diagnostic markers of NS and provide insights into the underlying mechanisms of the associated inflammatory responses. Three biomarkers (SEMA7A, SERPINA3, and ITIH4) are validated as contributors to NS diagnosis through multicenter verification of an additional 115 CSF samples. We anticipate that the identified biomarkers will become effective tools for assisting in diagnosis of NS. Our insights into NS pathogenesis in brain tissue may inform therapeutic strategies and drug discoveries for NS patients.

Global One Health index for zoonoses: A performance assessment in 160 countries and territories.

The One Health (OH) approach is used to control/prevent zoonotic events. However, there is a lack of tools for systematically assessing OH practices. Here, we applied the Global OH Index (GOHI) to evaluate the global OH performance for zoonoses (GOHI-Zoonoses). The fuzzy analytic hierarchy process algorithm and fuzzy comparison matrix were used to calculate the weights and scores of five key indicators, 16 subindicators, and 31 datasets for 160 countries and territories worldwide. The distribution of GOHI-Zoonoses scores varies significantly across countries and regions, reflecting the strengths and weaknesses in controlling or responding to zoonotic threats. Correlation analyses revealed that the GOHI-Zoonoses score was associated with economic, sociodemographic, environmental, climatic, and zoological factors. Additionally, the Human Development Index had a positive effect on the score. This study provides an evidence-based reference and guidance for global, regional, and country-level efforts to optimize the health of people, animals, and the environment.

How far has the globe gone in achieving One Health? Current evidence and policy implications based on global One Health index.

Background: In the 21st century, as globalization accelerates and global public health crises occur, the One Health approach, guided by the holistic thinking of human-animal-environment and emphasizing interdisciplinary collaboration to address global health issues, has been strongly advocated by the international community. An immediate requirement exists for the creation of an assessment tool to foster One Health initiatives on both global and national scales. Methods: Built upon extensive expert consultations and dialogues, this follow-up study enhances the 2022 global One Health index (GOHI) indicator system. The GOHI framework is enriched by covering three indices, e.g. external drivers index (EDI), intrinsic drivers index (IDI), and core drivers index (CDI). The comprehensive indicator system incorporates 13 key indicators, 50 indicators, and 170 sub I-indicators, utilizing a fuzzy analytic hierarchy process to ascertain the weight for each indicator. Weighted and summed, the EDI, IDI, and CDI scores contribute to the computation of the overall GOHI 2022 score. By comparing the ranking and the overall scores among the seven regions and across 160 countries/territories, we have not only derived an overall profile of the GOHI 2022 scores, but also assessed the GOHI framework. We also compared rankings of indicators and sub I-indicators to provide greater clarity on the strengths and weaknesses of each region within the One Health domains. Results: The GOHI 2022 performance reveals significant disparities between countries/territories ranged from 39.03 to 70.61. The global average score of the GOHI 2022 is 54.82. The average score for EDI, IDI, and CDI are 46.57, 58.01, and 57.25, respectively. In terms of global rankings, countries from North America, Europe and Central Asia, East Asia and Pacific present higher scores. In terms of One Health domains of CDI, the lowest scores are observed in antimicrobial resistance (median: 43.09), followed by food security (median: 53.78), governance (median: 54.77), climate change (median: 64.12) and zoonotic diseases (median: 69.23). Globally, the scores of GOHI vary spatially, with the highest score in North America while lowest in sub-Saharan Africa. In addition, evidence shows associations between the socio-demographic profile of countries/territories and their GOHI performance in certain One Health scenarios. Conclusion: The objective of GOHI is to guide impactful strategies for enhancing capacity building in One Health. With advanced technology and an annually updated database, intensifying efforts to refine GOHI's data-mining methodologies become imperative. The goal is to offer profound insights into disparities and progressions in practical One Health implementation, particularly in anticipation of future pandemics.