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.

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.

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.

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.

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.

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 H2 O2 . 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.

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.

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.

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.

Chloroxine inhibits pancreatic cancer progression through targeted antagonization of the PI3K/AKT/mTOR signaling pathway.

BACKGROUND: Patients with pancreatic cancer have a dismal prognosis due to tumor cell infiltration and metastasis. Many reports have documented that EMT and PI3K-AKT-mTOR axis control pancreatic cancer cell infiltration and metastasis. Chloroxine is an artificially synthesized antibacterial compound that demonstrated anti-pancreatic cancer effects in our previous drug-screening trial. We have explored the impact of chloroxine on pancreatic cancer growth, infiltration, migration, and apoptosis. METHODS: The proliferation of pancreatic cancer cell lines (PCCs) treated with chloroxine was assessed through real-time cell analysis (RTCA), colony formation assay, CCK-8 assay, as well as immunofluorescence. Chloroxine effects on the infiltrative and migratory capacities of PCCs were assessed via Transwell invasion and scratch experiments. To assess the contents of EMT- and apoptosis-associated proteins in tumor cells, we adopted Western immunoblotting as well as immunofluorescence assays, and flow cytometry to determine chloroxine effects on PCCs apoptosis. The in vivo chloroxine antineoplastic effects were explored in nude mice xenografts. RESULTS: Chloroxine repressed pancreatic cancer cell growth, migration, and infiltration in vitro, as well as in vivo, and stimulated apoptosis of the PCCs. Chloroxine appeared to inhibit PCC growth by Ki67 downregulation; this targeted and inhibited aberrant stimulation of the PI3K-AKT-mTOR signaling cascade, triggered apoptosis in PCC via mitochondria-dependent apoptosis, and modulated the EMT to inhibit PCC infiltration and migration. CONCLUSIONS: Chloroxine targeted and inhibited the PI3K-AKT-mTOR cascade to repress PCCs growth, migration, as well as invasion, and triggered cellular apoptosis. Therefore, chloroxine may constitute a potential antineoplastic drug for the treatment of pancreatic cancer.

Psychological distress and aggression among adolescents with internet gaming disorder symptoms.

The present study aimed to investigate the current situation of internet gaming disorder (IGD) in Chinese adolescents and explore the impact of IGD-related factors on adolescent aggression. We hypothesized that IGD symptoms in adolescents would be associated with aggressive behavior and that risk factors for IGD symptoms could increase the aggressive tendencies of adolescents. To verify the above hypothesis, a cross-sectional survey of junior and senior high school students from southern, southwestern, central, and eastern China was conducted. A total of 9306 valid questionnaires were collected. The results showed that the prevalence of IGD symptoms was 1.78 % among Chinese adolescents. The adolescents in the disordered gamer group had the most severe IGD symptoms, with the highest levels of psychological distress and aggression. Interestingly, adolescents in the casual gamer group had the lowest psychological distress and aggression scores. Linear regression analysis further showed that higher levels of aggression were significantly associated with male sex, younger age, more severe psychological distress and IGD symptoms, and more violent game exposure. Our results suggested that excessive online gaming not only contributes to psychological distress in adolescents but also increases their levels of aggressive behavior. Apart from male sex and younger age, severe IGD symptoms and psychological distress are the most important predictors of the development of aggressive behavior.

SARS-CoV-2-infected hiPSC-derived cardiomyocytes reveal dynamic changes in the COVID-19 hearts.

BACKGROUND: The ongoing coronavirus disease 2019 (COVID-19) pandemic has had an enormous impact on our societies. Moreover, the disease's extensive and sustained symptoms are now becoming a nonnegligible medical challenge. In this respect, data indicate that heart failure is one of the most common readmission diagnoses among COVID-19 patients. METHODS: In this study, we used human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes to develop an in vitro model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and studied the dynamic changes occurring in cardiomyocytes after SARS-CoV-2 infection. RESULTS: To this end, we have created an effective time series SARS-CoV-2 infection model exhibiting different functional patterns of up- and downregulated proteins, and demonstrating that SARS-CoV-2 mainly affects (i) the lipid and the energy metabolism of hiPSC-derived cardiomyocytes during the early infection stage, and (ii) the DNA repair ability of cardiomyocytes during the late infection stage. By analyzing the proteome changes occurring at different infection timepoints, we were able to observe that the simulated disease (COVID-19) course developed rapidly, and that each of the studied timepoints was characterized by a distinct protein expression pattern. CONCLUSIONS: Our findings highlight the importance of early detection and personalized treatment based on the disease stage. Finally, by combing the proteomics data with virus-host interaction network analysis, we were able to identify several potential drug targets for the disease.

Three-dimensional reconstructions of mechanosensory end organs suggest a unifying mechanism underlying dynamic, light touch.

Across mammalian skin, structurally complex and diverse mechanosensory end organs respond to mechanical stimuli and enable our perception of dynamic, light touch. How forces act on morphologically dissimilar mechanosensory end organs of the skin to gate the requisite mechanotransduction channel Piezo2 and excite mechanosensory neurons is not understood. Here, we report high-resolution reconstructions of the hair follicle lanceolate complex, Meissner corpuscle, and Pacinian corpuscle and the subcellular distribution of Piezo2 within them. Across all three end organs, Piezo2 is restricted to the sensory axon membrane, including axon protrusions that extend from the axon body. These protrusions, which are numerous and elaborate extensively within the end organs, tether the axon to resident non-neuronal cells via adherens junctions. These findings support a unified model for dynamic touch in which mechanical stimuli stretch hundreds to thousands of axon protrusions across an end organ, opening proximal, axonal Piezo2 channels and exciting the neuron.

Interaction of total dissolved gas supersaturation and suspended sediment on swimming performance of bighead carp (Hypopthalmichthys nobilis).

When dams discharge floodwaters, the river downstream often becomes supersaturated in total dissolved gases (TDG) and contains high volumes of suspended sediments (SS). Supersaturated TDG and high SS concentrations in water may affect fish physiologically in ways that manifest in swimming performance. Despite increasing awareness of the separate effects of TDG supersaturation and SS, knowledge about their synergistic effects remains unknown. To explore the interactive effects of TDG and SS on the swimming performance of bighead carp, the juveniles were exposed to 100, 110, 115, 120, 125, 130, 135, and 140% of TDG-supersaturated water with SS concentrations of 0, 50, 100, and 150 mg/L, respectively, and the critical swimming ability speed (Ucrit ) and burst swimming ability speed (Uburst ) were measured. The results indicated that the swimming ability (Ucrit and Uburst ) decreased when TDG levels and SS concentrations increased. TDG and SS did not interact significantly to decrease both Ucrit and Uburst . In contrast, exposure to TDG alone significantly decreased both Ucrit and Uburst , whereas exposure to SS alone decreased only Uburst . In addition, our results suggested that there was a negative linear relationship between TDG and fatigue time. Swimming ability can decline significantly due to high TDG levels (>130%). Therefore, high TDG levels (>130%) should be restricted during reservoir operation to prevent the stress caused by TDG.

Tackling global health security by building an academic community for One Health action.

BACKGROUND: One Health approach is crucial to tackling complex global public health threats at the interface of humans, animals, and the environment. As outlined in the One Health Joint Plan of Action, the international One Health community includes stakeholders from different sectors. Supported by the Bill & Melinda Gates Foundation, an academic community for One Health action has been proposed with the aim of promoting the understanding and real-world implementation of One Health approach and contribution towards the Sustainable Development Goals for a healthy planet. MAIN TEXT: The proposed academic community would contribute to generating high-quality scientific evidence, distilling local experiences as well as fostering an interconnected One Health culture and mindset, among various stakeholders on different levels and in all sectors. The major scope of the community covers One Health governance, zoonotic diseases, food security, antimicrobial resistance, and climate change along with the research agenda to be developed. The academic community will be supported by two committees, including a strategic consultancy committee and a scientific steering committee, composed of influential scientists selected from the One Health information database. A workplan containing activities under six objectives is proposed to provide research support, strengthen local capacity, and enhance global participation. CONCLUSIONS: The proposed academic community for One Health action is a crucial step towards enhancing communication, coordination, collaboration, and capacity building for the implementation of One Health. By bringing eminent global experts together, the academic community possesses the potential to generate scientific evidence and provide advice to local governments and international organizations, enabling the pursuit of common goals, collaborative policies, and solutions to misaligned interests.

China's application of the One Health approach in addressing public health threats at the human-animal-environment interface: Advances and challenges.

Background: Due to emerging issues such as global climate change and zoonotic disease pandemics, the One Health approach has gained more attention since the turn of the 21st century. Although One Health thinking has deep roots and early applications in Chinese history, significant gaps exist in China's real-world implementation at the complex interface of the human-animal-environment. Methods: We abstracted the data from the global One Health index study and analysed China's performance in selected fields based on Structure-Process-Outcome model. By comparing China to the Belt & Road and G20 countries, the advances and gaps in China's One Health performance were determined and analysed. Findings: For the selected scientific fields, China generally performs better in ensuring food security and controlling antimicrobial resistance and worse in addressing climate change. Based on the SPO model, the "structure" indicators have the highest proportion (80.00%) of high ranking and the "outcome" indicators have the highest proportion (20.00%) of low ranking. When compared with Belt and Road countries, China scores above the median in almost all indicators (16 out of 18) under the selected scientific fields. When compared with G20 countries, China ranks highest in food security (scores 72.56 and ranks 6th), and lowest in climate change (48.74, 11th). Conclusion: Our results indicate that while China has made significant efforts to enhance the application of the One Health approach in national policies, it still faces challenges in translating policies into practical measures. It is recommended that a holistic One Health action framework be established for China in accordance with diverse social and cultural contexts, with a particular emphasis on overcoming data barriers and mobilizing stakeholders both domestically and globally. Implementation mechanisms, with clarified stakeholder responsibilities and incentives, should be improved along with top-level design.

Spatial oblivion channel attention targeting intra-class diversity feature learning.

Convolutional neural networks (CNNs) have successfully driven many visual recognition tasks including image classification. However, when dealing with classification tasks with intra-class sample style diversity, the network tends to be disturbed by more diverse features, resulting in limited feature learning. In this article, a spatial oblivion channel attention (SOCA) for intra-class diversity feature learning is proposed. Specifically, SOCA performs spatial structure oblivion in a progressive regularization for each channel after convolution, so that the network is not restricted to a limited feature learning, and pays attention to more regionally detailed features. Further, SOCA reassigns channel weights in the progressively oblivious feature space from top to bottom along the channel direction, to ensure the network learns more image details in an orderly manner while not falling into feature redundancy. Experiments are conducted on the standard classification dataset CIFAR-10/100 and two garbage datasets with intra-class diverse styles. SOCA improves SqueezeNet, MobileNet, BN-VGG-19, Inception and ResNet-50 in classification accuracy by 1.31%, 1.18%, 1.57%, 2.09% and 2.27% on average, respectively. The feasibility and effectiveness of intra-class diversity feature learning in SOCA-enhanced networks are verified. Besides, the class activation map shows that more local detail feature regions are activated by adding the SOCA module, which also demonstrates the interpretability of the method for intra-class diversity feature learning.

The projection-specific signals that establish functionally segregated dopaminergic synapses.

Dopaminergic projections regulate various brain functions and are implicated in many neuropsychiatric disorders. There are two anatomically and functionally distinct dopaminergic projections connecting the midbrain to striatum: nigrostriatal, which controls movement, and mesolimbic, which regulates motivation. However, how these discrete dopaminergic synaptic connections are established is unknown. Through an unbiased search, we identify that two groups of antagonistic TGF-ß family members, bone morphogenetic protein (BMP)6/BMP2 and transforming growth factor (TGF)-ß2, regulate dopaminergic synapse development of nigrostriatal and mesolimbic neurons, respectively. Projection-preferential expression of their receptors contributes to specific synapse development. Downstream, Smad1 and Smad2 are specifically activated and required for dopaminergic synapse development and function in nigrostriatal vs. mesolimbic projections. Remarkably, Smad1 mutant mice show motor defects, whereas Smad2 mutant mice show lack of motivation. These results uncover the molecular logic underlying the proper establishment of functionally segregated dopaminergic synapses and may provide strategies to treat relevant, projection-specific disease symptoms by targeting specific BMPs/TGF-ß and/or Smads.

Are biodegradable mulch films a sustainable solution to microplastic mulch film pollution? A biogeochemical perspective.

Mulch film residue contributes significantly to global plastic pollution, and consequently biodegradable mulch films (BDMs) are being adopted as a solution. BDMs decompose relatively quickly, but their complete biodegradation requires suitable conditions that are difficult to achieve in nature, causing biodegradable microplastics (bio-MPs) to be more likely to accumulate in soil than traditional microplastics (MPs). If BDMs are to be considered as a sustainable solution, long-term and in-depth studies to investigate the impact of bio-MPs on the biogeochemical processes are vital to agroecosystems operation and ecosystem services supply. Although bio-MP-derived carbon can potentially convert into biomass during decomposition, its contribution to soil carbon stocks is insignificant. Instead, given their biodegradability, bio-MPs can result in greater alterations of soil biodiversity and community composition. Their high carbon-nitrogen ratios may also significantly regulate various processes involved in the natural decomposition and transformation of soil organic matter, including the reduction of nutrient availability and increase in greenhouse gas emissions. Soil ecosystems are complex organic entities interconnected by disturbance-feedback mechanisms. Given the prevailing knowledge gaps regarding the impact of bio-MPs on soil biogeochemical cycles and ecosystem balance, this study emphasized the safety and sustainability assessment of bio-MPs and the prevailing comprehensive challenges.

Predicting Recurrence in Pancreatic Ductal Adenocarcinoma after Radical Surgery Using an AX-Unet Pancreas Segmentation Model and Dynamic Nomogram.

This study aims to investigate the reliability of radiomic features extracted from contrast-enhanced computer tomography (CT) by AX-Unet, a pancreas segmentation model, to analyse the recurrence of pancreatic ductal adenocarcinoma (PDAC) after radical surgery. In this study, we trained an AX-Unet model to extract the radiomic features from preoperative contrast-enhanced CT images on a training set of 205 PDAC patients. Then we evaluated the segmentation ability of AX-Unet and the relationship between radiomic features and clinical characteristics on an independent testing set of 64 patients with clear prognoses. The lasso regression analysis was used to screen for variables of interest affecting patients' post-operative recurrence, and the Cox proportional risk model regression analysis was used to screen for risk factors and create a nomogram prediction model. The proposed model achieved an accuracy of 85.9% for pancreas segmentation, meeting the requirements of most clinical applications. Radiomic features were found to be significantly correlated with clinical characteristics such as lymph node metastasis, resectability status, and abnormally elevated serum carbohydrate antigen 19-9 (CA 19-9) levels. Specifically, variance and entropy were associated with the recurrence rate (p < 0.05). The AUC for the nomogram predicting whether the patient recurred after surgery was 0.92 (95% CI: 0.78-0.99) and the C index was 0.62 (95% CI: 0.48-0.78). The AX-Unet pancreas segmentation model shows promise in analysing recurrence risk factors after radical surgery for PDAC. Additionally, our findings suggest that a dynamic nomogram model based on AX-Unet can provide pancreatic oncologists with more accurate prognostic assessments for their patients.