Collaborative multiple change detection methods for monitoring the spatio-temporal dynamics of mangroves in Beibu Gulf, China

Mangrove ecosystems are one of the most diverse and productive marine ecosystems around the world, although losses of global mangrove area have been occurring over the past decades. Therefore, tracking spatio-temporal changes and assessing the current state are essential for mangroves conservation. To solve the issues of inaccurate detection results of single algorithms and those limited to historical change detection, this study proposes the detect–monitor–predict (DMP) framework of mangroves for detecting time-series historical changes, monitoring abrupt near-real-time events, and predicting future trends in Beibu Gulf, China, through the synergetic use of multiple detection change algorithms. This study further developed a method for extracting mangroves using multi-source inter-annual time-series spectral indices images, and evaluated the performance of twenty-one spectral indices for capturing expansion events of mangroves. Finally, this study reveals the spatio-temporal dynamics of mangroves in Beibu Gulf from 1986 to 2021. In this study, we found that our method could extract mangrove growth regions from 1986 to 2021, and achieved 0.887 overall accuracy, which proved that this method is able to rapidly extract large-scale mangroves without field-based samples. We confirmed that the normalized difference vegetation index and tasseled cap angle outperform other spectral indexes in capturing mangrove expansion changes, while enhanced vegetation index and soil-adjusted vegetation index capture the change events with a time delay. This study revealed that mangrove changes displayed historical changes in the hierarchical gradient from land to sea with an average annual expansion of 239.822 ha in the Beibu Gulf during 1986–2021, detected slight improvements and deteriorations of some contemporary mangroves, and predicted 72.778% of mangroves with good growth conditions in the future

Protocol for a longitudinal twin birth cohort study to unravel the complex interplay between early-life environmental and genetic risk factors in health and disease: the Chongqing Longitudinal Twin Study (LoTiS)

INTRODUCTION: Non-communicable diseases (NCD) now represent the major burden of adverse health in most countries. It is clear that much of the risk of such conditions begins very early in life, potentially in utero. Given their complex aetiology, an understanding of the origins of NCD requires an in-depth analysis of the interplay between genetic variation and environment, preferably over time. For decades, twin studies have played a key role in understanding such traits. Their strength lies in the ability to disentangle genetic and environmental factors that contribute to a phenotype. This is done by comparing genetically identical monozygotic (MZ) with dizygotic twins, who share on average 50% of genetic variation, or by comparing MZ twins within a pair. This study aims to determine the relative contributions of genes and environment to early-onset intermediate phenotypes related to later adult onset disease (such as growth and neurodevelopment) and to identify specific biomarkers and time points for emergence of phenotypes from infancy, largely independent of underlying genetic factors. METHODS/DESIGN: The Chongqing Longitudinal Twin Study (LoTiS) will recruit 300 women pregnant with twins, enriched for MZ pregnancies, with follow-up to 3&thinsp;years of age. Data collection will be undertaken at key time points in gestation (&times;3), at delivery and postnatally (&times;9). Maternal and infant biospecimens including blood, urine, hair, nails and buccal swabs along with measures such as fetal scans and body measurements will be collected. Additional information from questionnaires and medical records includes pregnancy, diet, sociodemographics, maternal stress, and infant growth and neurodevelopment. ETHICS AND DISSEMINATION: This study has been approved by the Ethics Committee of Chongqing Medical University (record no: 201530) and has been registered with the Chinese Clinical Trial Registry (registry no: ChiCTR-OOC-16008203). Results of the recruitment and all subsequent analyses will be submitted for publication in peer-reviewed journals.<br /

Peripheral blood CD19 positive B lymphocytes increase after ischemic stroke and correlate with carotid atherosclerosis

IntroductionAtherosclerosis is the primary pathological basis of ischemic stroke, and dyslipidemia is one of its major etiological factors. Acute ischemic stroke patients exhibit imbalances in lymphocyte subpopulations, yet the correlation between these dynamic changes in lymphocyte subpopulations and lipid metabolism disorders, as well as carotid atherosclerosis in stroke patients remains poorly understood.MethodsWe retrospectively analyzed the demographic data, risk factors of cerebrovascular disease, laboratory examination (lymphocyte subsets, lipid indexes, etc.), clinical features and c;/]-sity from December 2017 to September 2019 and non-stroke patients with dizziness/vertigo during the same period.ResultsThe results showed that peripheral B lymphocyte proportions are elevated in acute ischemic stroke patients compared with those of the control group (13.6 ± 5.3 vs. 11.7 ± 4.4%, p = 0.006). Higher B lymphocyte proportions are associated with concurrent dyslipidemia, increased levels of vascular risk factors including triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and very-low-density lipoprotein cholesterol (VLDL-C), as well as decreased levels of the protective factor high-density lipoprotein cholesterol (HDL-C). Elevated B lymphocyte proportions are independently correlated with carotid atherosclerosis in stroke patients.DiscussionWe found CD19 positive B Lymphocytes increase after ischemic stroke and correlate with Carotid Atherosclerosis. Lymphocyte subpopulations should be highlighted in stroke patients

Sgrgan: sketch-guided restoration for traditional Chinese landscape paintings

Abstract Image restoration is a prominent field of research in computer vision. Restoring broken paintings, especially ancient Chinese artworks, is a significant challenge for current restoration models. The difficulty lies in realistically reinstating the intricate and delicate textures inherent in the original pieces. This process requires preserving the unique style and artistic characteristics of the ancient Chinese paintings. To enhance the effectiveness of restoring and preserving traditional Chinese paintings, this paper presents a framework called Sketch-Guided Restoration Generative Adversarial Network, termd SGRGAN. The framework employs sketch images as structural priors, providing essential information for the restoration process. Additionally, a novel Focal block is proposed to enhance the fusion and interaction of textural and structural elements. It is noteworthy that a BiSCCFormer block, incorporating a Bi-level routing attention mechanism, is devised to comprehensively grasp the structural and semantic details of the image, including its contours and layout. Extensive experiments and ablation studies on MaskCLP and Mural datasets demonstrate the superiority of the proposed method over previous state-of-the-art methods. Specifically, the model demonstrates outstanding visual fidelity, particularly in the restoration of landscape paintings. This further underscores its efficacy and universality in the realm of cultural heritage preservation and restoration

Multicomponent comprehensive confirms that erythroferrone is a molecular biomarker of pan-cancer

All vertebrates organisms produce erythroferrone, a secretory hormone with structure-related functions during iron homeostasis. However, limited knowledge exists regarding the effect of this hormone on the occurrence and progression of cancer. To systematically and comprehensively identify the diverse implications of Erythroferrone (ERFE) in various malignant tumors, we conducted an in-depth analysis of multiple datasets, including the expression levels of oncogenes and target proteins, biological functions, and molecular characteristics. This analysis aimed to assess the diagnostic and prognostic value of ERFE in pan-cancer. Our findings revealed a significant elevation in ERFE expression across 20 distinct cancer types, with notable increases in gastrointestinal cancers. Utilizing the Cytoscape and STRING databases, we identified 35 ERFE-targeted binding proteins. Survival prognosis studies, particularly gastrointestinal cancers indicated by Colon adenocarcinoma (COAD), demonstrated a poor prognosis in patients with high ERFE expression (p 0.9). Understanding the roles and interactions of ERFE in biological processes can also be aided by examining the genes co-expressed with ERFE in the coat and ranking the top 50 positive and negative genes. In the correlation analysis between the ERFE gene and different immune cells in COAD, we discovered that the expression of ERFE was positively correlated with Th1 cells, cytotoxic cells, and activated DC (aDC) abundance, and negatively correlated with Tcm (T central memory) abundance (P < 0.001). in summary, ERFE emerges as strongly associated with various malignant cancers, positioning it as a prospective biological target for cancer treatment. It stands out as a key molecular biomarker for diagnosing and prognosticating pancreatic cancer, also serves as an independent prognostic risk factor for COAD

Ultrasmall metal alloy nanozymes mimicking neutrophil enzymatic cascades for tumor catalytic therapy

Abstract Developing strategies that emulate the killing mechanism of neutrophils, which involves the enzymatic cascade of superoxide dismutase (SOD) and myeloperoxidase (MPO), shows potential as a viable approach for cancer therapy. Nonetheless, utilizing natural enzymes as therapeutics is hindered by various challenges. While nanozymes have emerged for cancer treatment, developing SOD-MPO cascade in one nanozyme remains a challenge. Here, we develop nanozymes possessing both SOD- and MPO-like activities through alloying Au and Pd, which exhibits the highest cascade activity when the ratio of Au and Pd is 1:3, attributing to the high d-band center and adsorption energy for superoxide anions, as determined through theoretical calculations. The Au1Pd3 alloy nanozymes exhibit excellent tumor therapeutic performance and safety in female tumor-bearing mice, with safety attributed to their tumor-specific killing ability and renal clearance ability caused by ultrasmall size. Together, this work develops ultrasmall AuPd alloy nanozymes that mimic neutrophil enzymatic cascades for catalytic treatment of tumors

Pluripotency and differentiation of embryonic stem cells

Mouse embryonic stem (ES) cells derive from the inner cell mass of an early embryo called blastocyst, making them promising resource for regenerative medicine. They possess two unique properties: self-renewal and pluripotency. Different ways can be used to assess which extracellular signal and factor inside ES cells has an impact on the pluripotency of ES cells. Nowadays, many extracellular signals and transcription factors have been identified, such as extracellular signals like LIF and transcription factors like Oct4. Studying the mechanism and function of these factors offers great insight and advance our understanding of pluripotency and self-renewal and thus shed light on regenerative medicine

Additional file 1 of The Effect of immunonutrition in patients undergoing pancreaticoduodenectomy: a systematic review and meta-analysis

Supplementary Material

Enhancing Machine-Learning Prediction of Enzyme Catalytic Temperature Optima through Amino Acid Conservation Analysis

Enzymes play a crucial role in various industrial production and pharmaceutical developments, serving as catalysts for numerous biochemical reactions. Determining the optimal catalytic temperature (Topt) of enzymes is crucial for optimizing reaction conditions, enhancing catalytic efficiency, and accelerating the industrial processes. However, due to the limited availability of experimentally determined Topt data and the insufficient accuracy of existing computational methods in predicting Topt, there is an urgent need for a computational approach to predict the Topt values of enzymes accurately. In this study, using phosphatase (EC 3.1.3.X) as an example, we constructed a machine learning model utilizing amino acid frequency and protein molecular weight information as features and employing the K-nearest neighbors regression algorithm to predict the Topt of enzymes. Usually, when conducting engineering for enzyme thermostability, researchers tend not to modify conserved amino acids. Therefore, we utilized this machine learning model to predict the Topt of phosphatase sequences after removing conserved amino acids. We found that the predictive model’s mean coefficient of determination (R2) value increased from 0.599 to 0.755 compared to the model based on the complete sequences. Subsequently, experimental validation on 10 phosphatase enzymes with undetermined optimal catalytic temperatures shows that the predicted values of most phosphatase enzymes based on the sequence without conservative amino acids are closer to the experimental optimal catalytic temperature values. This study lays the foundation for the rapid selection of enzymes suitable for industrial conditions

A Novel Fast Photothermal Therapy Using Hot Spots of Gold Nanorods for Malignant Melanoma Cells

In this paper, the plasmon resonance effects of gold nanorods was used to achieve rapid photothermal therapy for malignant melanoma cells (A375 cells). After incubation with A375 cells for 24 h, gold nanorods were taken up by the cells and gold nanorod clusters were formed naturally in the organelles of A375 cells. After analyzing the angle and space between the nanorods in clusters, a series of numerical simulations were performed and the results show that the plasmon resonance coupling between the gold nanorods can lead to a field enhancement of up to 60 times. Such high energy localization causes the temperature around the nanorods to rise rapidly and induce cell death. In this treatment, a laser as low as 9.3 mW was used to irradiate a single cell for 20 s and the cell died two h later. The cell death time can also be controlled by changing the power of laser which is focused on the cells. The advantage of this therapy is low laser treatment power, short treatment time, and small treatment range. As a result, the damage of the normal tissue by the photothermal effect can be greatly avoided