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Microeukaryotic plankton are essential to marine food webs and biogeochemical cycles, with coastal seas playing a critical role in aquatic ecosystems. Understanding the diversity of microeukaryotic plankton, deciphering their community structure and succession patterns, and identifying the key factors influencing these dynamics remain central challenges in coastal ecology. In this study, we examine patterns of biodiversity, community structure, and co-occurrence using environmental DNA (eDNA)-based methods. Our results show a linear correlation between α-diversity and distance from the shore, with nutrient-related factors, especially inorganic nitrogen, being the primary determinants of the spatial distribution of plankton communities. Alternation of coastal habitat have shifted the succession patterns of coastal eukaryotic plankton communities from stochastic to deterministic processes. Additionally, our observations indicate that the topology and structure of eukaryotic plankton symbiotic patterns and networks are significantly influenced by environmental heterogeneity such as nutrients, which increase the vulnerability and decrease the stability of offshore ecological networks. Overall, our study demonstrates that the distribution of microeukaryotic plankton communities is influenced by factors related to environmental heterogeneity.

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Image-to-image translation is a vital component in medical imaging processing, with many uses in a wide range of imaging modalities and clinical scenarios. Previous methods include Generative Adversarial Networks (GANs) and Diffusion Models (DMs), which offer realism but suffer from instability and lack uncertainty estimation. Even though both GAN and DM methods have individually exhibited their capability in medical image translation tasks, the potential of combining a GAN and DM to further improve translation performance and to enable uncertainty estimation remains largely unexplored. In this work, we address these challenges by proposing a Cascade Multi-path Shortcut Diffusion Model (CMDM) for high-quality medical image translation and uncertainty estimation. To reduce the required number of iterations and ensure robust performance, our method first obtains a conditional GAN-generated prior image that will be used for the efficient reverse translation with a DM in the subsequent step. Additionally, a multi-path shortcut diffusion strategy is employed to refine translation results and estimate uncertainty. A cascaded pipeline further enhances translation quality, incorporating residual averaging between cascades. We collected three different medical image datasets with two sub-tasks for each dataset to test the generalizability of our approach. Our experimental results found that CMDM can produce high-quality translations comparable to state-of-the-art methods while providing reasonable uncertainty estimations that correlate well with the translation error.

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Lithium-ion batteries are widely used in various applications, including electric vehicles and renewable energy storage. The prediction of the remaining useful life (RUL) of batteries is crucial for ensuring reliable and efficient operation, as well as reducing maintenance costs. However, determining the life cycle of batteries in real-world scenarios is challenging, and existing methods have limitations in predicting the number of cycles iteratively. In addition, existing works often oversimplify the datasets, neglecting important features of the batteries such as temperature, internal resistance, and material type. To address these limitations, this paper proposes a two-stage RUL prediction scheme for Lithium-ion batteries using a spatio-temporal multimodal attention network (ST-MAN). The proposed ST-MAN is to capture the complex spatio-temporal dependencies in the battery data, including the features that are often neglected in existing works. Despite operating without prior knowledge of end-of-life (EOL) events, our method consistently achieves lower error rates, boasting mean absolute error (MAE) and mean square error (MSE) of 0.0275 and 0.0014, respectively, compared to existing convolutional neural networks (CNN) and long short-term memory (LSTM)-based methods. The proposed method has the potential to improve the reliability and efficiency of battery operations and is applicable in various industries.

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BACKGROUND: Associations of dietary sodium and potassium intake with fracture risk are inconsistent and the effects of salt substitute on fracture incidence are unknown. We assessed the effect of salt substitute compared to regular salt intake on fracture incidence using data from the Salt Substitute and Stroke Study (SSaSS). METHODS: SSaSS was a cluster-randomized controlled trial conducted in 600 villages in northern China. Villages were randomly allocated into intervention and control groups in a 1:1 ratio. Salt substitute was provided to intervention villages and control villages continued regular salt use for 5 years. The primary outcome for this secondary analysis was the incidence of all fractures. Secondary outcomes included incidence of vertebral fracture, non-vertebral fracture, and fracture of unknown or non-specific location. RESULTS: 20,995 participants were included in this study, and 821 fractures occurred during follow-up. Intention-to-treat analyses showed no differences between the salt substitute and regular salt groups in the incidence of all fractures (rate ratio (RR) 0.96; 95% CI 0.81 to 1.14), vertebral fracture (RR 0.82; 95% CI 0.53 to 1.26), non-vertebral fracture (RR 1.05; 95% CI 0.86 to 1.29), or fracture of unknown or non-specific location (RR 0.80; 95% CI 0.54 to 1.18). CONCLUSIONS: Use of salt substitute compared to regular salt had no detectable effect on the incidence of fracture in a population at high risk of cardiovascular disease and fracture. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02092090. Registered on March 12, 2014.

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The periosteum contains skeletal stem/progenitor cells that contribute to bone fracture healing. However, the in vivo identity of periosteal skeletal stem cells (P-SSCs) remains unclear, and membrane protein markers of P-SSCs that facilitate tissue engineering are needed. Here, we identified integral membrane protein 2A (Itm2a) enriched in SSCs using single-cell transcriptomics. Itm2a+ P-SSCs displayed clonal multipotency and self-renewal and sat at the apex of their differentiation hierarchy. Lineage-tracing experiments showed that Itm2a selectively labeled the periosteum and that Itm2a+ cells were preferentially located in the outer fibrous layer of the periosteum. The Itm2a+ cells rarely expressed CD34 or Osx, but expressed periosteal markers such as Ctsk, CD51, PDGFRA, Sca1, and Gli1. Itm2a+ P-SSCs contributed to osteoblasts, chondrocytes, and marrow stromal cells upon injury. Genetic lineage tracing using dual recombinases showed that Itm2a and Prrx1 lineage cells generated spatially separated subsets of chondrocytes and osteoblasts during fracture healing. Bone morphogenetic protein 2 (Bmp2) deficiency or ablation of Itm2a+ P-SSCs resulted in defects in fracture healing. ITM2A+ P-SSCs were also present in the human periosteum. Thus, our study identified a membrane protein marker that labels P-SSCs, providing an attractive target for drug and cellular therapy for skeletal disorders.

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Background: Diabetic foot ulcer (DFU) is a serious clinical problem with high amputation and mortality rates, yet there is a lack of desirable therapy. While the extracellular matrix (ECM) contributes significantly to wound healing, ECM-related biomarker for DFU is still unknown. The study was designed to identify ECM-related biomarker in DFU using bioinformatics and machine learning and validate it in STZ-induced mice models. Methods: GSE80178 and GSE134431 microarray datasets were fetched from the GEO database, and differentially expressed genes (DEGs) analysis was performed, respectively. By analyzing DEGs and ECM genes, we identified ECM-related DEGs, and functional enrichment analysis was conducted. Subsequently, three machine learning algorithms (LASSO, RF and SVM-RFE) were applied to filter ECM-related DEGs to identify key ECM-related biomarkers. Next, we conducted immune infiltration analysis, GSEA, and correlation analysis to explore the hub gene underlying mechanism. A lncRNA-miRNA-mRNA and drug regulatory network were constructed. Finally, we validated the key ECM-related biomarker in STZ-induced mice models. Results: One hundred and forty-five common DEGs in adult DFU between the two datasets were identified. Taking the intersection of 145 common DEGs and 964 ECM genes, we identified 13 ECM-related DEGs. Thirteen ECM-related DEGs were mainly enriched in pathways associated with tissue remodeling, inflammation and defense against infectious agents. Ultimately, CTSH was identified as the key ECM-related biomarker. CTSH was associated with difference immune cells during the occurrence and development of DFU, and it influenced hedgehog, IL-17 and TNF signaling pathway. Additionally, CTSH expression is correlated with many ECM- and immune-related genes. A lncRNA-miRNA-mRNA and drug regulatory network were constructed with 10 lncRNAs, 2 miRNAs, CTSH and 1 drug. Finally, CTSH was validated as a key biomarker for DFU in animal models. Conclusion: Our study found that CTSH can be used for both diagnostic and prognostic purposes and might be a potential therapeutic target.

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The dehydro-Diels-Alder (DDA) reaction is a powerful method for the construction of aromatic compounds. However, the enantioselective DDA reaction has been rarely developed, probably due to the competitive thermal reaction. Herein, we report a copper-catalyzed enantioselective DDA reaction through vinyl cation pathway. The reaction leads to the atom-economical synthesis of axially chiral phenyl and indolyl carbazoles in generally excellent yields with good to excellent atroposelectivities. This methodology represents the first example of non-noble metal-catalyzed enantioselective DDA reaction. Notably, new chiral ligand and organocatalyst derived from the constructed axially chiral carbazole are demonstrated to be useful in asymmetric catalysis.

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BACKGROUND: Pain empathy represents a fundamental building block of several social functions, which have been demonstrated to be impaired across various mental disorders by accumulating evidence from case-control functional magnetic resonance imaging (fMRI) studies. However, it remains unclear whether the dysregulations are underpinned by robust neural alterations across mental disorders. METHODS: This study utilized coordinate-based meta-analyses to quantitatively determine robust markers of altered pain empathy across mental disorders. To support the interpretation of the findings exploratory network-level and behavioral meta-analyses were conducted. RESULTS: Quantitative analysis of eleven case-control fMRI studies with data from 296 patients and 229 controls revealed patients with mental disorders exhibited increased pain empathic reactivity in the left anterior cingulate gyrus, adjacent medial prefrontal cortex, and right middle temporal gyrus, yet decreased activity in the left cerebellum IV/V and left middle occipital gyrus compared to controls. The hyperactive regions showed network-level interactions with the core default mode network (DMN) and were associated with affective and social cognitive domains. CONCLUSIONS: The findings suggest that pain-empathic alterations across mental disorders are underpinned by excessive empathic reactivity in brain systems involved in empathic distress and social processes, highlighting a shared therapeutic target to normalize basal social dysfunctions in mental disorders.

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Joint pain and osteoarthritis can occur as coronavirus disease 2019 (COVID-19) sequelae after infection. However, little is known about the damage to articular cartilage. Here we illustrate knee joint damage after wild-type, Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in vivo. Rapid joint injury with cystic lesions at the osteochondral junction was observed in two patients with post-COVID osteoarthritis and recapitulated in a golden Syrian hamster model. SARS-CoV-2-activated endothelin-1 signalling increased vascular permeability and caused viral spike proteins leakage into the subchondral bone. Osteoclast activation, chondrocyte dropout and cyst formation were confirmed histologically. The US Food and Drug Administration-approved endothelin receptor antagonist, macitentan, mitigated cystic lesions and preserved chondrocyte number in the acute phase of viral infection in hamsters. Delayed macitentan treatment at post-acute infection phase alleviated chondrocyte senescence and restored subchondral bone loss. It is worth noting that it could also attenuate viral spike-induced joint pain. Our work suggests endothelin receptor blockade as a novel therapeutic strategy for post-COVID arthritis.

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Extracellular vesicles (EVs) are heterogenous in size, biogenesis, cargo and function. Beside small EVs, aggressive tumor cells release a population of particularly large EVs, namely large oncosomes (LO). This study provides the first resource of label-free quantitative proteomics of LO and small EVs obtained from distinct cancer cell types (prostate, breast, and glioma). This dataset was integrated with a SWATH Proteomic assay on LO, rigorously isolated from the plasma of patients with metastatic prostate cancer (PC). Proteins enriched in LO, which were identified also at the RNA level, and found in plasma LO significantly correlated with PC progression. Single EV RNA-Seq of the PC cell-derived LO confirmed some of the main findings from the bulk RNA-Seq, providing first evidence that single cell technologies can be successfully applied to EVs. This multiomics resource of cancer EVs can be leveraged for developing a multi-analyte approach for liquid biopsy.

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Ovarian cancer (OC) is the deadliest malignancy of the female reproductive system. The standard first-line therapy for OC involves cytoreductive surgical debulking followed by chemotherapy based on platinum and paclitaxel. Despite these treatments, there remains a high rate of tumor recurrence and resistance to platinum. Recent studies have highlighted the potential anti-tumor properties of metformin (met), a traditional diabetes drug. In our study, we investigated the impact of met on the anticancer activities of cisplatin (cDDP) both in vitro and in vivo. Our findings revealed that combining met with cisplatin significantly reduced apoptosis in OC cells, decreased DNA damage, and induced resistance to cDDP. Furthermore, our mechanistic study indicated that the resistance induced by met is primarily driven by the inhibition of the ATM/CHK2 pathway and the upregulation of the Rad51 protein. Using an ATM inhibitor, KU55933, effectively reversed the cisplatin resistance phenotype. In conclusion, our results suggest that met can antagonize the effects of cDDP in specific types of OC cells, leading to a reduction in the chemotherapeutic efficacy of cDDP.

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BACKGROUND: We previously optimized the duration and dose of vonoprazan and amoxicillin dual therapy in China. The efficacy of vonoprazan with b.i.d. amoxicillin in comparison with vonoprazan-containing quadruple therapy as the first-line treatment of Helicobacter pylori infection has not been adequately evaluated. METHODS: In a non-inferiority, randomized clinical trial, H. pylori infected and treatment-naïve patients were randomly assigned to receive 14 days of either vonoprazan dual (vonoprazan 20 mg and amoxicillin 1 g twice daily) or quadruple therapy (vonoprazan 20 mg + amoxicillin 1 g + furazolidone 100 mg + bismuth potassium citrate 600 mg twice daily). H. pylori status was confirmed using 13C-urea breath tests or fecal antigen test. The primary outcome was the H. pylori eradication rate following vonoprazan dual and quadruple therapy at 4-12 weeks. We also compared drug compliance to either regimen and documented their side effect. RESULTS: A total of 190 subjects were randomized. The eradication rate of vonoprazan dual and quadruple therapy were 87.4% and 92.6% (p = 0.23) by intention-to-treat analysis, respectively, and 96.5% and 97.7% (p = 0.63) by per-protocol analysis, respectively. The efficacy of vonoprazan dual therapy was non-inferior to vonoprazan-containing quadruple therapy in per-protocol analysis (p < 0.001; difference: -1.2%; 90% confidence interval: -5.4% to 3.0%). CONCLUSION: Vonoprazan with b.i.d. amoxicillin for 14 days provided similar satisfactory efficacy with vonoprazan-containing quadruple therapy as a first-line H. pylori treatment in China.

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Endemic to the upper and middle reaches of the Yangtze River in China, elongate loach (Leptobotia elongata) has become a vulnerable species mainly due to overfishing and habitat destruction. Thus far, no genome data of this species are reported. As a result, lacking of such genomic information has restricted practical conservation and utilization of this economic fish. Here, we constructed chromosome-level genome assemblies for both male and female elongate loach by integration of MGI, PacBio HiFi and Hi-C sequencing technologies. Two primary genome assemblies (586-Mb and 589-Mb) were obtained for female and male fishes, respectively. Indeed, 98.22% and 98.61% of the contig sequences were anchored onto 25 chromosomes, with identification of 26.22% and 25.92% repeat contents in both assembled genomes. Meanwhile, a total of 25,215 and 25,253 protein-coding genes were annotated, of which 97.41% and 98.8% could be predicted with functions. Taken together, our genome data presented here provide a valuable genomic resource for in-depth evolutionary and functional research, as well as molecular breeding and conservation of this economic fish species.

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PURPOSE: The aim of this study was to observe the influence of differential nutritional status on bone age (BA) change according to body mass index (BMI) and analyze the risk of advanced bone age in children with overweight and obesity. METHODS: In total 23,305 children from Beijing were included in this cross-sectional study. Childhood overweight and obesity were defined according to the China and World Health Organization growth criteria. The data were analyzed by the R coding platform version 4.3.0. RESULTS: Under the Chinese criteria, 29%, 15%, and 4% of boys with overweight; 33%, 33%, and 3% of boys with obesity; 39%, 25%, and 2% of girls with overweight; and 37%, 42% and 1% of girls with obesity had advanced, significantly advanced and delayed BA, respectively. After adjustment, overweight (odds ratio, 95% confidence interval, P under the Chinese criteria: 2.52, 2.30-2.75, <0.001 and 4.54, 4.06-5.09, <0.001) and obesity (4.31, 3.85-4.82, <0.001 and 14.01, 12.39-15.85, <0.001) were risk factors for both advanced BA and significantly advanced BA. CONCLUSIONS: Different nutritional statuses lead to differences in children's BA development. Children with overweight and obesity have higher rates of advanced BA under two growth criteria, and girls have more advances in BA than boys do. Overweight and obesity are risk factors for advanced BA.

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Diet is an inseparable part of good health, from maintaining a healthy lifestyle for the general population to supporting the treatment of patients suffering from specific diseases. Therefore it is of great significance to be able to monitor people's dietary activity in their daily life remotely. While the traditional practices of self-reporting and retrospective analysis are often unreliable and prone to errors; sensor-based remote diet monitoring is therefore an appealing approach. In this work, we explore an atypical use of bio-impedance by leveraging its unique temporal signal patterns, which are caused by the dynamic close-loop circuit variation between a pair of electrodes due to the body-food interactions during dining activities. Specifically, we introduce iEat, a wearable impedance-sensing device for automatic dietary activity monitoring without the need for external instrumented devices such as smart utensils. By deploying a single impedance sensing channel with one electrode on each wrist, iEat can recognize food intake activities (e.g., cutting, putting food in the mouth with or without utensils, drinking, etc.) and food types from a defined category. The principle is that, at idle, iEat measures only the normal body impedance between the wrist-worn electrodes; while the subject is doing the food-intake activities, new paralleled circuits will be formed through the hand, mouth, utensils, and food, leading to consequential impedance variation. To quantitatively evaluate iEat in real-life settings, a food intake experiment was conducted in an everyday table-dining environment, including 40 meals performed by ten volunteers. With a lightweight, user-independent neural network model, iEat could detect four food intake-related activities with a macro F1 score of 86.4% and classify seven types of foods with a macro F1 score of 64.2%.

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Direct dehydrogenation of carboxylic acids to their unsaturated counterparts represents a valuable transformation for complex molecule synthesis, which, however, has been challenging to achieve. In addition, the current carbonyl desaturation methods are almost all based on oxidative conditions. Here we report an Ir-catalyzed redox-neutral transfer dehydrogenation approach to directly convert carboxylic acids to either α,ß- or ß,γ-unsaturated counterparts. These reactions avoid using oxidants or strong bases, thus, tolerating various functional groups. The combined experimental and computational mechanistic studies suggest that this transfer hydrogenation reaction involves directed C-H oxidative addition, ß-H elimination, and dihydride transfer to an alkene acceptor with C(sp3)-H reductive elimination as the turnover-limiting step.

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The structural composition of reduced graphene oxide (rGO) can be modified and controlled by appropriate reduction methods to modulate its electronic structure, rendering it a versatile platform for tailoring optoelectronic and catalytic properties. Nevertheless, it is uncommon to concurrently amplify the photocatalytic and photothermal effects when regulating and utilizing pure rGO. Here, we investigate the impact of structural variations in thermally reduced graphene oxide (TGO) on its photocatalytic and photothermal properties. Various characterization results demonstrate that appropriate thermal reduction facilitates the preservation and transformation of oxygenated groups and structure defects, which in turn encourages the formation of reactive carbon radicals and discrete graphitic domains, thereby strengthening the activation of molecular oxygen and the plasmonic photothermal effect under near-infrared (NIR) light irradiation. Moreover, the optimized TGOs exhibit efficient sterilization with NIR irradiation due to enhanced photocatalytic activities and photothermal effects. This work highlights the potential for developing photocatalytic and photothermal rGO-based materials through structural engineering.

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BACKGROUND: Multiple studies have shown that Long COVID (LC) disease is associated with heightened immune activation, as evidenced by elevated levels of inflammatory mediators. However, there is no comprehensive meta-analysis focusing on activation of the immune inflammatory response system (IRS) and the compensatory immunoregulatory system (CIRS) along with other immune phenotypes in LC patients. OBJECTIVES: This meta-analysis is designed to explore the IRS and CIRS profiles in LC patients, the individual cytokines, chemokines, growth factors, along with C-reactive protein (CRP) and immune-associated neurotoxicity. METHODS: To gather relevant studies for our research, we conducted a thorough search using databases such as PubMed, Google Scholar, and SciFinder, covering all available literature up to July 5th, 2024. RESULTS: The current meta-analysis encompassed 103 studies that examined multiple immune profiles, C-reactive protein, and 58 cytokines/chemokines/growth factors in 5502 LC patients versus 5962 normal controls (NC). LC patients showed significant increases in IRS/CIRS ratio (standardized mean difference (SMD: 0.156, confidence interval (CI): 0.062;0.250), IRS (SMD: 0.338, CI: 0.236;0.440), M1 macrophage (SMD: 0.371, CI: 0.263;0.480), T helper (Th)1 (SMD: 0.316, CI: 0.185;0.446), Th17 (SMD: 0.439, CI: 0.302;0.577) and immune-associated neurotoxicity (SMD: 0.384, CI: 0.271;0.497). In addition, CRP and 21 different cytokines displayed significantly elevated levels in LC patients compared to NC. CONCLUSION: LC disease is characterized by IRS activation and increased immune-associated neurotoxicity.

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