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To improve detection efficiency and reduce cost consumption in fishery surveys, target detection methods based on computer vision have become a new method for fishery resource surveys. However, the specialty and complexity of underwater photography result in low detection accuracy, limiting its use in fishery resource surveys. To solve these problems, this study proposed an accurate method named BSSFISH-YOLOv8 for fish detection in natural underwater environments. First, replacing the original convolutional module with the SPD-Conv module allows the model to lose less fine-grained information. Next, the backbone network is supplemented with a dynamic sparse attention technique, BiFormer, which enhances the model's attention to crucial information in the input features while also optimizing detection efficiency. Finally, adding a 160 × 160 small target detection layer (STDL) improves sensitivity for smaller targets. The model scored 88.3% and 58.3% in the two indicators of mAP@50 and mAP@50:95, respectively, which is 2.0% and 3.3% higher than the YOLOv8n model. The results of this research can be applied to fishery resource surveys, reducing measurement costs, improving detection efficiency, and bringing environmental and economic benefits.
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Aqueous Zn-metal batteries have attracted increasing interest for large-scale energy storage owing to their outstanding merits in terms of safety, cost and production. However, they constantly suffer from inadequate energy density and poor cycling stability due to the presence of zinc ions in the fully hydrated solvation state. Thus, designing the dehydrated solvation structure of zinc ions can effectively address the current drawbacks of aqueous Zn-metal batteries. In this case, considering the lack of studies focused on strategies for the dehydration of zinc ions, herein, we present a systematic and comprehensive review to deepen the understanding of zinc-ion solvation regulation. Two fundamental design principles of component regulation and pre-desolvation are summarized in terms of solvation environment formation and interfacial desolvation behavior. Subsequently, specific strategy based distinct principles are carefully discussed, including preparation methods, working mechanisms, analysis approaches and performance improvements. Finally, we present a general summary of the issues addressed using zinc-ion dehydration strategies, and four critical aspects to promote zinc-ion solvation regulation are presented as an outlook, involving updating (de)solvation theories, revealing interfacial evolution, enhancing analysis techniques and developing functional materials. We believe that this review will not only stimulate more creativity in optimizing aqueous electrolytes but also provide valuable insights into designing other battery systems.
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Liposomes (LIP) loaded with natural active ingredients have significant potential in the food industry. However, their low loading efficiency (LE) hampers the advancement of liposomal products. To improve the loading capacity of functional compounds, bionic oleosomes (BOLE) with a monolayer of phospholipid membranes and a glyceryl tricaprylate/caprate (GTCC) oil core have first been engineered by high-pressure homogenization. TEM revealed that the core of BOLE consists of GTCC instead of water, thereby extending the hydrophobic space. Steady-state fluorescence and active loading experiments confirmed that cholesterol (CH) detached from the phospholipid membrane and entered the oil core, where it repelled cannabidiol (CBD). Based on the extending hydrophobic space, CBD-BOLE was prepared and its LE was 3.13 times higher than CBD-LIP. The CBD-phospholipid ratio (CPR) of CBD-BOLE significantly improved at least 7.8 times. Meanwhile, the free radical scavenging activity of CBD was increased and cytotoxicity was reduced.
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Colesterol , Interacciones Hidrofóbicas e Hidrofílicas , Liposomas , Liposomas/química , Colesterol/química , Fosfolípidos/química , Humanos , Cannabidiol/química , Cannabidiol/farmacología , Tamaño de la PartículaRESUMEN
Transition metal single-atom catalysts (SACs) have been regarded as possible alternatives to platinum-based materials due to their satisfactory performance of the oxygen reduction reaction (ORR). By contrast, main-group metal elements are rarely studied due to their unfavorable surface and electronic states. Herein, a main-group Sn-based SAC with penta-coordinated and asymmetric first-shell ligands is reported as an efficient and robust ORR catalyst. The introduction of the vertical oxygen atom breaks the symmetric charge balance, modulating the binding strength to oxygen intermediates and decreasing the energy barrier for the ORR process. As expected, the prepared Sn SAC exhibits outstanding ORR activity with a high half-wave potential of 0.912 V (vs RHE) and an excellent mass activity of 13.1 A mgSn-1 at 0.850 V (vs RHE), which surpasses that of commercial Pt/C and most reported transition-metal-based SACs. Additionally, the reported Sn SAC shows excellent ORR stability due to the strong interaction between Sn sites and the carbon support with oxygen atom as the bridge. The excellent ORR performance of Sn SAC was also proven by both liquid- and solid-state zinc-air battery (ZAB) measurements, indicating its great potential in practical applications.
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Non-coding RNAs (ncRNAs) are recognized as pivotal players in the regulation of essential physiological processes such as nutrient homeostasis, development, and stress responses in plants. Common methods for predicting ncRNAs are susceptible to significant effects of experimental conditions and computational methods, resulting in the need for significant investment of time and resources. Therefore, we constructed an ncRNA predictor(MFPINC), to predict potential ncRNA in plants which is based on the PINC tool proposed by our previous studies. Specifically, sequence features were carefully refined using variance thresholding and F-test methods, while deep features were extracted and feature fusion were performed by applying the GRU model. The comprehensive evaluation of multiple standard datasets shows that MFPINC not only achieves more comprehensive and accurate identification of gene sequences, but also significantly improves the expressive and generalization performance of the model, and MFPINC significantly outperforms the existing competing methods in ncRNA identification. In addition, it is worth mentioning that our tool can also be found on Github ( https://github.com/Zhenj-Nie/MFPINC ) the data and source code can also be downloaded for free.
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Biología Computacional , ARN de Planta , ARN no Traducido , ARN no Traducido/genética , ARN de Planta/genética , Biología Computacional/métodos , Programas Informáticos , Plantas/genética , Algoritmos , Análisis de Secuencia de ARN/métodosRESUMEN
All-solid-state lithium batteries (ASSBs) have received increasing attentions as one promising candidate for the next-generation energy storage devices. Among various solid electrolytes, sulfide-based ASSBs combined with layered oxide cathodes have emerged due to the high energy density and safety performance, even at high-voltage conditions. However, the interface compatibility issues remain to be solved at the interface between the oxide cathode and sulfide electrolyte. To circumvent this issue, we propose a simple but effective approach to magic the adverse surface alkali into a uniform oxyhalide coating on LiNi0.8Co0.1Mn0.1O2 (NCM811) via a controllable gas-solid reaction. Due to the enhancement of the close contact at interface, the ASSBs exhibit improved kinetic performance across a broad temperature range, especially at the freezing point. Besides, owing to the high-voltage tolerance of the protective layer, ASSBs demonstrate excellent cyclic stability under high cutoff voltages (500â cycles~94.0 % at 4.5â V, 200â cycles~80.4 % at 4.8â V). This work provides insights into using a high voltage stable oxyhalide coating strategy to enhance the development of high energy density ASSBs.
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The utilization of anionic redox chemistry provides an opportunity to further improve the energy density of Li-ion batteries, particularly for Li-rich layered oxides. However, oxygen-based hosts still suffer from unfavorable structural rearrangement, including the oxygen release and transition metal (TM)-ion migration, in association with the tenuous framework rooted in the ionicity of the TM-O bonding. An intrinsic solution, by using a sulfur-based host with strong TM-S covalency, is proposed here to buffer the lattice distortion upon the highly activating sulfur redox process, and it achieves howling success in stabilizing the host frameworks. Experimental results demonstrate the prolonged preservation of the layered sulfur lattice, especially the honeycomb superlattice, during the Li+ extraction/insertion process in contrast to the large structural degeneration in Li-rich oxides. Moreover, the Li-rich sulfide cathodes exhibited a negligible overpotential of 0.08 V and a voltage drop of 0.13 mV/cycle, while maintaining a substantial reversible capacity upon cycling. These superior electrochemical performances can be unambiguously ascribed to the much shorter trajectories of sulfur in comparison to those of oxygen revealed by molecular dynamics simulations at a large scale (â¼30 nm) and a long time scale (â¼300 ps) via high-dimensional neural network potentials during the delithiation process. Our findings highlight the importance of stabilizing host frameworks and establish general guidance for designing Li-rich cathodes with durable anionic redox chemistry.
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BACKGROUND: More and more studies show that miRNA plays a crucial role in plants' response to different abiotic stresses. However, traditional experimental methods are often expensive and inefficient, so it is important to develop efficient and economical computational methods. Although researchers have developed machine learning-based method, the information of miRNAs and abiotic stresses has not been fully exploited. Therefore, we propose a novel approach based on graph neural networks for predicting potential miRNA-abiotic stress associations. RESULTS: In this study, we fully considered the multi-source feature information from miRNAs and abiotic stresses, and calculated and integrated the similarity network of miRNA and abiotic stress from different feature perspectives using multiple similarity measures. Then, the above multi-source similarity network and association information between miRNAs and abiotic stresses are effectively fused through heterogeneous networks. Subsequently, the Restart Random Walk (RWR) algorithm is employed to extract global structural information from heterogeneous networks, providing feature vectors for miRNA and abiotic stress. After that, we utilized the graph autoencoder based on GIN (Graph Isomorphism Networks) to learn and reconstruct a miRNA-abiotic stress association matrix to obtain potential miRNA-abiotic stress associations. The experimental results show that our model is superior to all known methods in predicting potential miRNA-abiotic stress associations, and the AUPR and AUC metrics of our model achieve 98.24% and 97.43%, respectively, under five-fold cross-validation. CONCLUSIONS: The robustness and effectiveness of our proposed model position it as a valuable approach for advancing the field of miRNA-abiotic stress association prediction.
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BACKGROUND: Postoperative thirst is common in patients admitted to the intensive care unit. Existing methods like wet cotton swabs or oral care prove ineffectual or operationally intricate. Currently, an efficacious postoperative thirst alleviation method remains elusive. Exploring a prompt, safe, and efficacious solution is of paramount importance. OBJECTIVE: To assess the effect of ice-cold water spray applied following a symptom management model on postoperative thirst and to establish a framework for mitigating thirst in intensive care unit patients. RESEARCH DESIGN: Single-center randomized controlled study. SETTING: Surgical intensive care unit in a university-affiliated hospital. MAIN OUTCOME MEASURES: 56 intensive care unit patients were selected and equally randomized. The experimental group received ice-cold water spray in conjunction with eight symptom management strategies, while the control group underwent standard care involving wet cotton swabs. Thirst intervention was initiated 0.5 hours after postoperative extubation, followed by subsequent interventions at 2-hour, 4-hour, and 6-hour intervals post-extubation. Thirst intensity, oral comfort, and the duration of relief from thirst were assessed and compared between groups before and 0.5 hours after each thirst intervention. RESULTS: Across different interventions, the experimental group exhibited superior scores in thirst intensity and oral comfort compared to the control group. Additionally, the nursing time required to alleviate thirst in the experimental group was significantly shorter than that in the control group (P < 0.01). CONCLUSION: Ice-cold water spray following the model for symptom management can effectively mitigate the postoperative thirst intensity in intensive care unit patients, improve oral comfort, and reduce the nursing time for relieving thirst. IMPLICATIONS FOR CLINICAL PRACTICE: Clinical nurses can employ ice-cold water spray following the model for symptom management to ameliorate postoperative thirst intensity in ICU patients while enhancing oral comfort. Furthermore, the utilization of ice-cold water spray can reduce the nursing time required for relieving postoperative thirst in intensive care unit patients.
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Sed , Agua , Humanos , Cuidados Críticos/métodos , Unidades de Cuidados IntensivosRESUMEN
The precise identification of associations between diseases and drugs is paramount for comprehending the etiology and mechanisms underlying parasitic diseases. Computational approaches are highly effective in discovering and predicting disease-drug associations. However, the majority of these approaches primarily rely on link-based methodologies within distinct biomedical bipartite networks. In this study, we reorganized a fundamental dataset of parasitic disease-drug associations using the latest databases, and proposed a prediction model called PDDGCN, based on a multi-view graph convolutional network. To begin with, we fused similarity networks with binary networks to establish multi-view heterogeneous networks. We utilized neighborhood information aggregation layers to refine node embeddings within each view of the multi-view heterogeneous networks, leveraging inter- and intra-domain message passing to aggregate information from neighboring nodes. Subsequently, we integrated multiple embeddings from each view and fed them into the ultimate discriminator. The experimental results demonstrate that PDDGCN outperforms five state-of-the-art methods and four compared machine learning algorithms. Additionally, case studies have substantiated the effectiveness of PDDGCN in identifying associations between parasitic diseases and drugs. In summary, the PDDGCN model has the potential to facilitate the discovery of potential treatments for parasitic diseases and advance our comprehension of the etiology in this field. The source code is available at https://github.com/AhauBioinformatics/PDDGCN .
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Enfermedades Parasitarias , Humanos , Algoritmos , Bases de Datos Factuales , Aprendizaje Automático , Programas InformáticosRESUMEN
Glucose oxidase (GOD) is widely used in the pharmaceutical industry, fermentation products and glucose biosensors for its essential role in catalyzing the conversion of glucose to gluconic acid and hydrogen peroxide (H2O2). As H2O2 is the by-product and will have a toxic effect on glucose oxidase, so introducing another enzyme that could consume H2O2 to form an enzymatic cascade reaction is a practical solution. However, this decision will lead to extra expenses and complex condition optimization such as the specific mass ratio, temperature and pH to improve the activity, stability and recyclability. Herein, we describe a mild and versatile strategy by anchoring GOD on carboxyl-activated MOF (Cu-TCPP(Fe)) through DNA-directed immobilization (DDI) technology. Robust MOF nanosheets were utilized as not only the carrier for the immobilization of GOD, but also a peroxidase-like catalyst for the decomposition of H2O2 to reduce its harmful impacts. In this work, the immobilized GOD retained 55.78% of its initial activity after being used for 7 times. More than 60% of the immobilized enzyme's catalytic activity was still maintained after 96 h of being stored at 50 â. This study provides a new idea for preparing immobilized enzymes with enhanced stability, fast diffusion and high activity, which can be used in fields such as biocatalysis and biotechnology.
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Glucosa Oxidasa , Glucosa , Peróxido de Hidrógeno , Enzimas Inmovilizadas/química , CatálisisRESUMEN
Layered oxides are widely accepted to be promising cathode candidate materials for K-ion batteries (KIBs) in terms of their rich raw materials and low price, while their further applications are restricted by sluggish kinetics and poor structural stability. Here, the high-entropy design concept is introduced into layered KIB cathodes to address the above issues, and an example of high-entropy layered K0.45Mn0.60Ni0.075Fe0.075Co0.075Ti0.10Cu0.05Mg0.025O2 (HE-KMO) is successfully prepared. Benefiting from the high-entropy oxide with multielement doping, the developed HE-KMO exhibits half-metallic oxide features with a narrow bandgap of 0.19 eV. Increased entropy can also reduce the surface energy of the {010} active facets, resulting in about 2.6 times more exposure of the {010} active facets of HE-KMO than the low-entropy K0.45MnO2 (KMO). Both can effectively improve the kinetics in terms of electron conduction and K+ diffusion. Furthermore, high entropy can inhibit space charge ordering during K+ (de)insertion, and the transition metal-oxygen covalent interaction of HE-KMO is also enhanced, leading to suppressed phase transition of HE-KMO in 1.5-4.2 V and better electrochemical stability of HE-KMO (average capacity drop of 0.20%, 200 cycles) than the low-entropy KMO (average capacity drop of 0.41%, 200 cycles) in the wide voltage window.
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All-solid-state batteries (ASSBs) represent a promising battery strategy to achieve high energy density with great safety. However, inadequate kinetic property and poor interfacial compatibility remain great challenges, which impede their practical application. A prototype of dual-ion conductor of Li+ synchronized with Cu+ unlocks a four-electron redox reaction with high reversibility and fast kinetics. As a result, the constructed ASSB exhibited a high reversible capacity of 603.0 mA·hour g-1 and an excellent cycling retention of 93.2% over 1500 cycles. Moreover, because of the ion highway connecting active materials and catholytes constructed by dual-ion conductor, remarkable temperature tolerance (-60°C) and excellent rate performance (231.6 mA·hour g-1 at 20 mA cm-2) were achieved. The superior electrochemical performance can be ascribed to the migration pathway with small energy barrier and low tortuosity once the Cu+ introduced into Li6PS5Cl. This work creates a unique perspective of ASSBs with dual-ion conducting strategy, thus inspiring a potential developing strategy of state-of-the-art ASSBs.
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Phase-shifting profilometry is extensively utilized for three-dimensional (3D) measurement. However, because of gamma nonlinearity, the image intensities of the captured fringe patterns are regrettably distorted. An effective nonlinear error reduction method without requiring parameter estimation is presented in this paper. Differing from the traditional whole-period phase histogram equalization (PHE) method, our method takes into account not only the periodicity but also the symmetry of the phase histogram. Taking a three-step phase-shifting algorithm as an example, the phase error frequency triples the fringe frequency; thus, we first propose a 1/3-period PHE method. Moreover, since the phase error distribution is sinusoidal with symmetry, we further propose a 1/6-period PHE method. Simulations and experiments both indicate that the 1/6-period PHE method, compared with the whole-period PHE and 1/3-period PHE methods, can further reduce the nonlinear error.
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Li-O2 battery (LOB) is a promising "beyond Li-ion" technology with ultrahigh theoretical energy density (3457â Wh kg-1 ), while currently impeded by the sluggish cathodic kinetics of the reversible gas-solid reaction between O2 and Li2 O2 . Despite many catalysts are developed for accelerating the conversion process, the lack of design guidance for achieving high performance makes catalysts exploring aleatory. The Sabatier principle is an acknowledged theory connecting the scaling relationship with heterogeneous catalytic activity, providing a tradeoff strategy for the topmost performance. Herein, a series of catalysts with wide-distributed d-band centers (i.e., wide range of adsorption strength) are elaborately constructed via high-entropy strategy, enabling an in-depth study of the Sabatier relations in electrocatalysts for LOBs. A volcano-type correlation of d-band center and catalytic activity emerges. Both theoretical and experimental results indicate that a moderate d-band center with appropriate adsorption strength propels the catalysts up to the top. As a demonstration of concept, the LOB using FeCoNiMnPtIr as catalyst provides an exceptional energy conversion efficiency of over 80 %, and works steadily for 2000â h with a high fixed specific capacity of 4000â mAh g-1 . This work certifies the applicability of Sabatier principle as a guidance for designing advanced heterogeneous catalysts assembled in LOBs.
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OBJECTIVE: Previous studies have highlighted the poor survival of patients with cutaneous angiosarcoma of the head and neck. Therapeutic options are limited, and effective treatment strategies are yet to be discovered. The objective of this study is to evaluate overall survival following intensified adjuvant treatment for high-risk resected angiosarcoma of the head and neck. STUDY DESIGN: Retrospective observational. SETTING: National Cancer Database (NCDB). METHODS: Patients diagnosed with nonmetastatic cutaneous angiosarcoma of the head and neck from 2004 to 2016 were identified by NCDB. We retrospectively compared demographics and overall survival between patients who received surgery and radiation therapy (SR) and patients who received surgery and chemoradiation (SRC). The χ2 test, Kaplan-Meier method, and Cox regression models were used to analyze data. RESULTS: A total of 249 patients were identified, of which 79.5% were treated with surgery and radiation alone and 20.5% were treated with surgery and chemoradiation. The addition of chemotherapy, regardless of the sequence of administration, was not associated with significantly higher overall survival. Factors associated with worse survival in both groups included positive nodal status and positive margins. Patients with positive nodes had higher overall survival with radiation doses >50.4 Gy compared to ≤50.4 Gy (hazard ratio: 2.93, confidence interval: 1.60-5.36, p < 0.001). CONCLUSION: Adjuvant chemotherapy was not significantly associated with higher overall survival for resected nonmetastatic angiosarcoma of the head and neck. Higher radiation doses appear to be prognostic for high-risk diseases.
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Neoplasias de Cabeza y Cuello , Hemangiosarcoma , Neoplasias Cutáneas , Humanos , Estudios Retrospectivos , Hemangiosarcoma/cirugía , Neoplasias de Cabeza y Cuello/cirugía , Neoplasias Cutáneas/cirugía , Resultado del Tratamiento , Radioterapia AdyuvanteRESUMEN
The multienzyme co-immobilization systems with high cascade catalytic efficiency and selectivity have attracted considerable attention. In this study, through DNA-directed immobilization (DDI) technology, two model enzymes, glucose oxidase (GOD) and horseradish peroxide (HRP) were co-immobilized on the multifunctional silica nanoparticles (DDI enzyme). In addition to the directional distribution promoted by DNA complementary chains, the multienzyme system allowed the control of the stoichiometric ratio of the enzymes by adjusting the ratio of amino/carboxyl groups. The optimal mole ratio of GOD/HRP was 1:2, while the protein loading amount could reach 8.06 mg·g-1. Compared with the conventional direct adsorption, the catalytic activity of the DDI enzyme was 2.49 times higher. Moreover, with the enhancement of thermal and mechanical stability, the DDI enzyme could still retain at least 50% of its initial activity after 12 cycles. Accompanied by an excellent response and good selectivity, the constructed multienzyme systems simultaneously showed the potential as a glucose detector. Therefore, based on the DDI technology, the highly efficient multienzyme co-immobilization system could be further extended for a wider range of research fields.
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Enzimas Inmovilizadas , Nanopartículas , Enzimas Inmovilizadas/metabolismo , Glucosa , Glucosa Oxidasa/metabolismo , Peroxidasa de Rábano Silvestre/metabolismo , ADNRESUMEN
INTRODUCTION: We aimed to characterize the clinicopathological characteristics and outcomes of HIV-positive patients with clinically localized, prostate cancer (PCa). METHODS: A retrospective study was conducted of HIV-positive patients from a single institution with elevated PSA and diagnosis of PCa by biopsy. PCa features, HIV characteristics, treatment type, toxicities, and outcomes were analyzed by descriptive statistics. Kaplan-Meier analysis was used to determine progression-free survival (PFS). RESULTS: Seventy-nine HIV-positive patients were included with a median age at PCa diagnosis of 61 years-old and median duration from HIV infection to PCa diagnosis of 21 years. The median PSA level at diagnosis and Gleason Score was 6.85 ng/mL and 7, respectively. The 5-year PFS was 82.5% with the lowest survival observed in patients treated with radical prostatectomy (RP) + radiation therapy (RT), followed by cryosurgery (CS). There were no reports of PCa-specific deaths, and the 5-year overall survival was 97.5%. CD4 count declined post-treatment in pooled treatment groups that included RT (P = .02). CONCLUSION: We present the characteristics and outcomes of the largest cohort of HIV-positive men with prostate cancer in published literature. RP and RT ± ADT is well-tolerated in HIV-positive patients with PCa as seen by the adequate biochemical control and mild toxicity. CS resulted in worse PFS compared to alternative treatments for patients within the same PCa risk group. A decline in CD4 counts was observed in patients treated RT, and further studies are needed to investigate this relationship. Our findings support the use of standard-of-care treatment for localized PCa in HIV-positive patients.