RESUMO

CD2-associated protein (CD2AP) is a scaffolding/adaptive protein that regulates intercellular adhesion and multiple signaling pathways. Although emerging evidence suggests that CD2AP is associated with several malignant tumors, there is no study investigating the expression and biological significance of CD2AP in glioblastoma multiforme (GBM). Here by studying public datasets, we found that CD2AP expression was significantly elevated in GBM and that glioma patients with increased CD2AP expression had a worse prognosis. We also confirmed the increase of CD2AP expression in clinical GBM samples and GBM cell lines. CD2AP overexpression in GBM cells promoted their proliferation, colony formation, migration, and invasion in vitro and their tumorigenesis in vivo, and reduced cell apoptosis both at basal levels and in response to temozolomide. While CD2AP knockdown had the opposite effects. Mechanistically, we revealed that CD2AP interacted with TRIM5, an NF-κB modulator. CD2AP overexpression and knockdown increased and decreased TRIM5 levels as well as the NF-κB activity, respectively. Moreover, downregulation of TRIM5 reversed elevated NF-κB activity in GBM cells with CD2AP overexpression; and inhibition of the NF-κB activity attenuated malignant features of GBM cells with CD2AP overexpression. Our findings demonstrate that CD2AP promotes GBM progression through activating TRIM5-mediated NF-κB signaling and that downregulation of CD2AP can attenuate GBM malignancy, suggesting that CD2AP may become a biomarker and the CD2AP-TRIM5-NF-κB axis may become a therapeutic target for GBM.

Assuntos

Proteínas Adaptadoras de Transdução de Sinal , Glioblastoma , NF-kappa B , Transdução de Sinais , Glioblastoma/patologia , Glioblastoma/metabolismo , Glioblastoma/genética , Humanos , NF-kappa B/metabolismo , Animais , Linhagem Celular Tumoral , Proteínas Adaptadoras de Transdução de Sinal/metabolismo , Proteínas Adaptadoras de Transdução de Sinal/genética , Progressão da Doença , Proliferação de Células , Neoplasias Encefálicas/patologia , Neoplasias Encefálicas/metabolismo , Neoplasias Encefálicas/genética , Camundongos , Camundongos Nus , Movimento Celular , Regulação Neoplásica da Expressão Gênica , Proteínas com Motivo Tripartido/metabolismo , Proteínas com Motivo Tripartido/genética , Apoptose , Masculino , Feminino , Proteínas do Citoesqueleto

RESUMO

Soup is an important presence in diet, but its absorption and transport mechanism by the human body remains unclear. In this study, Caco-2 intact cell and monolayer cell models were constructed to simulate small intestine absorption on colloidal nanoparticles (CNPs) isolated from lamb soup. The intracellular localization of CNPs was viewed by laser confocal microscopy (LSCM). CNPs uptake and release pathways were explored by differences in CNPs concentrations in 5 endocytosis inhibitor models and 4 exocytosis inhibitor models. Results indicated that CNPs endocytosis by Caco-2 cells was restrained by Nystatin and Cytochalasin D, with exocytosis being inhibited by Nocodazole and Monensin. Therefore, the major absorption pathways for CNPs were caveolin-dependent endocytosis, macropinocytosis and phagocytosis. The major transport pathways were microtubule-vesicle-mediated protein transport to the membrane and transportation between the Golgi apparatus and membrane. This study may provide theoretical support for the transport mechanism of soup products in the small intestine.

RESUMO

With the wave of artificial intelligence sweeping the world in recent years, UAVs is widely used in various fields. UAV path planning has attracted much attention from scientists as an essential part of UAV work. In order to design an efficient and reasonable 3D UAV path planning program, recent researchers have invented and improved many algorithms. This paper proposes an elite RIME algorithm for 3D UAV path planning. First, we propose an elite reverse learning population selection strategy based on piecewise mapping to enhance the population diversity of the algorithm for better exploration. Second, this paper proposes a stochastic factor-controlled elite pool exploration strategy so that the algorithm is difficult to enter the local optimum and can better explore the global optimum. Then, this paper proposes a hard frost puncture exploitation strategy based on the sine-cosine function so that the algorithm can find the global optimum faster during the exploitation process. Meanwhile, in order to test the performance of the algorithm proposed in this paper, we compare it with 13 other intelligent optimization algorithms that are classical and popular nowadays on 52 test functions in three test sets, CEC2017, CEC2020, and CEC2022, and obtain competitive results. Finally, we applied it to the 3D UAV path planning problem in three different terrain scenarios, and the ELRIME algorithm achieved good results in all of them. Especially in the 7-peak model, the ELRIME algorithm improves the performance of the RIME algorithm by a factor of two. In the 9-peak model, the average value aspect also reduce the cost by 91 compared to the RIME algorithm, and more importantly, it has the smallest fluctuation in 30 runs, which is among the most stable of all the compared algorithms. In the 12-peak model, its stability is also significantly enhanced, and in terms of worst-case cost, it improves the cost by 340 compared to RIME.

RESUMO

The rice albumin (RAG) gene family belongs to the Tryp_alpha_amyl family. RAG2, specifically expressed in 14-21 DAP (days after pollination) seeds, regulates grain yield and quality. In this study, we identified another RAG family gene, RAL6, which exhibits specific expression in developing seeds, particularly in 7, 10, and 15 DAP seeds. Employing the CRISPR/Cas9 system, we analyzed functions of RAL6 and found that the ral6 lines (ral6-1, ral6-2, ral6-3, and ral6-4) displayed thinner seeds with significantly decreased 1000-grain weight and grain thickness compared to ZH11. Additionally, the cell width of spikelet cells, total protein and glutelin contents were significantly reduced in ral6. The germination assay and 1% TTC staining revealed a significant decrease in seed vigor among the ral6 lines. The alpha-amylase activity in ral6 mutant seeds was also markedly lower than in ZH11 seeds after 2 days of imbibition. Furthermore, co-expression analysis and GO annotation showed that co-expressed genes were involved in immune response, oligopeptide transport, and the glucan biosynthetic process. Collectively, our findings suggest that RAL6 plays a coordinating role in regulating grain weight and seed germination in rice.

RESUMO

Humans have the ability to constantly learn new knowledge. However, for artificial intelligence, trying to continuously learn new knowledge usually results in catastrophic forgetting, the existing regularization-based and dynamic structure-based approaches have shown great potential for alleviating. Nevertheless, these approaches have certain limitations. They usually do not fully consider the problem of incompatible feature embeddings. Instead, they tend to focus only on the features of new or previous classes and fail to comprehensively consider the entire model. Therefore, we propose a two-stage learning paradigm to solve feature embedding incompatibility problems. Specifically, we retain the previous model and freeze all its parameters in the first stage while dynamically expanding a new module to alleviate feature embedding incompatibility questions. In the second stage, a fusion knowledge distillation approach is used to compress the redundant feature dimensions. Moreover, we propose weight pruning and consolidation approaches to improve the efficiency of the model. Our experimental results obtained on the CIFAR-100, ImageNet-100 and ImageNet-1000 benchmark datasets show that the proposed approaches achieve the best performance among all the compared approaches. For example, on the ImageNet-100 dataset, the maximal accuracy improvement is 5.08%. Code is available at https://github.com/ybyangjing/CIL-FCE.

RESUMO

Effect of part differences on metabolite molecule alterations in refrigerated pork was investigated. A metabolomics methodology combined with chemometric analysis was successfully established to identify key compounds and their conversion pathways, including precursors and volatile metabolites, in the Longissimus lumborum as well as the breast and flank stored for 11 days. In total, 12 discriminative precursors were identified using the Short Time-series Expression Miner. In tandem with Random Forest and ANOVA analyses, nine volatile metabolites were identified as key compounds that could be attributed to differences in pork sections. Bidirectional orthogonal partial least squares analysis revealed a potential correlation between these key metabolites and discriminative precursors. Metabolic pathway enrichment analysis demonstrated that the primary metabolic process affected by variations in pork sections is linoleic acid metabolism, which participates in the metabolism of cysteine and glutamic acid to produce methoxy-phenyl-oxime. This study provides valuable insights into the identification of differential metabolites.

Assuntos

Metabolômica , Animais , Suínos , Refrigeração , Compostos Orgânicos Voláteis/metabolismo , Compostos Orgânicos Voláteis/química , Músculo Esquelético/metabolismo , Músculo Esquelético/química , Carne/análise , Armazenamento de Alimentos , Redes e Vias Metabólicas

RESUMO

Alterations in microbiotas and endogenous enzymes have been implicated in meat deterioration. However, the factors that mediate the interactions between meat quality and microbiome profile were inadequately investigated. In this study, we collected pork samples throughout the refrigeration period and employed metaproteomics to characterize both the pork and microbial proteins. Our findings demonstrated that pork proteins associated with the catabolic process are upregulated during storage compared to the initial stage. Pseudomonas, Clostridium, Goodfellowiella, and Gonapodya contribute to the spoilage process. Notably, we observed an elevated abundance of microbial proteins related to glycolytic enzymes in refrigerated pork, identifying numerous proteins linked to biogenic amine production, thus highlighting their essential role in microbial decay. Further, we reveal that many of these microbial proteins from Pseudomonas are ribosomal proteins, promoting enzyme synthesis by enhancing transcription and translation. This study provides intrinsic insights into the underlying mechanisms by which microorganisms contribute to meat spoilage.

Assuntos

Bactérias , Proteínas de Bactérias , Armazenamento de Alimentos , Proteômica , Refrigeração , Animais , Suínos , Bactérias/classificação , Bactérias/metabolismo , Bactérias/isolamento & purificação , Bactérias/genética , Proteínas de Bactérias/metabolismo , Proteínas de Bactérias/análise , Proteínas de Bactérias/genética , Microbiota

RESUMO

The real-time, precise qualitative and quantitative sensing of food flavor compounds is crucial for ensuring food safety, quality, and consumer acceptance. As indicators for food flavor labeling, it is vital to delve deep into the specific ingredient and content of food flavor compounds to assess the food flavor quality, but still facing huge challenges. Photoluminescent fluorescent probe technology, with fast detection and high sensitivity, has shown immense potentials in detecting food flavor compounds. In this review, the classification and optical sensing mechanism of photoluminescent fluorescent probe technology are described in detail. Besides, challenges in applying photoluminescent fluorescent probe technology to analyze food flavor compounds are outlined to indicate future research directions. We hope this review can provide an insight for the applications of photoluminescent fluorescent probe technology in the evaluation of food flavor quality in future.

Assuntos

Aromatizantes , Corantes Fluorescentes , Análise de Alimentos , Corantes Fluorescentes/química , Aromatizantes/química , Aromatizantes/análise , Paladar , Humanos

RESUMO

Membrane proteins are considered the major source of drug targets and are indispensable for drug design and disease prevention. However, traditional biomechanical experiments are costly and time-consuming; thus, many computational methods for predicting membrane protein types are gaining popularity. The position-specific scoring matrix (PSSM) method is an excellent method for describing the evolutionary information of protein sequences. In this study, we propose an improved capsule neural network (ICNN) model based on a capsule neural network to acquire sufficient relevant information from the PSSM. Furthermore, accounting for the complementarity between traditional machine learning and deep learning, we propose a hybrid framework that combines both approaches to predict protein types. This framework trains 41 baseline models based on the PSSM. The optimal subset features, selected after traversal, are fused using a two-level decision-level feature fusion approach. Subsequently, comparisons are made using three combined strategies within an ensemble learning framework. The experimental results demonstrate that solely relying on PSSM input, the proposed method not only surpasses the optimal methods by 1.52 % , 2.26 % and 2.67 % on Dataset1, Dataset2, and Datasets3, respectively, but also exhibits superior generalizability. Furthermore, the code and dataset can be free download at https://github.com/ruanxiaoli/membrane-protein-types .

Assuntos

Biologia Computacional , Proteínas de Membrana , Redes Neurais de Computação , Matrizes de Pontuação de Posição Específica , Proteínas de Membrana/química , Biologia Computacional/métodos , Aprendizado de Máquina , Aprendizado Profundo , Bases de Dados de Proteínas , Humanos , Algoritmos

RESUMO

Server load levels affect the performance of cloud task execution, which is rooted in the impact of server performance on cloud task execution. Traditional cloud task scheduling methods usually only consider server load without fully considering the server's real-time load-performance mapping relationship, resulting in the inability to evaluate the server's real-time processing capability accurately. This deficiency directly affects the efficiency, performance, and user experience of cloud task scheduling. Firstly, we construct a performance platform model to monitor server real-time load and performance status information in response to the above problems. In addition, we propose a new deep reinforcement learning task scheduling method based on server real-time performance (SRP-DRL). This method introduces a real-time performance-aware strategy and adds status information about the real-time impact of task load on server performance on top of considering server load. It enhances the perception capability of the deep reinforcement learning (DRL) model in cloud scheduling environments and improves the server's load-balancing ability under latency constraints. Experimental results indicate that the SRP-DRL method has better overall performance regarding task average response time, success rate, and server average load variance compared to Random, Round-Robin, Earliest Idle Time First (EITF), and Best Fit (BEST-FIT) task scheduling methods. In particular, the SRP-DRL is highly effective in reducing server average load variance when numerous tasks arrive within a unit of time, ultimately optimizing the performance of the cloud system.

RESUMO

It is essential and still remains a big challenge to obtain fast-charge anodes with large capacities and long lifespans for Li-ion batteries (LIBs). Among all of the alternative materials, molybdenum trioxide shows the advantages of large theoretical specific capacity, distinct tunnel framework, and low cost. However, there are also some key shortcomings, such as fast capacity decaying due to structural instability during Li insertion and poor rate performance due to low intrinsic electron conductivity and ion diffusion capability, dying to be overcome. A unique strategy is proposed to prepare Ti-h-MoO3-x@TiO2 nanosheets by a one-step hydrothermal approach with NiTi alloy as a control reagent. The density functional theory (DFT) calculations indicate that the doping of Ti element can make the hexagonal h-MoO3-x material show the best electronic structure and it is favor to be synthesized. Furthermore, the hexagonal Ti-h-MoO3-x material has better lithium storage capacity and lithium diffusion capacity than the orthogonal α-MoO3 material, and its theoretical capacity is more than 50% higher than that of the orthogonal α-MoO3 material. Additionally, it is found that Ti-h-MoO3-x@TiO2 as an anode displays extremely high reversible discharge/charge capacities of 1326.8/1321.3 mAh g-1 at 1 A g-1 for 800 cycles and 611.2/606.6 mAh g-1 at 5 A g-1 for 2000 cycles. Thus, Ti-h-MoO3-x@TiO2 can be considered a high-power-density and high-energy-density anode material with excellent stability for LIBs.

RESUMO

Nanobactericides are employed as a promising class of nanomaterials for eradicating microbial infections, considering the rapid resistance risks of conventional antibiotics. Herein, we present a pioneering approach, reporting the synthesis of two-dimensional titanium disulfide nanosheets coated by nitrogen/sulfur-codoped carbon nanosheets (2D-TiS2@NSCLAA hybrid NSs) using a rapid l-ascorbic acid-assisted sulfurization of Ti3C2Tx-MXene to achieve efficient alternative bactericides. The as-developed materials were systematically characterized using a suite of different spectroscopy and microscopy techniques, in which the X-ray diffraction/Raman spectroscopy/X-ray photoelectron spectroscopy data confirm the existence of TiS2 and C, while the morphological investigation reveals single- to few-layered TiS2 NSs confined by N,S-doped C, suggesting the successful synthesis of the ultrathin hybrid NSs. From in vitro evaluation, the resultant product demonstrates impressive bactericidal potential against both Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli bacteria, achieving a substantial decrease in the bacterial viability under a 1.2 J dose of visible-light irradiation at the lowest concentration of 5 µg·mL-1 compared to Ti3C2Tx (15 µg·mL-1), TiS2-C (10 µg·mL-1), and standard antibiotic ciprofloxacin (15 µg·mL-1), respectively. The enhanced degradation efficiency is attributed to the ultrathin TiS2 NSs encapsulated within heteroatom N,S-doped C, facilitating effective photogenerated charge-carrier separation that generates multiple reactive oxygen species (ROS) and induced physical stress as well as piercing action due to its ultrathin structure, resulting in multimechanistic cytotoxicity and damage to bacterial cells. Furthermore, the obtained results from molecular docking studies conducted via computational simulation (in silico) of the as-synthesized materials against selected proteins (ß-lactamasE. coli/DNA-GyrasE. coli) are well-consistent with the in vitro antibacterial results, providing strong and consistent validation. Thus, this sophisticated study presents a simple and effective synthesis technique for the structural engineering of metal sulfide-based hybrids as functionalized synthetic bactericides.

Assuntos

Antibacterianos , Carbono , Escherichia coli , Testes de Sensibilidade Microbiana , Nanoestruturas , Nitrogênio , Staphylococcus aureus , Titânio , Antibacterianos/farmacologia , Antibacterianos/química , Antibacterianos/síntese química , Titânio/química , Titânio/farmacologia , Escherichia coli/efeitos dos fármacos , Staphylococcus aureus/efeitos dos fármacos , Carbono/química , Carbono/farmacologia , Nanoestruturas/química , Nitrogênio/química , Enxofre/química , Enxofre/farmacologia , Luz

RESUMO

BACKGROUND: As a chronic metabolic disease, diabetes poses a serious threat to human health and has become a major public health problem in China and worldwide. In 2020, 30% of Chinese people (aged ≥ 60 years) reported having diabetes mellitus. Moreover, individuals with diabetes living in rural areas face a significantly higher mortality risk compared to those in urban areas. In this study, we explored the inner experience of self-management behaviors in elderly patients with type 2 diabetes in rural areas to inform targeted interventions. METHODS: A phenomenological research design was used to explore the inner experience of self-management in rural elderly diabetes. Ten elderly diabetic patients were sampled from December 2022 to March 2023 in rural areas of Yangcheng County, Jincheng City, ShanXi Province, China. The seven-step Colaizzi phenomenological was used to analyze the interview data and generate themes. RESULTS: Four themes emerged: "Insufficient self-management cognition", "Negative self-management attitude", "Slack self-management behavior", and "No time for self-management". CONCLUSION: The level of self-management among elderly patients with type 2 diabetes in rural areas is low. Healthcare professionals should develop targeted interventions aimed at enhancing their cognitive levels, modifying their coping styles, and improving their self-management abilities to improve their quality of life.

Assuntos

Diabetes Mellitus Tipo 2 , Pesquisa Qualitativa , População Rural , Autogestão , Humanos , Diabetes Mellitus Tipo 2/terapia , Diabetes Mellitus Tipo 2/psicologia , Idoso , Masculino , Feminino , Autogestão/psicologia , População Rural/estatística & dados numéricos , China/epidemiologia , Pessoa de Meia-Idade , Idoso de 80 Anos ou mais

RESUMO

Nickel-molybdenum-boron (Ni-Mo-B)-based catalysts with biphasic interfaces are highly advantageous in bifunctional electrocatalytic activity in alkaline water-splitting. However, it remains an ongoing challenge to obtain porous Ni-Mo alloy substrates that provide stable adhesion to catalysts, ensuring the long-term performance of bifunctional self-supporting electrodes at a high current density. Herein, a porous Ni-Mo alloy substrate was effectively obtained by a cost-effective dealloying process on a commercial Ni-Mo alloy with high-energy crystal planes. Subsequently, the Mo2NiB2/Ni3B bifunctional catalyst was in situ synthesized on this substrate via boriding heat treatment, resulting in outstanding catalytic activity and stability. Density functional theory (DFT) calculations reveal that the abundant biphasic interfaces and surface-reconstructed sites of the Mo2NiB2/Ni3B catalyst can decrease the energy barriers for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), respectively. Thus, the designed self-supporting electrodes show bifunctional catalytic activity with overpotentials of 151 mV for HER and 260 mV for OER at a current density of 10 mA cm-2. Markedly, the assembled water electrolyzer can be driven up to 10 mA cm-2 at 1.64 V and maintain catalytic activity at a high current density of 1000 mA cm-2 for 100 h. The new strategy is expected to provide a low-cost scheme for designing self-supporting bifunctional electrodes with high activity and excellent stability and contribute to the development of hydrogen energy technology.

RESUMO

Adenosine triphosphate (ATP) plays a vital role in physiological processes and is an essential indicator of microbial content in food. Herein, a new sensitive, rapid and water-soluble probe for ATP detection was developed. Rhodamine B and pentaethylenehexamine were employed to design and synthesise the probe rhodamine-pentaethylenehexamine (RP) for selective ATP detection. The synthesised probe RP was characterized using Fourier transform infrared, NMR and dynamic light scattering size distributions. Upon the addition of ATP, the probe exhibited a distinct change in fluorescence intensity, with fluorescence emission at 580 nm. A linear relationship was observed between fluorescence intensity and ATP concentrations at 0-50 µmol/L, with a limit of detection of 10.97 × 10-9 mol/L. The results of the zeta potential and molecular dynamics simulation demonstrated that the detection mechanism of the probe RP is associated with the electrostatic adsorption interaction between the multi-positively charged sites of RP and the negatively charged triphosphate structure of ATP. Our study provides new insights into improving charge site identification in small molecule detection. Furthermore, the successful detection of ATP on meat surfaces indicates that RP has the potential to assess meat freshness.

Assuntos

Trifosfato de Adenosina , Corantes Fluorescentes , Carne , Rodaminas , Trifosfato de Adenosina/análise , Trifosfato de Adenosina/química , Rodaminas/química , Corantes Fluorescentes/química , Animais , Carne/análise , Espectrometria de Fluorescência/métodos

RESUMO

BACKGROUND: To investigate the clinical distribution and changing trend of antibiotic resistance profiles of multidrug-resistant organisms (MDROs), a retrospective study was undertaken. METHODS: The characteristics of MDROs isolated from 2016 to March 2023 were retrospectively analysed. The detection rate of these MDROs was compared prior to COVID-19 (Period 1, 2016-2019), during the COVID-19 pandemic with restrictions (Period 2, 2020-2022), and after the end of zero-policy (Period 3, Jan-March, 2023). Antibiotic-resistant genes were detected. RESULTS: The overall detection rates of CRPA, CRAB, CREC, CRKP, MRSA, and VREfm were 22.6%, 22.6%, 1.3%, 4.0%, 19.5%, and 3.1%, respectively. The detection rate of CRAB was significantly lower in Period 2 and 3 compared with Period 1 (P < 0.0001). The detection rate of CRPA and VREfm was significantly increased in Period 3 compared with Period 1 and 2 (P < 0.0001). The resistance rate to ticarcillin/clavulanic acid (TIM) and piperacillin/tazobactam (TZP) has gradually increased in CRPA since 2018. NDM and KPC were the most common carbapenemase genes identified in CREC (60.0%) and CRKP isolates (47.8%), respectively. All the 10 VREfm isolates carried the vanA gene. CONCLUSIONS: The detection rate of CRAB has decreased since 2018, but a significantly increased prevalence of CRPA and VREfm was seen after the end of zero-policy. An increasing resistance rate to TIM and TZP was seen in CRPA. NDM, KPC, and vanA were the common genes harboured by CREC, CRKP, and VREfm, respectively. Ongoing surveillance after the COVID-19 era is suggested.

Assuntos

COVID-19 , Farmacorresistência Bacteriana Múltipla , Hospitais de Ensino , SARS-CoV-2 , China/epidemiologia , Humanos , COVID-19/epidemiologia , Farmacorresistência Bacteriana Múltipla/genética , Estudos Retrospectivos , SARS-CoV-2/efeitos dos fármacos , SARS-CoV-2/genética , Antibacterianos/farmacologia , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Adulto , Testes de Sensibilidade Microbiana

RESUMO

MicroRNAs (miRNAs) are known to play critical roles in regulating rice agronomic traits through mRNA cleavage or translational repression. Our previous study indicated that miR5504 regulates plant height by affecting cell proliferation and expansion. Here, the two independent homozygous mir5504 mutants (CR1 and CR2) and overexpression lines (OE1 and OE2) were further used to investigate the functions of miR5504. The panicle length, 1000-grain weight and grain yield per plant of miR5504-OE lines were identical to those of Nipponbare (NIP), but the 1000-grain weight of mir5504 mutants was reduced by about 10% and 9%, respectively. Meanwhile, the grain width and thickness of mir5504 mutants decreased significantly by approximately 10% and 11%, respectively. Moreover, the cytological results revealed a significant decrease in cell number along grain width direction and cell width in spikelet in mir5504, compared with those in NIP. In addition, several major storage substances of the rice seeds were measured. Compared to NIP, the amylose content of the mir5504 seeds was noticeably decreased, leading to an increase of nearly 10 mm in gel consistency (GC) in mir5504 lines. Further investigation confirmed that LOC_Os08g16914 was the genuine target of miR5504: LOC_Os08g16914 over-expression plants phenocopied the mir5504 mutants. This study provides insights into the role of miR5504 in rice seed development.

Assuntos

Grão Comestível , Regulação da Expressão Gênica de Plantas , MicroRNAs , Oryza , Oryza/genética , Oryza/crescimento & desenvolvimento , Oryza/metabolismo , MicroRNAs/genética , MicroRNAs/metabolismo , Grão Comestível/genética , Grão Comestível/crescimento & desenvolvimento , Grão Comestível/metabolismo , Sementes/genética , Sementes/crescimento & desenvolvimento , Sementes/metabolismo , Mutação , Pleiotropia Genética , Plantas Geneticamente Modificadas , RNA de Plantas/genética , RNA de Plantas/metabolismo , Amilose/metabolismo

RESUMO

The fluorescent flexible sensor for point-of-care quantification of clinical anticoagulant drug, Heparin (Hep), is still an urgent need of breakthrough. In this research, a hyperbranched poly(amido amine) (HPA) was decorated with tetraphenylethene (TPE) and Rhodamine B (RhB), constructing a ratiometric fluorescent sensor (TR-HPA) for Hep. When the sensor was exposed to Hep, the TPE units within the probe skeleton would aggregate, resulting in an increasing fluorescent emission at 483 nm. The 580 nm of fluorescence came from RhB enhance, simultaneously, due to the fluorescence resonance energy transfer. As a result, there are two good linear correlation between the fluorescence emission ratio (E483/E580) of TR-HPA and the Hep concentration over a range of 0-1.0 µM, with a low limit of detection of 3.0 nM. Furthermore, we incorporate the TR-HPA probe into a polyvinyl alcohol (PVA) hydrogel matrix to create a flexible fluorescent sensing system platform, denoted as TR-HPA/PVA. This approach offers a straightforward visual detection method by causing a fluorescence color change from pink to blue when trace amounts of Hep are present. The hydrogel-based fluorescent sensor streamlines the detection procedures for Hep in biomedical applications. It shows great potential in rapid and point-of-care human blood clotting condition monitoring, making it suitable for next-generation wearable medical devices.

Assuntos

Corantes Fluorescentes , Heparina , Rodaminas , Humanos , Aminas , Espectrometria de Fluorescência/métodos , Hidrogéis

RESUMO

OBJECTIVE: The objective of this study was to determine the role of body fat percentage (BFP) changes in diabetes remission (DR) and the association between baseline body composition and its changes after bariatric surgery. METHODS: We analyzed 203 patients with type 2 diabetes who underwent Roux-en-Y gastric bypass. Body composition was measured using a gold-standard-derived predictive equation and magnetic resonance imaging. Body composition changes were calculated as 100 × (baseline value - follow-up value)/baseline value. We verified the results in a laparoscopic sleeve gastrectomy cohort with 311 patients. RESULTS: Compared with non-remission patients in the Roux-en-Y gastric bypass cohort, those who achieved DR showed a higher baseline fat-free mass index (FFMI) and experienced the most significant changes in BFP (p < 0.001). In comparative analyses, BFP changes were significantly better than BMI changes in identifying short- and long-term DR. Linear regression analysis identified FFMI as the most significant baseline variable correlated with BFP changes (p < 0.001). Baseline BMI was positively correlated with changes in BFP but negatively correlated with changes in FFMI. These findings were replicated in the laparoscopic sleeve gastrectomy cohort. CONCLUSIONS: BFP changes determine DR after bariatric surgery, and baseline FFMI is crucial for BFP changes. A low initial BMI is associated with a smaller BFP reduction and greater FFMI loss after bariatric surgery.

RESUMO

As a promising alternative to conventional antibiotic drugs in the biomedical field, functional peptide has been widely used in disease treatment owing to its low toxicity, high absorption rate, and biological activity. Recently, several machine learning methods have been developed for functional peptide prediction. However, the main research heavily relies on statistical features and few consider multifunctional peptide identification. So, we propose SME-MFP, a novel predictor in the imbalanced multi-label functional peptide datasets. First, we employ physicochemical and evolutionary information to represent the peptide sequence's initialization features from multiple perspectives. Second, the features are fused and then put into spatial feature extractors, where the residual connection and multiscale convolutional neural network extract more discriminative features of different lengths' peptide sequences. Besides, we also design AFT-based temporal feature extractors to fully capture the global interactions of the sequences. Finally, devising a new loss to replace the traditional cross entropy loss to settle the class imbalance problems. The results show that our framework not only enhances the model's ability to capture sequence features effectively, but also accuracy improves by 3.89% over existing methods on public peptide datasets.

Assuntos

Redes Neurais de Computação , Peptídeos , Aprendizado de Máquina , Sequência de Aminoácidos