Search Results (12)

Herbivore-induced plant volatiles (HIPVs) play a pivotal role in mediating tritrophic interactions between plants, herbivores, and their natural enemies. Paracarophenax alternatus, a parasitic mite targeting the egg stage of Monochamus alternatus, has emerged as a promising biocontrol agent. However, its ability to detect Pinus massoniana-derived HIPVs for host insect localization remains unclear. G-protein-coupled receptors (GPCRs) may play a role in mediating the perception of HIPVs and associated chemosensory signaling pathways in mites. In this study, a total of 85 GPCRs were identified from P. alternatus. All GPCRs exhibited conserved transmembrane domains and stage-specific expression patterns, with 21 receptors significantly upregulated in viviparous mites. Combined with two previously identified odorant receptors (ORs), six candidate chemosensory receptors were selected for molecular dynamics simulations to validate their binding stability with key volatile compounds. The results demonstrate that specific GPCRs likely facilitate HIPV detection in mites, enabling precise host localization within dynamic ecological niches. Our findings provide critical insights into the molecular basis of mite–host interactions and establish a framework for optimizing P. alternatus-based biocontrol strategies against pine wilt disease vectors. Full article

Microecological preparations (MPs), encompassing probiotics, prebiotics, synbiotics, and postbiotics, are microbial feed supplements that enhance host health through gut microbiota modulation. Unlike the narrow definition of probiotics (viable microorganisms), MPs constitute a broader category including non-viable microbial derivatives and selectively fermented substrates. Their application in aquaculture significantly reduces antibiotic dependence. Given the industry’s intensification challenges, while meeting global protein demands, high-density aquaculture elevates disease risks, driving prophylactic antibiotic overuse. This practice accelerates antimicrobial resistance (AMR) development, compromising treatment efficacy and causing residual antibiotics in aquatic products. Such residues violate international food safety standards, triggering trade disputes. As sustainable alternatives, MPs operate through multiple mechanisms: the competitive exclusion of pathogens, immune stimulation, and nutrient absorption enhancement. This review examines the patterns of antibiotic abuse and the emergence of AMR in carp aquaculture, evaluates MP-based mitigation strategies from the perspective of antibiotic alternatives, and analyzes the advantages, disadvantages, and application progress of MPs. Based on existing evidence, we propose targeted research priorities for MP optimization, advocating for scientifically guided implementation in commercial cyprinid aquaculture. Full article

Mobility limitations due to congenital disabilities, accidents, or illnesses pose significant challenges to the daily lives of individuals with disabilities. This study presents a novel design for a multifunctional intelligent vehicle, integrating head recognition, eye-tracking, Bluetooth control, and ultrasonic obstacle avoidance to offer an innovative mobility solution. The smart vehicle supports three driving modes: (1) a nostril-based control system using MediaPipe to track displacement for movement commands, (2) an eye-tracking control system based on the Viola–Jones algorithm processed via an Arduino Nano board, and (3) a Bluetooth-assisted mode for caregiver intervention. Additionally, an ultrasonic sensor system ensures real-time obstacle detection and avoidance, enhancing user safety. Extensive experimental evaluations were conducted to validate the effectiveness of the system. The results indicate that the proposed vehicle achieves an 85% accuracy in nostril tracking, over 90% precision in eye direction detection, and efficient obstacle avoidance within a 1 m range. These findings demonstrate the robustness and reliability of the system in real-world applications. Compared to existing assistive mobility solutions, this vehicle offers non-invasive, cost-effective, and adaptable control mechanisms that cater to a diverse range of disabilities. By enhancing accessibility and promoting user independence, this research contributes to the development of inclusive mobility solutions for disabled and elderly individuals. Full article

Objectives: Gut microbiota-derived metabolites—trimethylamine N-oxide (TMAO) and its precursors choline, betaine, and carnitine—have been linked to various health outcomes. However, their role in gestational diabetes mellitus (GDM) remains unclear due to inconsistent findings. This study aims to investigate the associations between maternal plasma concentrations of these metabolites during early pregnancy and the risk of GDM. Methods: A nested case–control study was performed in the Shanghai Birth Cohort. GDM cases and non-GDM controls were matched according to maternal age at a ratio of 1:4. Three hundred twenty-one identified GDM cases and 1284 controls were included. Maternal plasma concentrations of TMAO and its precursors were measured between 12 and 16 weeks of gestation in early pregnancy using high-performance liquid chromatography-tandem mass spectrometry. Conditional logistic regression models were applied to assess associations between metabolite levels and GDM risk and to calculate odds ratios (ORs) and their 95% confidence intervals (CIs). Multivariate linear regressions evaluated relationships between metabolite concentrations and glycemic indicators. Stratified and sensitivity analyses were conducted to ensure robustness. Results: Maternal plasma levels of TMAO, choline, betaine, and carnitine in early pregnancy were 1.95 μmol/L (IQR, 1.16–3.20), 9.25 μmol/L (IQR, 7.31–11.98), 20.51 μmol/L (IQR, 16.92–24.79), and 17.13 μmol/L (IQR, 13.33–21.16), respectively. Betaine and carnitine were significantly higher in GDM cases (p = 0.002 and p = 0.042, respectively). No significant associations were identified between TMAO levels and GDM risk and glycemic indicators. Each SD increase in choline was associated with a 16% higher GDM risk (OR = 1.16, 95% CI: 1.01, 1.34, p = 0.039), while increased betaine and carnitine levels were linked to a 19% (OR = 0.81, 95% CI: 0.70, 0.95; p = 0.010) and 20% (OR = 0.80, 95% CI: 0.69, 0.94; p = 0.007) lower risk, respectively. Restricted cubic spline models showed no evidence of non-linear relationships (p_{for non-linearity} > 0.05). Interaction analyses indicated that the protective effect of betaine may be more pronounced in parous women. Conclusions: Higher early pregnancy levels of betaine and carnitine were associated with a reduced GDM risk, while elevated choline levels increased the risk. The protective association between betaine and GDM was more pronounced in parous women. No significant relationship was found between TMAO and GDM. The roles of choline, betaine, and carnitine in glucose metabolism warrant further investigation. Full article

Pleurotus eryngii is a tasty and low-calorie mushroom containing abundant high-quality protein. This study aims to improve the digestibility of P. eryngii protein (PEP) and hence to facilitate its development as a healthy alternative protein. The extracted PEP was pretreated with 1000–5000 U of papain, neutral protease and alkaline protease. The Chyme collected from in vitro simulated gastrointestinal digestion was analyzed by fluorescence microscopy and protein particle analyzer, and the endpoint profiles of peptides and amino acids were determined by UHPLC-MS/MS and NanoLC-MS/MS. The particle size curve and fluorescence microscopy images jointly supported that protease hydrolysis improved decomposition and dispersion of PEP during digestion, particularly in the gastric phase. The impact on Zeta potential was minimal. Proteases effectively increased the abundance of amino acids after digestion, particularly L-isomer Lys and Arg Maximum release was achieved when pretreated with 5000 U of alkaline protease, reaching 7.54 times that of control. Pretreatments by proteases also notably increased digestive yields of 16,736–19,870 peptides, with the maximum reaching 1.70 times that of the control, which mainly consisted of small peptides composed of 7–15 amino acids with molecular weight below 800 Da. The findings indicated that protease hydrolysis, especially pretreatment with 5000 U of alkaline protease, effectively enhanced the digestibility of PEP, which shed light on providing enzymatic approaches for improving bioavailability and developing healthy fungal proteins. Full article

This study aims to improve the precision of wheat spike counting and disease detection, exploring the application of deep learning in the agricultural sector. Addressing the shortcomings of traditional detection methods, we propose an advanced feature extraction strategy and a model based on the probability density attention mechanism, designed to more effectively handle feature extraction in complex backgrounds and dense areas. Through comparative experiments with various advanced models, we comprehensively evaluate the performance of our model. In the disease detection task, our model performs excellently, achieving a precision of 0.93, a recall of 0.89, an accuracy of 0.91, and an mAP of 0.90. By introducing the density loss function, we are able to effectively improve the detection accuracy when dealing with high-density regions. In the wheat spike counting task, the model similarly demonstrates a strong performance, with a precision of 0.91, a recall of 0.88, an accuracy of 0.90, and an mAP of 0.90, further validating its effectiveness. Furthermore, this paper also conducts ablation experiments on different loss functions. The results of this research provide a new method for wheat spike counting and disease detection, fully reflecting the application value of deep learning in precision agriculture. By combining the probability density attention mechanism and the density loss function, the proposed model significantly improves the detection accuracy and efficiency, offering important references for future related research. Full article

Background: A gut-microbial metabolite, trimethylamine N-oxide (TMAO), has been associated with type 2 diabetes mellitus (T2DM). Few previous prospective studies have addressed associations between the changes in TMAO and T2DM incidence. Methods: Data were derived from a longitudinal cohort conducted from 2019 to 2021 in rural areas of Fuxin County, Liaoning Province, China, and 1515 diabetes-free participants aged above 35 years were included. The concentrations of serum TMAO and its precursors were measured at two time points, namely in 2019 and 2021. TMAO and TMAO changes (ΔTMAO) were separately tested in a logistic regression model. For further examination, the odds ratios (ORs) for T2DM were calculated according to a combination of TMAO levels and ΔTMAO levels. Results: During a median follow-up of 1.85 years, 81 incident cases of T2DM (5.35%) were identified. Baseline TMAO levels exhibited a nonlinear relationship, first decreasing and then increasing, and only at the highest quartile was it associated with the risk of T2DM. The OR for T2DM in the highest quartile of serum TMAO was 3.35 (95%CI: 1.55–7.26, p = 0.002), compared with the lowest quartile. As for its precursors, only choline level was associated with T2DM risk and the OR for T2DM in the Q3 and Q4 of serum choline was 3.37 (95%CI: 1.41–8.05, p = 0.006) and 4.72 (95%CI: 1.47–15.13, p = 0.009), respectively. When considering both baseline TMAO levels and ΔTMAO over time, participants with sustained high TMAO levels demonstrated a significantly increased risk of T2DM, with a multivariable-adjusted OR of 8.68 (95%CI: 1.97, 38.34). Conclusion: Both initial serum TMAO levels and long-term serum TMAO changes were collectively and significantly associated with the occurrence of subsequent T2DM events. Interventions aimed at normalizing TMAO levels, such as adopting a healthy dietary pattern, may be particularly beneficial in T2DM prevention. Full article

Sardina pilchardus is a valuable source of bioactive peptides with potential applications in functional foods. In this study, we investigated the angiotensin-converting enzyme (ACE) inhibitory activity of Sardina pilchardus protein hydrolysate (SPH) produced using dispase and alkaline protease. Our results showed that the low molecular mass fractions (<3 kDa) obtained through ultrafiltration exhibited more effective ACE inhibition, as indicated by screening with ACE inhibitory activity. We further identified the low molecular mass fractions (<3 kDa) using an LC-MS/MS rapid screening strategy. A total of 37 peptides with potential ACE inhibitory activity were identified based on high biological activity scores, non-toxicity, good solubility, and novelty. Molecular docking was used to screen for peptides with ACE inhibitory activity, resulting in the identification of 11 peptides with higher -CDOCKER ENERGY and -CDOCKER INTERACTION ENERGY scores than lisinopril. The sequences FIGR, FILR, FQRL, FRAL, KFL, and KLF were obtained by synthesizing and validating these 11 peptides in vitro, all of which had ACE inhibitory activity, as well as zinc-chelating capacity. All six peptides were found to bind to the three active pockets (S1, S2, and S1’) of ACE during molecular docking, indicating that their inhibition patterns were competitive. Further analysis of the structural characteristics of these peptides indicated that all six peptides contain phenylalanine, which suggests that they may possess antioxidant activities. After experimental verification, it was found that all six of these peptides have antioxidant activities, and we also found that the SPH and ultrafiltration fractions of SPH had antioxidant activities. These findings suggest that Sardina pilchardus may be a potential source of natural antioxidants and ACE inhibitors for the development of functional foods, and using LC-MS/MS in combination with an online database and molecular docking represents a promising, effective, and accurate approach for the discovery of novel ACE inhibitory peptides. Full article

Solving high electrical-energy input for pollutants degradation is one of the core requirements for the practical application of photoelectrocatalytic (PEC) technology. Herein, we developed a self-driven dual-photoelectrode PEC system (TiO₂ NNs-Co₃O₄) composed of a TiO₂ nanoneedle arrays (TiO₂ NNs) photoanode and Co₃O₄ photocathode for the first time. Under light-emitting-diode (LED) illumination, the bias-free TiO₂ NNs-Co₃O₄ PEC system exhibited excellent PEC performance, with an internal bias as high as 0.19 V, achieving near complete degradation (99.62%) of sulfamethazine (SMT) with a pseudo-first-order rate constant of 0.042 min⁻¹. The influences of solution pH, typical inorganic anions, natural organic matter, and initial SMT concentration on the PEC performance were investigated. Moreover, the main reactive oxygen species (h⁺, ^•OH, ^•O₂⁻) in the dual-photoelectrode PEC system for SMT decomposition were elaborated. The practical application feasibility for efficient water purification of this unbiased PEC system was evaluated. It was proved that the TiO₂ NNs photoanode provided a negative bias while the Co₃O₄ photocathode provided a positive bias for the photoanode, which made this system operate without external bias. This work elucidated the cooperative mechanism of photoelectrodes, providing guidance to develop a sustainable, efficient, and energy-saving PEC system for wastewater treatment. Full article

The race against climate change has been a great challenge for years, and the UK government has taken serious steps towards achieving the net-zero carbon target by 2050. Technology is leading the way and innovation is believed to be a key solution. Nevertheless, tackling the issue, by attempting to limit the waste in energy, due to negative energy usage behaviour, has proven to be a successful approach that is capable of complementing other technology-based initiatives. The first step towards this is to promote energy-conscious behaviour and pinpoint where savings can be made. Thereby, this paper contributes to the existing literature, by presenting a new methodology to identify potential energy waste and negative energy usage behaviour in an NHS hospital. The paper presents an analysis of electricity consumption vs occupancy during minimal consumption periods (i.e, bank holidays and weekends) and it presents a log of equipment left switched on outside of working hours, in order to highlight the level of energy-conscious behaviour. The results revealed that the proposed technique is not only able to identify negative energy usage behaviour amongst the hospital staff but helps identify areas where immediate energy savings can be made, with potential savings of more than 30,000 pounds, if action is taken. Full article

Smart cities employ technology and data to increase efficiencies, economic development, sustainability, and life quality for citizens in urban areas. Inevitably, clean technologies promote smart cities development including for energy, transportation and health. The smart city concept is ambitious and is being refined with standards. Standards are used to help with regulating how smart cities function and contributing to define a smart city. Smart cities must be officially recognized by national and international authorities and organizations in order to promote societal advancement. There are many research and review articles on smart cities. However, technical standards are seldom discussed in the current literature. This review firstly presents the study of smart city definitions and domain. The well-known smart city standards will be presented to better recognize the smart city concept. Well-defined standards allow meaningful comparisons among smart cities implementation. How smart city initiatives make a city smarter and improve the quality of life will be discussed for various countries. This review highlights that technical standards are important for smart cities implementation. This paper serves as a guide to the most recent developments of smart cities standards. Full article

Sports analysis has recently attracted increasing research efforts in computer vision. Among them, basketball video analysis is very challenging due to severe occlusions and fast motions. As a typical tracking-by-detection method, k-shortest paths (KSP) tracking framework has been well used for multiple-person tracking. While effective and fast, the neglect of the appearance model would easily lead to identity switches, especially when two or more players are intertwined with each other. This paper addresses this problem by taking the appearance features into account based on the KSP framework. Furthermore, we also introduce a similarity measurement method that can fuse multiple appearance features together. In this paper, we select jersey color and jersey number as two example features. Experiments indicate that about 70% of jersey color and 50% of jersey number over a whole sequence would ensure our proposed method preserve the player identity better than the existing KSP tracking method. Full article