Search Results (223)

Background: Brucellosis is a global zoonosis caused by Brucella. Histidine biosynthesis is essential for bacterial growth, but its role in Brucella melitensis virulence remains unclear. HisD catalyzes the final two steps of histidine synthesis and is absent in mammals, making it a potential drug target. Results: We constructed a hisD deletion mutant (ΔhisD) and complemented strain (ChisD) via homologous recombination. ΔhisD failed to grow in medium without histidine supplementation. It showed reduced survival under polymyxin B and SDS stress, and impaired outer membrane integrity under polymyxin B challenge, though no defect was observed under non-stressed conditions. Intracellularly, ΔhisD replicated poorly in HeLa and RAW264.7 cells, and this defect was rescued by exogenous histidine. In a mouse model, ΔhisD exhibited lower bacterial loads in liver and spleen, reduced splenomegaly, and attenuated hepatic granuloma formation. Conclusions: Histidine biosynthesis deficiency attenuates Brucella virulence by restricting nutritional acquisition and conditionally compromising outer membrane stability. HisD is a promising target for anti-brucellosis drug development, and ΔhisD holds potential as a live attenuated vaccine candidate. Full article

In oncology, body composition (BC) provides clinically meaningful information beyond body mass index, capturing muscle and adipose tissue alterations associated with survival, treatment tolerance, surgical complications and quality of life. Although routine oncologic imaging is widely available, BC assessment remains poorly integrated into daily clinical practice, largely because conventional imaging-based approaches require time-consuming manual analyses, dedicated software and specialized expertise. Artificial intelligence (AI), particularly deep learning-based image segmentation, may automate BC analysis and generate rapid, reproducible, and scalable estimates from routinely acquired imaging, without increasing clinical workload. This opinion paper aims to examine AI-based BC analysis as a potential strategy to integrate BC into routine oncology workflows, outlining its potential clinical benefits and the aspects that need to be addressed before widespread implementation. AI-based BC analysis may improve nutritional assessment, refine clinical and nutritional risk stratification, and help identify patients at increased risk of treatment-related toxicity. In perspective, BC data may also support more personalized nutritional and physical activity interventions and contribute to muscle mass-informed anticancer treatment dosing strategies. Several gaps still limit its clinical implementation, including the need of robust external validation, standardized acquisition and analytical protocols, clinically meaningful cut-offs and ethical, and regulatory and data governance frameworks. AI-based BC analysis is therefore a promising but still evolving approach that may help translate BC from a prognostic marker into a clinically actionable tool in oncology. Full article

Understanding how P availability affects root turnover and P redistribution within plants is essential for optimizing fertilization strategies and sustaining forest growth under low-P soils. This study evaluated the effects of P fertilization on root system dynamics, plant growth, and P nutrition of Handroanthus heptaphyllus, a flowering landscape tree, cultivated in a subtropical climate. Plants were grown under two soil P levels (low and high). Plant height, stem diameter, leaf P concentration, soil P availability, total numbers of living and dead fine roots, total fine root surface area, and fine root production rate were measured at 18, 24, 30, and 36 months after planting. Phosphate fertilization increased soil P availability during the first 24 months and resulted in significant gains in plant height, stem diameter, fine root production, total surface area, and the ratio between living and dead fine roots, indicating a higher proportion of living roots relative to dead ones. Under high P availability, the greatest fine root production and surface area of living fine roots occurred in the 0–20 cm soil layer, reflecting localized P application near the plants. High P availability enhanced root system development, promoted greater soil exploration, and improved P uptake. These results indicate that under P supplementation, plants strategically invest in root growth, improving nutrient acquisition efficiency and reducing dependence on external inputs. Increased phosphorus availability enhances root growth and increases fine root production and turnover. Minirhizotron monitoring effectively captured shifts in root system dynamics driven by P availability, including enhanced root growth, increased fine root production and turnover, and improved nutrient uptake under high P, as well as limited root activity under low P conditions, indicating a more conservative strategy with reduced investment in root production. Full article

Bark beetle–fungus associations are essential for nutrition, detoxification, and host colonisation, but their composition and function vary across developmental stages and environmental contexts. Hence, we characterised the fungal communities associated with two pine-feeding bark beetles, Ips sexdentatus (ISX) and Ips acuminatus (IAC), across developmental stages and compared wild-collected and laboratory-bred populations using ITS2 amplicon sequencing. Both beetle species maintained a stable core mycobiome dominated by Kuraishia, Ogataea, Ophiostoma, Graphilbum, and Cyberlindnera. These taxa have been earlier reported to be associated with nutrient provisioning, detoxification of host secondary metabolites, and chemical signalling. Adult beetles showed species-specific community differences, whereas wild-collected beetles, particularly IAC, harboured higher fungal diversity than laboratory populations, indicating a strong environmental effect. Beetles shared more fungal taxa with control wood than with gallery wood, suggesting possible fungal acquisition during feeding and concurrent restructuring of the wood mycobiome during infestation. Monoterpene bioassays with selected yeast symbionts showed differential growth responses to α-pinene, 3-carene, and terpinolene, and their mixture, with the mixture producing stronger inhibition than individual compounds. These yeast symbionts further displayed selective antagonistic activity in vitro against selected filamentous fungi, including entomopathogenic taxa, along with detectable lytic and digestive enzyme activities. Together, our findings highlight a link between community structure, predicted functions, and observed interaction phenotypes, providing a strong basis for future mechanistic studies of beetle–fungus–conifer interactions. Full article

Xinyu pear is one of the important pear cultivars in China. Owing to its rich nutritional composition, high quality, and distinctive flavor, it is highly favored in the market. In this study, near-infrared spectroscopy was employed to determine the soluble solid content (SSC) of Xinyu pears. To investigate the influence of spectral preprocessing on SSC prediction, near-infrared spectra of two batches of Xinyu pear samples were collected using the same portable spectrometer under different acquisition parameters, resulting in differences in spectral bands. A linear interpolation method was introduced to the first batch to generate a new dataset to match the dimensionality of the second batch, and a total of three datasets were used. Five preprocessing methods, including moving average smoothing (MA), standard normal variate transformation (SNV), multiplicative scatter correction (MSC), first derivative (D1), and second derivative (D2), together with three regression models, namely partial least squares regression (PLSR), support vector regression (SVR), and convolutional neural network (CNN), were systematically evaluated and compared in terms of predictive accuracy. Overall, PLSR achieved the best prediction performance, followed by CNN and SVR. Certain differences in model performance were observed among the three datasets. In general, MA exhibited the best overall performance across different datasets and models. Although SNV and MSC were slightly inferior to MA, they showed relatively stable predictive accuracy. By contrast, prediction models based on derivative spectra generally performed poorly. To further exploit the complementary information contained in differently preprocessed spectra, a four-branch CNN model was constructed using raw spectra, MA-preprocessed spectra, SNV-preprocessed spectra, and MSC-preprocessed spectra as separate inputs. Based on the fused features extracted by the CNN, PLSR and SVR models were subsequently developed. The prediction correlation coefficients of the feature-fusion CNN model on the prediction sets of the three datasets were 0.8811, 0.8259, and 0.7064, respectively. For the original datasets of the first and second batches, the feature-fusion model outperformed all single-preprocessing models. For the dataset generated by linear interpolation, the predictive performance of the feature-fusion strategy was comparable across the three models; specifically, its accuracy in SVR exceeded that of all single-preprocessing models, while its accuracies in CNN and PLSR surpassed those of most preprocessing methods. These results demonstrate that integrating feature information from spectra subjected to different preprocessing methods is a feasible strategy for improving prediction accuracy. This study provides an effective reference for SSC prediction in Xinyu pears based on portable spectrometers. Full article

Hyperspectral airborne data combined with machine learning has proven effective for characterizing plant nutritional quality. However, terrain, viewing geometry, and illumination can distort spectral signatures, leading to biased models with limited generalizability for large-scale mapping across farms with a heterogeneous landscape. In this study, we developed a framework for mapping pasture quality using airborne hyperspectral imaging while explicitly accounting for in-field acquisition and environmental effects. Nitrogen content (N%) and metabolizable energy (ME) were used as reference indicators across four hill country farms in New Zealand with contrasting environmental and management conditions. Ground truth was obtained using standard laboratory wet chemistry methods and paired with AisaFENIX airborne hyperspectral data, resulting in 1610 spectral samples derived from 161 spatially independent ground plots. Gaussian Process Regression (GPR) and a one-dimensional convolutional neural network (1D-CNN) were trained and evaluated on an independent test dataset. Both models achieved strong predictive performance (R² > 0.8); however, GPR provided more reliable estimates through predictive uncertainty. Using a 95% confidence interval threshold to mask uncertain predictions increased overall performance (R² > 0.9) and consequently improved the reliability of the mapped outputs. This approach enables spatially explicit pasture nutrient assessment to support precision land management for carbon and nitrogen. Full article

The C-terminal binding protein 1 (CTBP1) is a transcriptional corepressor with a major role in nervous system growth and development. There are only 20 published cases with CTBP1 mutations, displaying a phenotype of Hypotonia, Ataxia, Developmental Delay and Tooth enamel defect Syndrome (HADDTS). Histochemical evidence of decreased mitochondrial respiratory chain activity has been previously reported, but comprehensive data on the metabolic phenotype assessed by various cellular respiration parameters are still missing. We present a 10-year-old female with typical HADDTS features, harboring the most reported de novo heterozygous CTBP1 mutation c.991C>T. To elucidate her metabolic phenotype, we quantified mitochondrial respiration in peripheral blood mononuclear cells (PBMCs) utilizing an analyzer for assessing mitochondrial function (Seahorse XFp). Real-time metabolic assays revealed profound mitochondrial dysfunction with significantly attenuated maximal respiration and spare respiratory capacity compared to neurotypical controls. Following mitochondria-targeted nutritional support for one-year measurable bioenergetic improvements and reduced number of respiratory infections were registered. However, neurological recovery and new skill acquisition were not observed. We present a novel case of CTBP1-related neurodevelopmental disorder and demonstrate, for the first time, the application of non-invasive, real-time mitochondrial functional assessment in this setting, providing additional evidence for mitochondrial dysfunction in HADDTS. Full article

Global climate change is rapid and poses an alarming threat to agricultural production, significantly impacting economies. Modern agriculture has strongly emphasized improving nutrient availability in crops to address rising malnutrition and contribute to global food security. However, abiotic stresses, including warmer temperatures, drought, waterlogging stress, and elevated CO₂, have critical direct and indirect effects on nutrient availability in plants. This systematic review was conducted in accordance with the PRISMA guidelines. The literature survey followed a time period of 2–5 months, during which the conceptualization, analysis, writing, and editing of the article were conducted. In the present era, it is essential to adopt measures to improve the nutritional value [enhance Nutrient Use Efficiency (NUE)] and nutrient management of plant-based foods. Plant-associated microbiomes have co-evolved with their plant counterparts and perform essential functions in nutrient acquisition, including microbial sensing and cross-talk with the plant host, nutrient uptake and sharing, and signaling mechanisms. In natural and agricultural ecosystems, plant microbiomes offer major opportunities and can be harnessed to sustainably supply essential plant nutrients and improve NUE in crops of global importance. Crop-associated microbiomes can be precisely tailored to achieve targeted outcomes, enhancing nutrient acquisition and utilization via microbiome engineering. However, bridging knowledge gaps, understanding microbial colonization, plant–microbiome dynamics, and adopting precise editing approaches are crucial to boost sustainable outcomes and crop productivity. By elucidating plant microbiome crosstalk and microbe–microbe signaling, a better understanding of microbe-mediated nutrient acquisition in plants can be achieved, defining key implications in global food security. Full article

This experiment investigated the effects of dietary Artemisia ordosica Krasch. (AOK) supplementation on the n3-polyunsaturated fatty acid (n3-PUFA) profile of subcutaneous adipose tissue (SADT) in Arbas cashmere goats and explored the underlying transcriptional mechanisms. Forty healthy, weaned kids (120 ± 10 days of age; similar body weight) were randomly allocated to two groups (n = 20): a control group (CON, basal diet) and an AOK group (AOK, basal diet with 3% of the roughage replaced by AOK). The feeding trial spanned 104 days, consisting of a 14-day adaptation period and 90 days of data acquisition. Compared with the CON group, AOK significantly reduced the content of saturated fatty acids (SFAs) and n6-polyunsaturated fatty acids (n6-PUFAs)/n3-PUFAs (n6/n3). In contrast, the levels of n3-PUFAs in the SADT of cashmere goats increased markedly (p < 0.05). Compared with the CON group, AOK exhibited significantly higher activities of hormone-sensitive lipase (HSL) (p = 0.027), adenylyl cyclase 2 (ADCY2) (p = 0.010), adenylyl cyclase 5 (ADCY5) (p = 0.046), cluster of differentiation 36 (CD36) (p = 0.013), solute carrier family 27 member 4 (SLC27A4) (p = 0.021), and fatty acid binding protein 4 (FABP4) (p = 0.040), along with significantly lower activities of fatty acid synthase (FAS) (p = 0.002), lipoprotein lipase (LPL) (p = 0.048), and stearoyl-coa desaturase (SCD) (p = 0.026) in SADT. Compared with the CON group, the activities of superoxide dismutase (SOD) (p = 0.032), catalase (CAT) (p = 0.010), glutathione peroxidase (GSH-PX) (p = 0.029), and total antioxidant capacity (T-AOC) (p = 0.002) were significantly increased in the AOK group. Transcriptomic profiling revealed that AOK supplementation downregulated mRNA levels of ADCY2, ADCY5, LPL, FAS, SCD, stearoyl-CoA desaturase 1 (SCD1), stearoyl-CoA desaturase 2 (SCD2), glycogen synthase 1 (GYS1), acyl-CoA oxidase 1 (ACOX1), acetyl-CoA carboxylase (ACC), diacylglycerol acyltransferase 1 (DGAT1), fatty acid desaturase 1 (FADS1), solute carrier family 27 member 2 (SLC27A2), erythroblastic leukemia viral oncogene homolog 4 (ERBB4), and carnitine palmitoyltransferase 1B (CPT1B) (p < 0.05). It also markedly induced acyl-CoA synthetase long-chain family member 4 (ACSL4) (p < 0.01) in SADT. Genes significantly enriched in the adenosine-monophosphate-activated protein kinase (AMPK) signaling pathway included LPL, SCD1, CPT1B, and GYS1 (p = 0.010). Genes significantly enriched in the phosphatidylinositol 3-kinase-akt (PI3K-Akt) signaling pathway included GYS1 and ERBB4 (p = 0.015). CPT1B, ADCY2, and GYS1 were identified as the genes significantly enriched in the insulin resistance signaling pathway (p = 0.048). LPL was the only gene significantly enriched in the cholesterol metabolism pathway (p = 0.049). Genes showing a tendency toward significant enrichment in the peroxisome-proliferator-activated receptor (PPAR) signaling pathway included ACSL4, CPT1B, SCD1, and LPL (p = 0.051). These interconnected cascades improve insulin sensitivity, stimulate triglyceride (TG) hydrolysis, and modulate n3-PUFA levels. Supplementation with AOK enhances n3-PUFA content by accelerating TG breakdown while simultaneously restraining FA oxidation in SADT. Consequently, AOK supplementation can be effectively used to enhance the nutritional value of cashmere goat meat through improved n3-PUFA deposition in SADT. Full article

Drip fertigation (DF) is increasingly adopted to improve winter wheat productivity, yet its interactions with planting density (PD) and the underlying source–sink mechanisms remain insufficiently quantified. Here, we evaluated winter wheat performance under two water–nitrogen (N) regimes—conventional management (CM) and DF—across a wide PD gradient (100–800 seeds m⁻²) during two growing seasons. Grain yield, yield components, population traits, dry matter production, source–sink indices, canopy N status, N uptake and N-use efficiencies were assessed. Across seasons, DF increased grain yield by 15.4–20.8% relative to CM. Yield exhibited a quadratic response to PD under both regimes; however, DF shifted the optimal PD upward (456–487 seeds m⁻²) compared with CM (377–378 seeds m⁻²) and sustained near-maximum yields over a broader PD range. DF improved population productivity by increasing productive stem percentage and grains per ear, resulting in greater grain number per m² (sink size). DF also strengthened source capacity during grain filling: post-anthesis dry matter production increased by 15.5–17.6% and strongly associated with yield (r² ≥ 0.819). Source–sink analysis suggested that DF was associated with more density treatments showing simultaneously high grain number and high post-anthesis dry matter accumulation, a pattern consistent with a broader high-yield density range. Enhanced N acquisition, especially after anthesis, may have contributed to this response. DF increased N nutrition index at anthesis and markedly increased post-anthesis N uptake by 47.7–49.5%, thereby raising total N uptake at maturity and grain N accumulation. DF improved fertilizer-N recovery efficiency and agronomic efficiency by 33.9–42.3% and 26.7–30.9%, respectively. Collectively, DF improved N uptake and source–sink coordination, enabling high yield and reduced yield penalties when planting density deviated from the optimum. Full article

Objectives: This scoping review synthesized the available evidence on bedside ultrasonography used to confirm short-term nasogastric tube (NGT) placement in adults. Methods: The review followed JBI Collaboration methodology. Searches were conducted in CINAHL, Embase, LILACS, PubMed, and Scopus, as well as in gray literature sources (Google Scholar and ProQuest Dissertation & Thesis Global). Primary studies and clinical guidelines addressing bedside ultrasonography for short-term NGT placement in adults (≥18 years) were eligible, with no limits on language or publication year. Data were extracted and narratively summarized with the I-AIM framework (Indication, Acquisition, Interpretation, and Decision-Making). Results: Twenty-nine studies met the inclusion criteria. Most were single-center observational studies performed in intensive care units or emergency departments. Ultrasound was primarily used for confirmation prior to enteral nutrition initiation, while gastric decompression was less frequently reported. Acquisition protocols varied, although supine positioning, convex abdominal probes, and linear cervical probes were most commonly described. The gastric antrum and esophagus were the principal anatomical landmarks, with interpretation based on direct tube visualization and dynamic fogging; color Doppler was occasionally used. Radiography remained the reference standard in most studies, and only a minority initiated feeding based solely on ultrasound findings. Reported facilitators included bedside feasibility, absence of radiation exposure, and timeliness. Barriers included operator dependency, limited visualization in patients with obesity or gas interposition, protocol heterogeneity, and the limited methodological robustness of available studies. Conclusions: Current evidence suggests that ultrasonography may represent a feasible, radiation-free bedside approach for confirmation of NGT placement. Evidence from selected studies suggests that, with structured training, healthcare professionals may achieve diagnostic accuracy in specific clinical settings, although further robust multicenter investigations are needed to confirm these findings. Full article

Tripartite interaction among arbuscular mycorrhizal fungi (AMF), small grain cereals—including wheat, barley, oats, and rye—and pathogenic organisms constitute a highly complex ecological system with major implications for plant health, productivity and resilience. AMF colonization increases nutrient acquisition, particularly phosphorus and nitrogen, while concurrently priming host defense mechanisms that increase resistance to a broad spectrum of pathogens. These benefits, however, are strongly context-dependent and modulated by AMF species composition, host genotype, soil characteristics, and environmental conditions. AMF activate resistance pathways and modulate the rhizosphere microbiome, underscoring their central role in shaping plant–pathogen dynamics. Importantly, the relevance of these interactions extend beyond crop protection and yield stability to encompass food security and sustainability goals aligned with the One Health framework, which recognizes the interconnectedness of plant, environmental, and human health. Field implementation of AMF-based strategies has the potential to reduce reliance on chemical fertilizers and pesticides, thereby promoting sustainable cereal production, restoring soil biodiversity, and enhancing ecosystem services, with downstream benefits for human nutrition and environmental safety. This review integrates current knowledge on AMF–cereal–pathogen interactions, synthesizing mechanistic advances and applied perspectives while identifying critical knowledge gaps that must be addressed to effectively deploy AMF in resilient and sustainable agroecosystems within a One Health context. Full article

Lisianthus [Eustoma grandiflorum (Raf.) Shinners] is among the 10 most produced and marketed cut flowers in the world. However, its slow growth represents a challenge for its production. This study evaluated the efficiency of rhizobacterial strains in vegetative growth and nutrient acquisition in lisianthus plants. Freshly germinated seeds of lisianthus cv. Mariachi Blue Double were used. Seven rhizobacterial strains and two controls (sterile distilled water and nutrient broth) were evaluated in a completely randomized design. Replication varied among treatments and variables: shoot growth traits were assessed on 10–12 plants per treatment, root biomass on a destructive subsample of six plants per treatment and shoot nutrient contents on four composite samples per treatment. Measurements taken 149 days after sowing showed that plants inoculated with the strains Acinetobacter vivianii C48, Achromobacter xylosoxidans C56, and Arthrobacter pokkalii JLB4 had greater height, leaf area, leaf number, and fresh and dry biomass, both aerial and in the root. These strains also enhanced N and P uptake in shoot tissues. In contrast, the Bacillus pumilus strain R44 significantly decreased height and leaf number. The results suggest that strains C48, C56 and JLB4 can stimulate nutrition, accelerate plant growth, and shorten the vegetative phase in lisianthus. Full article

Reliable visual characterization of food composition is a fundamental prerequisite for image-based dietary assessment and health-oriented food analysis. In fine-grained food recognition, models often suffer from large intra-class variation and small inter-class differences, where visually similar dishes exhibit subtle yet discriminative differences in ingredient compositions, spatial distribution, and structural organization, which are closely associated with different nutritional characteristics and health relevance. Capturing such composition-related visual structures in a non-invasive manner remains challenging. In this work, we propose a fine-grained food classification framework that enhances spatial relation modeling and key-region awareness to improve discriminative feature representation. The proposed approach strengthens sensitivity to composition-related visual cues while effectively suppressing background interference. A lightweight multi-branch fusion strategy is further introduced for the stable integration of heterogeneous features. Moreover, to support reliable classification under large intra-class variation, a token-aware subcenter-based classification head is designed. The proposed framework is evaluated on the public FoodX-251 and UEC Food-256 datasets, achieving accuracies of 82.28% and 82.64%, respectively. Beyond benchmark performance, the framework is designed to support practical image-based dietary analysis under real-world dining conditions, where variations in appearance, viewpoint, and background are common. By enabling stable recognition of the same food category across diverse acquisition conditions and accurate discrimination among visually similar dishes with different ingredient compositions, the proposed approach provides reliable food characterization for dietary interpretation, thereby supporting practical dietary monitoring and health-oriented food analysis applications. Full article

Different groups of microorganisms—namely lactic acid bacteria (LAB), coagulase-negative staphylococci (CNS), dairy propionibacteria, yeasts, and molds—play essential roles in producing safe fermented foods of animal and plant origin with high nutritional value and sensory quality. The acquisition of genetic traits with technological relevance by natural horizontal gene transfer (HGT) via transformation, conjugation, phage transduction, and other routes would broaden the spectrum of beneficial activities exerted by individual microbial strains with no limitations for their use in food. Therefore, this critical review aimed to identify the potential for natural genetic improvement of microbial species relevant to food technology, based on reports of natural genetic exchanges occurring in environmental niches and laboratory conditions. Results showed that the species most frequently involved in natural HGT is Lactiplantibacillus plantarum, followed by Streptococcus thermophilus and Lactococcus lactis. Extensive HGT events enabling adaptation to food have been observed in domesticated filamentous fungi. The transferred traits of technological relevance include resistance to various stress factors, exopolysaccharide (EPS) and bacteriocin production, protein and amino acid utilization, phage immunity, lactose and citrate metabolism in dairy species, and use of plant carbohydrates in vegetable adapted species. Methods suitable for detecting HGT events in microbial communities have been developed and can aid in isolating improved strains for use in fermented foods. Full article