Search Results (8,571)

Background: Treatment with recombinant human growth hormone (rhGH) is approved for children born small for gestational age (SGA) who fail to show postnatal catch-up growth; however, optimizing its efficacy remains a challenge. Aim: to evaluate the impact of rhGH therapy on growth trajectory (GT) and adult height (AH) in SGA children and to identify factors influencing height gain (HG). Methods: A total of 49 SGA children (24 males, 25 females) without postnatal growth recovery and treated with rhGH were enrolled. Clinical and anthropometric data were collected at treatment initiation (T0), after 1 (T1) and 2 years (T2) of therapy, at pubertal onset (P0), during the first (P1) and second year (P2) of puberty, and at attainment of AH. Parameters included age, bone age, H, weight, BMI (all expressed as SDS), HG, and the difference between H and target height (Δ H-TH). Results: a significant increase in HG at all evaluated stages was observed (p < 0.05). The H–TH difference progressively decreased from T0, particularly until the first two years of puberty. Nevertheless, mean AH was −1.75 ± 0.63 SDS, and it was found to fall within the TH range in 86% of cases. Univariate and multivariate regression analysis revealed that age and H at T0 were independent predictors of HG. Conclusions: rhGH treatment has a positive impact on GT in children born SGA. Pubertal growth has a limited contribution in influencing AH of these patients. H and timing of treatment initiation significantly influence HG in SGA children. Early selection of patients for rhGH therapy could further improve their GT. Full article

Background: Hybrid cardiac rehabilitation (CR) combining supervised and home-based phases with wearable monitoring may improve access and outcomes after myocardial infarction (MI). Objective: To assess the impact of a 14-week hybrid CR program on functional class, exercise capacity, hemodynamics, body composition, and physical activity in post-MI patients with NYHA class II symptoms. Methods: Sixty-six adults post-MI underwent 2 weeks of in-hospital initiation followed by 12 weeks of home-based rehabilitation via a smartwatch–smartphone platform. Within-subject changes from baseline to week 14 were analyzed using appropriate paired statistical tests. Results: NYHA class improved significantly, with 39% of participants downgrading their class (p < 0.001). Body weight decreased by 1.27 ± 2.51 kg (p < 0.001). Systolic and diastolic blood pressures declined (both p ≤ 0.002). Maximal METS rose markedly (25.7% increase; p < 0.001), and watts/kg improved (p < 0.001). Resting heart rate decreased (p = 0.002); peak exercise heart rate change was non-significant. Fat mass declined and skeletal muscle mass increased (mean gain 0.98 kg; p < 0.001). Daily step count increased from 5550 ± 2026 to 7267 ± 2500 steps (p < 0.001). Total body water also increased (p < 0.001). Conclusions: The hybrid CR program produced significant improvements in functional class, exercise capacity, blood pressure, body composition, and physical activity in post-MI NYHA II patients, supporting its effectiveness as a remotely enabled secondary prevention strategy. However, the results are based on hypotheses and randomized controlled trials must confirm the benefits especially with a control group. Nonetheless, it is a feasible and potentially effective alternative to conventional programs in resource-limited settings. Full article

The main approach for improving multiple traits simultaneously is the selection index. The most widely used selection indices are those based on factor analysis, which overcome statistical limitations such as multicollinearity and the reliance on arbitrary weights of the classical Smith–Hazel approach and support multi-environment trials. Nevertheless, the efficiency indices are affected by factors such as genotype number, environment and trait correlation, and heritability. In this study, we simulated different scenarios varying the mentioned factors to evaluate the performance of the Factor-Analysis and Ideotype-Design-Based Index (FAI-BLUP), Multi-trait Genotype–Ideotype Distance Index (MGIDI), and Multi-Trait Stability Index (MTSI). All correlations were positive and constant within each scenario, while the ideotype sought genetic gains for traits in opposite directions. Simulations were conducted using AlphaSimR and FieldSimR, and indices were implemented via the metan package. Results showed that index efficiency was higher in scenarios with larger numbers of genotypes, low-to-moderate trait correlations, and moderate-to-high inter-environment correlations. However, strong correlations among traits, particularly when combined with high heritability, compromise selection index efficiency in scenarios with antagonistic trait objectives. Despite that, the MGIDI consistently outperformed the other indices across most scenarios. Therefore, we emphasize accounting for trait genetic architectures, genotype–trait correlations, and target environment correlations. Full article

Improving productivity under resource and environmental constraints is a key challenge for sustainability-oriented transformation in manufacturing. Using panel data from 30 Chinese provinces during the period 2010–2024, this study examines how regional digital innovation capability is associated with manufacturing total factor productivity at the provincial level. A multidimensional digital innovation index is constructed using the entropy-weighting method, while manufacturing total factor productivity (TFP) is measured using the DEA–Malmquist index. In this study, conventional manufacturing TFP is treated as a productivity-oriented proxy within a sustainability-oriented transformation context, rather than as a direct measure of environmental performance. The empirical framework applies a two-way fixed-effects model and is complemented by supplementary instrumental-variable estimation, mediation analysis, and threshold regression to examine transmission channels and nonlinear effects. The results indicate that digital innovation capability is positively associated with manufacturing TFP, with stronger associations observed in regions that have more developed digital and innovation foundations. Decomposition results show that the gains are mainly related to technological progress rather than short-term efficiency improvements, suggesting that digitalization is reflected primarily through innovation-led upgrading. Mechanism tests further show that improvements in R&D efficiency, data element allocation, and human capital structure play important mediating roles. A significant threshold effect is also observed: When the share of digital-skilled labor exceeds a critical level, the productivity return from digital innovation increases markedly. These findings underscore the role of digital innovation and digital maturity in supporting manufacturing productivity upgrading within a sustainability-oriented transformation context and imply that policy should prioritize coordinated investment in digital infrastructure, data governance, and digital skills development. Full article

Feed supplements play a crucial role in improving and maintaining fish health in modern aquaculture practices. Squalene is a functional lipid naturally present in fatty tissues, possessing numerous beneficial biological properties and wide applications in the food and pharmaceutical industries. In this study, the effects of 100 mg/kg (S1), 200 mg/kg (S2), 300 mg/kg (S3), and 400 mg/kg (S4) of dietary squalene supplementation over four weeks on growth performance, antioxidation, hepatoprotection, hypoxia tolerance, immune relative genes expression, and disease resistance of largemouth bass (Micropterus salmoides) were assessed. The results showed that squalene supplementation significantly increased the weight gain rate (WGR) and specific growth rate (SGR) of largemouth bass (p < 0.05). Serum glucose (GLU) levels were significantly decreased in all squalene-supplemented groups (p < 0.05). Squalene supplementation had minimal effect on serum triglyceride (TG) and total cholesterol in (TCHO) levels. A decrease in malondialdehyde (MDA) level, but accompanied by increases in superoxide dismutase (SOD) and hepatic catalase (CAT) activities, was observed in the S1 group supplemented with squalene. These suggest that squalene may mitigate free radical damage and promote health in largemouth bass. Dietary squalene supplementation enhanced intestinal enzyme activities (trypsin, lipase, and α-amylase) in largemouth bass without inducing any apparent hepatic or histopathological alterations. Squalene supplementation improved hypoxia tolerance and antiviral gene expression (mx, ifn-γ, and irf3) while suppressing the expression of inflammatory cytokine (il-1β, il-8, and tnf-α). The survival rate following LMBRaV infection was significantly higher in the S1 group (100 mg/kg group) compared to the control (p < 0.05). In conclusion, this study demonstrated that adding squalene into the diet of largemouth bass at an optimal level of 100 mg/kg effectively promotes growth performance, enhances digestive enzyme activity and hypoxia tolerance, and modulates lipid metabolism and immune gene expression, thereby contributing to improved resistance against LMBRaV. These findings confirm that squalene can serve as a beneficial functional feed additive in aquaculture. Full article

Hyaluronan (HA) is a ubiquitous extracellular matrix (ECM) component that is gaining significant attention for its diverse roles in cell signalling and disease. The biological functions of HA are dependent on its molecular weight (M_w): low M_w polysaccharide chains drive stimulatory processes such as inflammation and angiogenesis, whereas high M_w HA is stabilising and anti-inflammatory. Growing evidence indicates that HA is integral to brain function. The composition of HA in the brain is regulated by the balance of enzymatic synthesis and degradation, mediated by different isoforms of hyaluronan synthase (HAS) and hyaluronidase (HYAL) respectively. Fluctuating expression of the genes encoding the HAS and HYAL enzymes has been implicated in neuropathology and ageing, with some studies providing evidence towards epigenetic regulation of these genes. The regulatory environment of the brain confers a unique balance of enhanced protection alongside the requirement for maximum flexibility. This scoping review focuses on summarising current knowledge regarding epigenetic regulation of HAS and HYAL genes in neural contexts, as well as identifying gaps in knowledge against which future research can be directed. Understanding how these genes are regulated, particularly through epigenetic mechanisms, provides insight into how HA is regulated in the brain, facilitating understanding regarding its function in brain health and disease. Full article

Consistent behavioural differences among individuals have been documented across many animal taxa, yet their developmental consequences in domestic production systems remain less clear. This gap is especially relevant in managed environments, where food availability and ecological constraints differ markedly from those in the wild. In this study, we assessed behavioural traits in 25 Tibetan sheep (Ovis aries) ewes and examined their associations with early growth in their lambs under semi-captive conditions on the Qinghai–Tibetan Plateau. We quantified docility, exploration, vocal responses, and several physiological measures of responsiveness in the ewes and related these variables to lamb birth weight, early weight gain, and a composite growth index. We found that maternal docility had no significant effect on lamb birth weight, whereas maternal activity, defined as locomotor movement recorded during the open-field phase, was negatively associated with offspring birth weight. One possible interpretation is that ewes showing greater locomotor activity during the open-field phase allocate energy differently during gestation, which could limit foetal growth, although this mechanism was not directly tested in this study. These results suggest that the behavioural effects on offspring development depend strongly on the production context. In this semi-captive system, greater maternal responsiveness was not associated with improved offspring performance, unlike patterns that are often observed in wild populations. This context dependence may be relevant when behavioural traits are considered in Tibetan sheep management or breeding. Full article

Functional foods enriched with bioactive compounds have attracted increasing attention for their potential to improve metabolic health and reduce the risk of chronic diseases. White tea, a minimally processed tea rich in polyphenols and antioxidant constituents, may exert beneficial effects on obesity-related metabolic disturbances through multiple molecular pathways. In this study, we investigated the effects of white tea in a high-fat diet-induced obesity model in rats, with particular emphasis on metabolic regulation and adipokine signaling. Body weight, lipid profile, glucose homeostasis, insulin resistance-related parameters, and circulating levels of apelin and irisin were evaluated. High-fat diet feeding impaired metabolic balance and altered obesity-associated biochemical parameters, whereas white tea administration ameliorated several of these changes. White tea was associated with improvements in body weight gain and selected metabolic parameters, together with modulation of adipokine-related markers. These findings suggest that white tea may function as a bioactive-rich functional food with beneficial effects on pathways involved in obesity and metabolic homeostasis. Our results support the potential contribution of white tea-derived compounds to nutrition-based strategies for the prevention and management of obesity. Full article

Background: Long noncoding RNAs (lncRNAs) have emerged as critical regulators of hepatic metabolism and disease progression. The hepatocyte nuclear factor 1 alpha antisense 1 (HNF1A-AS1) lncRNA modulates liver-specific transcription factors; however, its physiological role in diet-dependent lipid homeostasis remains poorly defined. Methods: In this study, we investigated the mouse ortholog, Hnf1a opposite strand 1 (Hnf1aos1), using AAV-mediated knockdown in C57BL/6J mice fed either a chow diet (10% kcal from fat) or a high-fat diet (HFD; 60% kcal from fat) for 12 weeks. Metabolic phenotyping included hepatic lipid quantification, histological analysis, serum biochemistry, and quantitative gene expression profiling. Results: Loss of Hnf1aos1 produced distinct, diet-dependent alterations in hepatic lipid handling. Under chow conditions, knockdown mice exhibited selective hepatic cholesterol accumulation (6.10 ± 2.9 mg/g tissue vs. 3.51 ± 1.1 mg/g in controls), accompanied by dysregulation of cholesterol clearance pathways. In contrast, under HFD conditions, knockdown precipitated severe macrovesicular degeneration, with hepatic triglyceride levels approximately doubled relative to HFD-fed controls (51.72 ± 19.8 mg/g vs. 26.34 ± 11.9 mg/g) and a numerically elevated triglyceride-to-cholesterol ratio (TG:TC ≈ 6.1:1; p = 0.0621, trend). Chow/Kd mice gained significantly less weight than chow-fed controls, whereas HFD/Kd mice exhibited weight gain comparable to HFD controls despite severe hepatic steatosis. This paradoxical phenotype suggests impaired metabolic feedback at the post-transcriptional level, in which compensatory upregulation of Hnf1a mRNA is insufficient to suppress lipid-associated genes such as Cd36, despite profound lipid overload; however, HNF1A protein levels were not directly measured in this study. Conclusion: Collectively, these findings identify Hnf1aos1 as a regulator of hepatic lipid homeostasis whose loss produces a phenotype consistent with inappropriate lipid accumulation during nutrient excess, without defining the underlying molecular mechanism. Our results support a role for Hnf1aos1 in shaping hepatic metabolic plasticity and provide insight into lncRNA-associated MASLD phenotypes. Full article

Non-alcoholic fatty liver disease (NAFLD) is a primary metabolic disorder that threatens adolescent health globally, with no effective therapeutic agents currently available. Bellamya purificata is a traditional Chinese medicine categorized as "medicinal food", and polysaccharides are among its active components. However, its physicochemical structure remains poorly characterized, and no study has evaluated its effects on NAFLD. In this study, a homogeneous neutral polysaccharide, α-D-glucan (Mw = 6,412.704 kDa), was isolated from B. purificata. The structure of the polysaccharide was characterized using monosaccharide composition analysis, methylation analysis, NMR spectroscopy, and scanning electron microscopy. The backbone structure of the polysaccharide comprises →4)-α-D-Glcp-(1→ and →4,6)-α-D-Glcp-(1→, with side chains of α-D-Glcp-(1→ attached to the O-6 position of the 1→4,6)-α-D-Glcp-(1→ sugar residues. Additionally, QSPS-1D effectively reduced weight gain, hepatic lipid accumulation (TC and TG), and inflammatory responses (tnf-α and il-1β) in NAFLD zebrafish. Moreover, QSPS-1D alleviated dysbiosis by inhibiting harmful bacteria (e.g., Stenotrophomonas, Agrobacterium, and Chryseobacterium) and promoting beneficial microbiota (e.g., Rothia), which restored the Firmicutes-to-Bacteroidetes ratio. In parallel, it enhanced the expression of tight junction proteins (zo-1 and claudin-1), leading to the repair of the intestinal mucosal barrier. These findings suggest that B. purificata polysaccharides may be a potential functional food for early NAFLD intervention, with effects potentially associated with the modulation of the gut microbiota. Full article

In modern intensive mutton sheep farming, the high cost and limited supply of conventional feed resources necessitate the exploration of sustainable alternatives. Cotton stalks and sugar beet pulp, abundant agricultural by-products in China, have potential as ruminant feed after proper fermentation treatment, yet their systematic application in sheep production remains underinvestigated. This study evaluated the effects of replacing whole-plant corn microsilage with mixed fermented feed (cotton stalks and sugar beet pulp, 1:1 dry matter ratio) on Suffolk rams (n = 84, 4 months old). Animals were randomly assigned to four groups: control (CK, 0% replacement), MS30 (30% replacement), MS60 (60% replacement), and MS90 (90% replacement). After a 15-day adaptation, the 120-day feeding trial assessed growth performance, slaughter characteristics, meat quality, muscle metabolomics (LC-MS), and jejunal microbiota (16S rRNA sequencing). The MS60 group significantly outperformed the CK group in final body weight, carcass weight, and net weight gain (p < 0.01), slaughter rate (p < 0.05), and meat tenderness (p < 0.05). Fatty acid composition was optimized, with lower SFAs (p < 0.01) and higher MUFAs (p < 0.01). Metabolomic analysis revealed 206 differentially abundant metabolites, with significant enrichment in linoleic acid metabolism, unsaturated fatty acid biosynthesis, and primary bile acid synthesis pathways. The MS60 group exhibited significantly altered jejunal microbiota structure (p < 0.05), including increased Patescibacteria abundance (p < 0.05) and decreased Bifidobacterium (p < 0.001). Replacing 60% of whole-plant corn microsilage with cotton stalk–beet pulp mixed microsilage effectively improved production performance, meat quality, and fatty acid profiles in Suffolk rams, while modulating muscle metabolism and intestinal microbiota structure. These findings provide a practical strategy for sustainable sheep farming utilizing regional agricultural by-products. Full article

Reliable and fast radiation pattern prediction is critical for large-scale tightly coupled linear antenna arrays. Strong mutual coupling and finite-array edge effects limit the accuracy of conventional array factor methods, while full-wave simulations become computationally prohibitive for large arrays. To address this issue, a fast and efficient radiation pattern prediction method (FERPP) is proposed. For central elements, the far-field response is obtained from a calibrated reference array and extended through position-dependent phase compensation. For edge elements, responses are extracted from independent local full-wave simulations. All element responses are assembled into a global far-field response matrix, enabling direct radiation pattern synthesis using the extended method of maximum power transmission efficiency. Simulation results obtained with a 1024-element linear microstrip patch antenna array operating at 3.5 GHz, with small inter-element spacing, demonstrate close agreement with full-wave simulations. For a broadside single-beam case, the predicted peak gain is 29.10 dBi, compared with 29.02 dBi from full-wave simulation. For a scanned beam at 30°, the predicted peak gain is 28.22 dBi, while the full-wave result is 28.99 dBi. For an equal-weight three-beam configuration at −30°, 0°, and 30°, the proposed method yields a peak gain of 23.87 dBi, compared with 24.21 dBi from full-wave simulation. In terms of computational efficiency, the proposed method requires only about 1.8% of the computational time required for a full-wave simulation. These results demonstrate that the proposed FERPP method provides a practical and efficient solution for radiation pattern prediction and beamforming analysis of large-scale tightly coupled linear antenna arrays. Full article

The purpose of this study was to investigate the effects of different feeding-promoting substances added to high plant protein diets on the growth, antioxidant, serum biochemical parameters, immune, and feeding-related genes of Procambarus clarkii. A total of 450 crayfish (3.94 ± 0.03 g) were selected and randomly divided into six groups, with each group consisting of three replicates and 25 crayfish per replicate. The crayfish were fed a basal diet without attractant (control group) and five experimental diets supplemented with 0.4% betaine (BET), 0.4% trimetlylamine oxide (TMAO), 0.4% squid paste (SQU), 0.4% dimethyl-β-propiothetin (DMPT), and 0.4% taurine (TAU). The feeding trial lasted for 6 weeks. The results showed that compared with the control group, the BET, SQU, DMPT, and TAU groups significantly improved in growth performance, weight gain rate, and specific growth rate of crayfish. Compared with the control group, the BET, MTAO, and SQU groups significantly increased hepatopancreas SOD, CAT, and T-AOC. Histological results showed that compared with the control group, all feeding attractant groups could alleviate hepatopancreas tissue damage. Compared with the control group, the TMAO and SQU groups significantly reduced serum GLU content as well as ACP and AKP activities. The results of gene quantitative analysis showed that, compared with the control, TMAO significantly upregulated the expression of tlr, nf-kb, propo, hsp70, and tgf-β, while TAU significantly increased the expression of hsp70, hsp90 and nf-kb genes. Compared with the control group, the expression levels of tor, 4ebp1, and s6k1 in the TMAO group were significantly increased. Compared with the control group, the expression levels of leptin and npy genes in the DMPT group were significantly increased. In summary, the addition of attractants to high plant protein feed has the effects of promoting growth, enhancing antioxidant capacity, improving digestive enzyme activity, alleviating hepatopancreas injury, improving immunity, and promoting feeding. Full article

Wearable sensor-based human activity recognition (HAR) has gained growing significance in healthcare monitoring and assisted living systems. Although considerable advances have been made in classifying dynamic movements, stationary activities—such as sleeping, driving, and watching TV—remain difficult to distinguish owing to their weak sensor signatures and limited discriminative cues. This paper presents the multi-scale hybrid attention temporal network (MHAT-Net), a deep learning framework whose key architectural novelty lies in the parallel (non-sequential) dual-pathway temporal modeling: a BiGRU branch and a transformer encoder branch operate simultaneously on the same spatially encoded representation, combined via a learnable attention-based fusion module. This design targets the underexplored problem of distinguishing stationary activities from weak inertial sensor signatures. The architecture is built upon three integrated components: (1) a multi-branch CNN with kernel sizes three, five, and seven combined with channel attention for adaptive spatial feature extraction across multiple temporal scales; (2) parallel bidirectional gated recurrent unit (BiGRU) and transformer encoder pathways for jointly capturing short-range sequential patterns and long-range temporal correlations; and (3) an attention-driven fusion module that adaptively weights the outputs of both temporal branches. The model was assessed on a publicly available benchmark comprising three motionless activity categories collected from 25 participants via smartphone sensors. In 5-fold cross-validation, MHAT-Net attained 97.42% (±4.69%) accuracy with accelerometer data and 92.31% (±0.31%) with gyroscope data, substantially exceeding the accuracies of five baseline architectures: CNN, LSTM, BiLSTM, GRU, and BiGRU. Ablation experiments identified multi-scale spatial feature extraction as the most influential module (2.21–2.47% contribution), followed by the hybrid temporal modeling components. Cross-modality analysis confirmed that accelerometer signals yielded richer discriminative content for stationary activities, while MHAT-Net sustained consistent performance across both sensor types. The proposed integration of multi-scale spatial encoding, hybrid temporal modeling, and multi-level attention gives MHAT-Net the ability to reliably detect subtle activity-specific patterns, establishing a new benchmark in wearable sensor-based recognition for comprehensive daily behavior monitoring. Full article

Background: In recent years, artificial intelligence (AI) methods, including deep convolutional neural networks (CNNs), have gained increasing importance in supporting the automated analysis of echocardiograms. The aim of this study was to evaluate the impact of selected image artifacts—motion blur, acoustic shadowing, and speckle noise—on the performance of automatic classification of standard transthoracic echocardiographic (TTE) views using deep learning models. Methods: The analysis included 217 TTE video clips (2170 frames) covering apical views: two-chamber (A2C), three-chamber (A3C), four-chamber (A4C), and five-chamber (A5C). Two convolutional neural network architectures—ResNet-18 and ResNet-34—were applied, initialized with weights pretrained on the ImageNet dataset (transfer learning). In a limited comparative scope, EfficientNet-B0, a ViT model used as a frozen feature extractor combined with Logistic Regression, and a classical HOG + SVM model, were also included as reference methods. Classification performance was evaluated under conditions of controlled image degradation caused by motion blur, acoustic shadowing, and speckle noise. Results: All analyzed artifacts reduced classification performance, although the magnitude of this effect depended on artifact type. Speckle noise proved to be the most destructive, causing performance collapse across all evaluated methods at high severity. Motion blur and acoustic shadowing produced more differentiated degradation profiles. The ResNet models achieved the highest performance under reference conditions; however, after degradation, the ranking of models was no longer stable. In the comparative analysis, HOG + SVM showed the smallest relative performance loss under motion blur and the highest balanced accuracy under severe acoustic shadowing, whereas severe speckle remained critical for all models. Conclusions: Image quality degradation significantly impairs TTE view classification performance, and evaluation based solely on reference-quality images does not fully reflect model robustness to artifacts. These findings indicate the need to complement standard model evaluation with a structured robustness analysis under degraded imaging conditions and highlight the importance of training and validation settings that better reflect real clinical practice. Full article