Search Results (82,914)

Ginkgo is a multi-purpose economic tree species that plays a significant role in human production and daily life. The dry biomass of leaves serves as an accurate key indicator of the growth status of Ginkgo saplings and represents a direct source of economic yield. Given the characteristics of flexibility and high operational efficiency, affordable unmanned aerial vehicles (UAVs) have been utilized for estimating aboveground biomass in plantations, but not specifically for estimating leaf biomass at the individual sapling level. Furthermore, previous studies have primarily focused on image metrics while neglecting the potential of digital aerial photogrammetry (DAP) point cloud metrics. This study aims to investigate the estimation of crown-level leaf biomass in 3-year-old Ginkgo saplings subjected to different nitrogen treatments, using a synergistic approach that combines both image metrics and DAP metrics derived from UAV RGB images captured at varying flight heights (30 m, 60 m, and 90 m). In this study, image metrics (including the color and texture feature parameters) and DAP point cloud metrics (encompassing crown-level structural parameters, height-related and density-related metrics) were extracted and evaluated for modeling leaf biomass. The results indicated that models that utilized both image metrics and point cloud metrics generally outperformed those relying solely on image metrics. Notably, the combination of image metrics obtained from the 60 m flight height with DAP metrics derived from the 30 m height significantly enhanced the overall modeling performance, especially when optimal metrics were selected through a backward elimination approach. Among the regression methods employed, Gaussian process regression (GPR) models exhibited superior performance (CV-R² = 0.79, rRMSE = 25.22% for the best model), compared to Partial Least Squares Regression (PLSR) models. The common critical image metrics for both GPR and PLSR models were found to be related to chlorophyll (including G, B, and their normalized indices such as NGI and NBI), while key common structural parameters from the DAP metrics included height-related and crown-related features (specifically, tree height and crown width). This approach of integrating optimal image metrics with DAP metrics derived from multi-height UAV imagery shows great promise for estimating crown-level leaf biomass in Ginkgo saplings and potentially other tree crops. Full article

Background: Sarcopenia, characterized by muscle mass decline due to aging or other causes, is exacerbated by decreased estrogen levels after menopause in women. Isoflavones, a class of flavonoids acting on estrogen receptors, may have beneficial effects on metabolic disorders. We examined these effects in ovariectomized mice fed a high-fat, high-sucrose diet (HFHSD). Methods: At 7 weeks old, female C57BL6/J mice (18–20 g, n = 12) underwent bilateral ovariectomy (OVX), and were then fed a high-fat, high-sucrose diet starting at 8 weeks of age. Half of the mice received isoflavone water (0.1%). Metabolic analyses, including glucose and insulin tolerance tests, were conducted. Muscle analysis involved grip strength assays, next-generation sequencing, quantitative RT–PCR, and western blotting of skeletal muscle after euthanizing the mice at 14 weeks old. Additionally, 16S rRNA gene sequence analysis of the gut microbiota was performed. Results: The results demonstrated that isoflavone administration did not affect body weight, glucose tolerance, or lipid metabolism. In contrast, isoflavone-treated mice had higher grip strength. Gene expression analysis of the soleus muscle revealed decreased Trim63 expression, and western blotting showed inactivation of muscle-specific RING finger protein 1 in isoflavone-treated mice. Gut microbiota analysis indicated higher Bacteroidetes and lower Firmicutes abundance in the isoflavone group, along with increased microbiota diversity. Gene sets related to TNF-α signaling via NF-κB and unfolded protein response were negatively associated with isoflavones. Conclusions: Isoflavone intake alters gut microbiota and increases muscle strength, suggesting a potential role in improving sarcopenia in menopausal women. Full article

Background/Objectives: This study aims to evaluate the computed tomography (CT) scans of glaucoma patients using prostaglandin analogs (PGA) in one eye, investigate findings associated with prostaglandin-associated periorbitopathy (PAP), and compare these findings with those of the contralateral eyes. Methods: Patients with open-angle glaucoma who had CT images of the orbital region taken for another reason at least one month after starting PGA treatment in one eye were included in the study. Enophthalmos measurements from thin-slice CT images, along with 3D volume measurements of orbital fat tissue, periorbital muscles, and the optic nerve, were performed. Ophthalmological examination findings and treatment information were collected. The values were compared with those of the contralateral eyes of the same patients not using PGA. Intraclass correlation coefficients (ICCs) were computed to evaluate measurement repeatability. Results: Forty patients were included in the study. Among them, 29 (72.5%) used latanoprost, 9 (22.5%) used bimatoprost, and 2 (5%) used travoprost. The mean enophthalmos values on the treated side (15.5 ± 2.0 mm) were lower than on the untreated side (16.1 ± 1.4 mm), but this difference was not statistically significant (p = 0.07). In 29 patients (72.5%), enophthalmos measurements were smaller on the treated side, with 7 patients (17.5%) showing a difference of 2 mm or more. No significant correlation was found between the duration of PGA use and enophthalmos measurements (p = 0.768 r = −0.048). Additionally, no significant differences were found in orbital fat volume, total extraocular muscle volume, and optic nerve volume (p > 0.05). ICC values demonstrated excellent reliability (ICC > 0.75) for all measurements. Conclusions: We did not find significant differences in enophthalmos measurements, orbital fat volume, total muscle volume, and optic nerve volume between the PGA-treated and untreated eyes. Full article

The Leaf Area Index (LAI) is a critical parameter that sheds light on the composition and function of forest ecosystems. Its efficient and rapid measurement is essential for simulating and estimating ecological activities such as vegetation productivity, water cycle, and carbon balance. In this study, we propose to combine high-resolution GF-6 2 m satellite images with the LESS three-dimensional RTM and employ different machine learning algorithms, including Random Forest, BP Neural Network, and XGBoost, to achieve LAI inversion for forest stands. By reconstructing real forest stand scenarios in the LESS model, we simulated reflectance data in blue, green, red, and near-infrared bands, as well as LAI data, and fused some real data as inputs to train the machine learning models. Subsequently, we used the remaining measured LAI data for validation and prediction to achieve LAI inversion. Among the three machine learning algorithms, Random Forest gave the highest performance, with an R² of 0.6164 and an RMSE of 0.4109, while the BP Neural Network performed inefficiently (R² = 0.4022, RMSE = 0.5407). Therefore, we ultimately employed the Random Forest algorithm to perform LAI inversion and generated LAI inversion spatial distribution maps, achieving an innovative, efficient, and reliable method for forest stand LAI inversion. Full article

Background/Objectives: Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by social interaction difficulties, repetitive behaviors, and immune dysregulation with elevated pro-inflammatory markers. Autophagic deficiency also contributes to social behavior deficits in ASD. Histamine H3 receptor (H3R) antagonism is a potential treatment strategy for brain disorders with features overlapping ASD, such as schizophrenia and Alzheimer’s disease. Methods: This study investigated the effects of sub-chronic systemic treatment with the H3R antagonist E159 on social deficits, repetitive behaviors, neuroinflammation, and autophagic disruption in male BTBR mice. Results: E159 (2.5, 5, and 10 mg/kg, i.p.) improved stereotypic repetitive behavior by reducing self-grooming time and enhancing spontaneous alternation in addition to attenuating social deficits. It also decreased pro-inflammatory cytokines in the cerebellum and hippocampus of treated BTBR mice. In BTBR mice, reduced expression of autophagy-related proteins LC3A/B and Beclin 1 was observed, which was elevated following treatment with E159, attenuating the disruption in autophagy. The co-administration with the H3R agonist MHA (10 mg/kg, i.p.) reversed these effects, highlighting the role of histaminergic neurotransmission in observed behavioral improvements. Conclusions: These preliminary findings suggest the therapeutic potential of H3R antagonists in targeting neuroinflammation and autophagic disruption to improve ASD-like behaviors. Full article

Maurotoxin (MTX) is a 34-residue peptide from Scorpio maurus venom. It is reticulated by four disulfide bridges with a unique arrangement compared to other scorpion toxins that target potassium (K⁺) channels. Structure–activity relationship studies have not been well performed for this toxin family. The screening of Scorpio maurus venom was performed by different steps of fractionation, followed by the ELISA test, using MTX antibodies, to isolate an MTX-like peptide. In vitro, in vivo and computational studies were performed to study the structure–activity relationship of the new isolated peptide. We isolated a new peptide designated MTX1, structurally related to MTX. It demonstrated toxicity on mice eight times more effectively than MTX. MTX1 blocks the Kv1.2 and Kv1.3 channels, expressed in Xenopus oocytes, with IC₅₀ values of 0.26 and 180 nM, respectively. Moreover, MTX1 competitively interacts with both ¹²⁵I-apamin (IC₅₀ = 1.7 nM) and ¹²⁵I-charybdotoxin (IC₅₀ = 5 nM) for binding to rat brain synaptosomes. Despite its high sequence similarity (85%) to MTX, MTX1 exhibits a higher binding affinity towards the Kv1.2 and SKCa channels. Computational analysis highlights the significance of specific residues in the β-sheet region, particularly the R27, in enhancing the binding affinity of MTX1 towards the Kv1.2 and SKCa channels. Full article

This study’s aim was an analysis regarding selected determinants of diet health quality in a group of elite Polish female team sport players. Relationships were assessed between age, sport experience, personal resources and personality traits with regard to the Big Five model and the pro-Health (pHDI-10) and non-Healthy (nHDI-14) Diet Indices. This study was conducted among 181 women (median age—25 years; sport experience—7 years) with the use of the Beliefs and Eating Habits Questionnaire (KomPAN), Generalised Self-Efficacy Scale (GSES), Multidimensional Health Locus of Control Scale (MHLC-B) and NEO-PI-R personality inventory. Statistical analysis was carried out via the Wilcoxon signed-rank test, Kruskal–Wallis’s ANOVA, Spearman’s rank correlation coefficient and forward stepwise regression at a significance level of α = 0.05. Multivariate regression analysis indicated that the value of the pro-Health Diet Index (pHDI-10) was positively explained by professional experience and extraversion, while negatively by openness to experiences (12% of the pHDI-10 variance). In turn, a higher value of the non-Healthy Diet Index (nHDI-14) was associated with the discipline of basketball (2% of the nHDI-14 variance). In summary, the demonstrated diet health quality was low and the predictive significance of competitive experience as well as type of discipline and selected personality traits was exhibited for diet quality among female team sport players. Full article

The aim of this study is to investigate body posture, physical exercises, head–neck relationship, and sleep quality among university students. A total of 96 students, with an average age of 20.86 ± 1.24 years and an average BMI of 23.41 ± 2.56, voluntarily participated in the study. The REEDCO Posture Evaluation (RPE) was used to assess the participants’ body posture scores. Head and neck measurements were taken using the Apecs-AI Posture Evaluation and Correction System^® (Apecs Posture Analysis Pro Plus Version 8.2.6). Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). Pearson correlation analysis indicated that increased caffeine consumption was associated with poorer sleep quality (r = 0.267, p < 0.05). Additionally, increased participation in physical activities was associated with improved sleep quality, with those engaging in sports having better sleep quality scores (r = −0.278, p < 0.05). As physical activity increased, REEDCO scores decreased (r = −0.423, p < 0.05), while scores for right head (r = 0.210, p < 0.05) and left head (r = 0.247, p < 0.05) increased. Significant negative correlations were found between REEDCO scores and right head (r = −0.296, p < 0.05) and left head (r = −0.463, p < 0.05) scores. In conclusion, due to the limited number of studies investigating head–neck relationships and sleep quality, definitive conclusions cannot be drawn; further and more comprehensive research is needed. Full article

In linear elastic fracture mechanics, the stress intensity factor describes the magnitude of the stress singularity near a crack tip caused by remote stress and is related to the rate of fatigue crack growth. The literature lacks SIF solutions for cracks emanating from a three-dimensional semi-ellipsoidal pit. This study undertakes a comprehensive parametric investigation of the Mode I stress intensity factor ${(K}_I)$ concerning cracks originating from a semi-ellipsoidal pit in a plate. This work utilizes finite element analysis, controlled by Python scripts, to conduct an extensive study on the effect of various pit dimensions and crack lengths on $K_I$. Two cracks in the shape of a circular arc are introduced at the pit mouth perpendicular to the loading direction. The $K_I$ values are calculated using the displacement extrapolation method. The effect of normalized geometric parameters pit-depth-to-pit-width $(a/2c$), pit-depth-to-plate-thickness $(a/t)$, and crack-radius-to-pit-depth $(R/a)$ are investigated. The crack-radius-to-pit-depth $(R/a)$ is found to be the dominating parameter based on correlation analysis. The data obtained from 216 FEA simulations are incorporated into a predictive model using a k-dimensional (k-d) tree and k-Nearest Neighbour (k-NN) algorithm. Full article

Background/Objectives: Patients with endometriosis still respond poorly to progestins due to progesterone resistance associated with microRNAs (miRNAs). The aim of this study was to investigate the expression of selected miRNAs, estrogen receptor (ER)α, ERβ, progesterone receptor (PR)-A and PR-B and to determine the target genes of upregulated miRNAs in endometriosis. Methods: In this study, 18 controls, 18 eutopic and 18 ectopic samples were analysed. Profiling and validation of miRNAs associated with functions of endometriosis were performed using next-generation sequencing (NGS) and qRT-PCR. At the same time, the expression of ERα, ERβ, PR-A and PR-B was also determined using qRT-PCR. Target prediction was also performed for miR-199a-3p, miR-1-3p and miR-125b-5p using StarBase. Results: In this study, NGS identified seven significantly differentially expressed miRNAs, of which six miRNAs related to the role of endometriosis were selected for validation by qRT-PCR. The expression of miR-199a-3p, miR-1-3p, miR-146a-5p and miR-125b-5p was upregulated in the ectopic group compared to the eutopic group. Meanwhile, ERα and ERβ were significantly differentially expressed in endometriosis compared to the control group. However, the expressions of PR-A and PR-B showed no significant differences between the groups. The predicted target genes for miR-199a-3p, miR-1-3p and miR-125b-5p are SCD, TAOK1, DDIT4, LASP1, CDK6, TAGLN2, G6PD and ELOVL6. Conclusions: Our findings demonstrated that the expressions of ERα and ERβ might be regulated by miRNAs contributing to progesterone resistance, whereas the binding of miRNAs to target genes could also contribute to the pathogenesis of endometriosis. Therefore, miRNAs could be used as potential biomarkers and for targeted therapy in patients with endometriosis. Full article

Yaks are one of the important livestock on the Qinghai–Tibet Plateau, providing abundant dairy and meat products for the local people. The formation of these dairy and meat products mainly relies on the microbiota in their gastrointestinal tract, which digests and metabolizes plant feed. The yak’s gastrointestinal microbiota is closely related to the health and production performance of the host, but the molecular mechanisms of diet-induced effects in intensively farmed yaks remain to be elucidated. In this study, 40 chyme samples were collected from the four stomach chambers of 10 intensively farmed yaks, and the bacterial diversity and bile acid changes in the rumen (SFRM), reticulum (SFRC), omasum (SFOM), and abomasum (SFAM) were systematically analyzed using 16S rRNA sequencing and bile acid metabolism. Our results showed that the gastrointestinal microbiota mainly distributes in the four-chambered stomach, with the highest microbial diversity in the reticulum. There is a highly negative correlation among the microbiota in the four chambers. The dominant bacterial phyla, Bacteroidota and Firmicutes, were identified, with Rikenellaceae_RC9_gut_group being the dominant genus, which potentially helps maintain short-chain fatty acid levels in the stomach. In contrast, the microbiome within the four stomach chambers synergistically and selectively altered the content and diversity of bile acid metabolites in response to intensive feeding. The results of this study provide new insights into the microbiota and bile acid metabolism functions in the rumen, reticulum, omasum, and abomasum of yaks. This can help uncover the role of gastrointestinal microbiota in yak growth and metabolic regulation, while also providing references for improving the production efficiency and health of ruminants. Full article

Urban Heat Islands are a major environmental and public health concern, causing temperature increase in urban areas. This study used satellite imagery and machine learning to analyze the spatial and temporal patterns of land surface temperature distribution in the Metropolitan Area of Merida (MAM), Mexico, from 2001 to 2021. The results show that land surface temperature has increased in the MAM over the study period, while the urban footprint has expanded. The study also found a high correlation ($r>$ 0.8) between changes in land surface temperature and land cover classes (urbanization/deforestation). If the current urbanization trend continues, the difference between the land surface temperature of the MAM and its surroundings is expected to reach 3.12 °C ± 1.11 °C by the year 2030. Hence, the findings of this study suggest that the Urban Heat Island effect is a growing problem in the MAM and highlight the importance of satellite imagery and machine learning for monitoring and developing mitigation strategies. Full article

Fractional vegetation cover (FVC) is a crucial indicator for measuring the growth of surface vegetation. The changes and predictions of FVC significantly impact biodiversity conservation, ecosystem health and stability, and climate change response and prediction. Southwest China (SWC) is characterized by complex topography, diverse climate types, and rich vegetation types. This study first analyzed the spatiotemporal variation of FVC at various timescales in SWC from 2000 to 2020 using FVC values derived from pixel dichotomy model. Next, we constructed four machine learning models—light gradient boosting machine (LightGBM), support vector regression (SVR), k-nearest neighbor (KNN), and ridge regression (RR)—along with a weighted average heterogeneous ensemble model (WAHEM) to predict growing-season FVC in SWC from 2000 to 2023. Finally, the performance of the different ML models was comprehensively evaluated using tenfold cross-validation and multiple performance metrics. The results indicated that the overall FVC in SWC predominantly increased from 2000 to 2020. Over the 21 years, the FVC spatial distribution in SWC generally showed a high east and low west pattern, with extremely low FVC in the western plateau of Tibet and higher FVC in parts of eastern Sichuan, Chongqing, Guizhou, and Yunnan. The determination coefficient R² scores from tenfold cross-validation for the four ML models indicated that LightGBM had the strongest predictive ability whereas RR had the weakest. WAHEM and LightGBM models performed the best overall in the training, validation, and test sets, with RR performing the worst. The predicted spatial change trends were consistent with the MODIS-MOD13A3-FVC and FY3D-MERSI-FVC, although the predicted FVC values were slightly higher but closer to the MODIS-MOD13A3-FVC. The feature importance scores from the LightGBM model indicated that digital elevation model (DEM) had the most significant influence on FVC among the six input features. In contrast, soil surface water retention capacity (SSWRC) was the most influential climate factor. The results of this study provided valuable insights and references for monitoring and predicting the vegetation cover in regions with complex topography, diverse climate types, and rich vegetation. Additionally, they offered guidance for selecting remote sensing products for vegetation cover and optimizing different ML models. Full article

Let $p,q\ge 1$ be two real numbers such that $\frac{1}{p}+\frac{1}{q}=1$, and let $a,b\in \mathbb{R}$ be two parameters defined on the domain of a function, for example, f. Based on the well known Hölder inequality, we propose a generic inequality of the form $\left|f(\frac{a}{p}+\frac{b}{q})\right|\le \left|f\left(a\right){|}^{\frac{1}{p}}\right|f\left(b\right){|}^{\frac{1}{q}},$ and show that many basic special functions, such as the gamma and polygamma functions, Riemann zeta function, beta function and Gauss and confluent hypergeometric functions, satisfy this type of inequality. In this sense, we also present some particular inequalities for the Gauss and confluent hypergeometric functions to confirm the main obtained inequalities. Full article

Biased agonists of G-protein-coupled receptors (GPCRs) have emerged as promising selective modulators of signaling pathways by offering therapeutic advantages over unbiased agonists to minimize side effects. The dopamine D3 receptor (D3R), a pivotal GPCR in the central nervous system, has gained significant attention as a therapeutic target for neurological diseases, including Parkinson’s disease (PD), addiction, psychosis, depression, and anxiety. We have recently designed and tested SK609, a G-protein biased D3R selective agonist, and demonstrated its efficacy in reducing motor impairment and improving cognitive effects in a rodent model of PD. The molecular mechanism by which SK609 recruits G-protein but not β-arrestin pathways is poorly understood. Utilizing all-atom molecular dynamics simulations, we investigated the distinct conformational dynamics imparted by SK609 and the reference unbiased agonist Pramipexole (PRX). Results from these studies show that the flexibility of transmembrane 3 is key to unbiased signaling, with a ~30° and ~17° shift in tilt angle in the D3R-Gi and D3R-βarrestin2 complexes, respectively. Additionally, untargeted phosphoproteomics analysis reveals unique phosphorylation sites by SK609 and PRX in D3R. These results suggest that SK609 induces conformational changes and unique phosphorylation patterns that promote interactions with G-proteins and are not conducive for β-arrestin2 recruitment and signaling. Full article