Search Results (19,665)

Current 3D tumor models for aggressive breast cancers inadequately recapitulate the native tumor microenvironment (TME), leading to poor translational potential. There is a critical need for models capable of mimicking the unique biochemical signals present in the TME. To address this gap, breast tissue and a patient-derived xenograft tumor were decellularized and processed to produce breast tissue- and tumor-specific decellularized extracellular matrices (dECM). Histology confirmed complete cellular removal while maintaining the ECM. Further, DNA content was significantly reduced while ECM composition (POSTN, COLI, FN1) was retained. Breast dECM was incorporated (0, 5, 10, 20, and 50 µg/mL) with triple-negative breast cancer cell lines to generate spheroids. Imaging and histology demonstrated that cells in low dECM (5 and 10 µg/mL) formed compact singular spheres, while higher dECM concentrations (20 and 50 µg/mL) resulted in cells concentrated on the outer edge of the sphere and irregular sphere circularity. RNA-sequencing of MDA-MB-231 dECM spheres demonstrated that gene changes were mediated by both the inclusion of dECM and its composition. High-density tumor dECM upregulated genes associated with metastasis, while high-density breast dECM enhanced tumor suppressors and anti-metastasis genes. These findings indicate that dECM provides physiological cues in 3D tumor models by incorporating TME. Full article

Mounting acaricide resistance in Tetranychus mexicanus (McGregor) (Acari: Tetranychidae), among the most damaging phytophagous mites in tropical and subtropical crops, has intensified the search for botanical alternatives. An oil-in-water nanoemulsion of Thymus vulgaris essential oil (TVEO-NE) was developed and evaluated for lethal and sublethal effects on adult females of T. mexicanus. TVEO, composed mainly of thymol (45%) and p-cymene (37%), was formulated by low-energy emulsification yielding stable dispersions (~200 nm; PDI < 0.25; zeta potential of −22.2 mV). At 30.0 mg a.i./mL, TVEO-NE caused 68.3% corrected mortality at 72 h and suppressed fecundity by ~44–52%; vehicle controls exerted only moderate effects, identifying the essential oil as the primary bioactive driver. Morphological examination revealed collapse of female idiosomata and disruption of excretory pellet architecture, corroborating the bioassay data. Molecular docking against a cathepsin L homology model revealed that thymol and p-cymene interact exclusively via hydrophobic contacts and display substantially lower ChemPLP fitness scores than the reference cysteine protease inhibitor E64, indicating weak predicted binding affinity and arguing against enzyme inhibition as the primary mechanism. Taken together, bioassay, morphological, and docking are consistent with supporting membrane partitioning as a plausible primary mode of action, positioning TVEO-based nanoemulsions as promising botanical tools for T. mexicanus management. Full article

Background: Endothelial dysfunction and renal injury are emerging as a common feature of long COVID, especially in those with hypertension. It is not yet well characterised whether SARS-CoV-2 infection exacerbates podocyte dysfunction, fibrotic signalling and renal hemodynamic remodelling, over and above the effects of hypertension alone and there are no reliable early biomarkers in this population. Methods: We conducted a comparative cross-sectional study with prospective 6-month treatment response follow-up in 120 adult patients (aged 30–60 years) with essential hypertension (Stage I, II or III; n = 40 per stage), at Bukhara Regional Multidisciplinary Hospital. Each stage subgroup was further divided into post-COVID (3–6 months after recovery; n = 20) and non-COVID (n = 20) strata. Patients with diabetes, known chronic kidney disease, previous myocardial infarction or stroke and other major comorbidities were excluded. Serum cystatin-C, creatinine, aldosterone, TGF-β1 and VEGF-A; urinary nephrin and microalbumin; cystatin-C-derived eGFR (CKD-EPI) and oral protein-loaded renal functional reserve (RFR); and renal Doppler indices (Vps, Ved, RI, PI) of the main, segmental and interlobar arteries were assessed before and after 6 months of guideline-based renin–angiotensin–aldosterone system (RAAS) blockade (enalapril 5–10 mg or azilsartan 40–80 mg, ±eplerenone). Comparisons were made by Student’s t-test—associations by Pearson correlation. Results: At baseline, post-COVID hypertensive patients exhibited consistently higher endothelial–podocyte injury markers than non-COVID counterparts. Urinary nephrin was elevated across all stages (Stage I: 126.5 ± 9.1 vs. 91.9 ± 8.3 pg/mL, p < 0.01; Stage III: 203.3 ± 11.2 vs. 164.5 ± 9.7 pg/mL, p < 0.05), as were VEGF-A (Stage III: 286.1 ± 16.4 vs. 223.2 ± 12.6 pg/mL, p < 0.01) and TGF-β1 (Stage III: 186.4 ± 10.1 pg/mL, 1.3-fold higher; p < 0.01). The detection of microalbuminuria was 100% in Stage III post-COVID patients and 85% in non-COVID controls. The post-COVID groups had selective loss of renal functional reserve (7.8 ± 1.1% in Stage III compared to 12.5 ± 1.6% in non-COVID controls, p < 0.001). Nephrinuria correlated strongly with RFR (r = −0.824, p < 0.001), eGFR (r = −0.797, p < 0.001) and aldosterone (r = 0.613, p < 0.001). Six months of RAAS blockade reduced nephrinuria, microalbuminuria and TGF-β1 in both arms but the magnitude of biomarker reduction appeared smaller in the post-COVID group, particularly in Stage III. Conclusions: Long COVID appears to be associated with persistent endothelial dysfunction and podocyte injury in hypertensive patients. These results indicate that nephrinuria, VEGF-A, TGF-β1 and renal functional reserve are potential exploratory markers of endothelial and renal abnormalities in hypertensive patients following COVID-19. Before clinical utility can be determined, larger studies with multivariable modelling, diagnostic-performance analyses and correction for multiple testing are needed. The differences in biomarker response between groups observed in this study need to be confirmed in larger prospective studies with multivariable modelling and formal interaction analyses. Full article

The bilingual advantage hypothesis proposes that bilingual children will display greater executive function (EF) skills compared to their monolingual peers. However, most research on this topic neglects to include monolingual children from both language groups for comparison, thus confounding language status and cultural context. To address this gap, we administered an extensive battery of EF tasks to 189 typically developing children ages 47–95 months (M_age = 71.47, SD = 11.68, 42.9 % Female) drawn from three language status groups: Korean-English Bilingual and English Monolingual (both in the northwestern United States) and Korean Monolingual (South Korea). Korean-English Bilingual children scored significantly higher on the EF composite than Korean Monolingual children, even after controlling for child age and verbal ability. Both English Monolingual and Korean-English Bilingual children waited significantly longer during a delay-of-gratification task than Korean Monolingual children when controlling for age and verbal ability. Korean-English Bilingual children outperformed English Monolingual and Korean Monolingual children on the Comprehensive Test of Nonverbal Intelligence. There were no significant differences between language status groups on the other individual EF tasks after adjusting for multiple comparisons. Taken together, we did not find consistent support for a bilingual advantage in EF skills: Country of residence also played a role, with children living in the United States outperforming children living in Korea in some cases. Full article

Accurate solar irradiance forecasting is important for efficient planning of solar energy systems, renewable energy integration, and data-driven energy management in smart cities. This becomes more essential in regions with limited measured data availability and varying climatic conditions, where reliable forecasting can support urban energy planning and smart grid operation. Pakistan faces a scarcity of available solar data and has varying climatic conditions, which makes it ideal for such a study. This study utilizes nine geographically diverse stations to develop a benchmark framework for direct one-step-ahead hourly solar irradiance forecasting. The dataset was subjected to data preprocessing, feature engineering, and multi-model evaluation. A staged approach was adopted for feature selection, starting from a base model comprising three input variables: extraterrestrial radiation, solar zenith angle, and relative humidity. Features were added in an incremental order, which resulted in an optimized four-variable input set through the addition of a lagged clearness index to the base model. The forecasting models evaluated in this study, using these input variables, were ANN, NAR, NARX, LSTM, GRU, SARIMA, and Prophet. Deep learning models outperformed the other considered approaches, with LSTM showing the best overall benchmark performance with an average RMSE of 92.93 W/m², MAE of 66.56 W/m², and R-Squared of 0.872. The performance trends were broadly consistent across the evaluated stations, indicating stable behaviour within the adopted dataset and experimental setup. The study shows that a compact and physically interpretable input feature set, used with recurrent deep learning models, provides an effective solution for hourly solar irradiance forecasting, especially in locations with varying climatic conditions. The proposed benchmark can support smart city applications related to distributed solar generation, energy-aware urban planning, and intelligent operation of renewable-rich power systems. Full article

Background/Objectives: Numerous natural compounds have been reported to exhibit anti-virulence properties against pathogenic bacteria. Particularly, plants constitute a rich source of anti-quorum-sensing (QS) and anti-biofilm compounds with highly diverse chemical structures. Notably, several studies reported that plant-derived pentacyclic triterpenoids exert anti-biofilm activity against Pseudomonas aeruginosa without affecting bacterial viability, suggesting that this class of naturally occurring chemical compounds may represent a source of potent and clinically relevant anti-biofilm agents. Methods: To further investigate this hypothesis, we evaluated several commercially available pentacyclic triterpenoid acids of the oleanane, ursane and lupane types for their potential impact on QS mechanisms and biofilm formation in the P. aeruginosa PAO1 model strain. Results: Oleanane-type (oleanolic acid and maslinic acid), ursane-type (ursolic acid and corosolic acid) and lupane-type (betulinic acid) triterpenoids inhibited the expression of the QS-regulated lasB and rhlA genes as well as biofilm formation, without affecting bacterial growth. Among tested compounds, oleanolic and ursolic acids, at 400 µM, exhibited the strongest anti-biofilm activities, with 45% and 40% inhibition, respectively. Fluorescence microscopy revealed a marked disorganization of biofilm architectures, with bacterial communities failing to establish compact cell-to-cell attachment and confluent microcolonies. Further analyses indicated that these triterpenoid acids did not affect the expression of QS-regulator genes (lasR/I and rhlR/I), suggesting that their impact on lasB and rhlA expression and biofilm formation is independent of the las and rhl systems. Conclusions: These findings suggest that oleanane and ursane triterpenoid acids represent promising chemical backbones for the development of strategies aimed at inhibiting P. aeruginosa biofilm formation. Full article

Proteins are the most common targets for antibody discovery and vaccine development, but their sequence variability can limit the breadth of resulting antigens. Lipids represent an alternative class of antigens due to their structural conservation and roles in host–pathogen interactions. Here, we describe the development and optimization of an in vitro antibody selection workflow using lipid-containing nanodiscs as antigen presentation platforms to enable phage and yeast display selections under conditions adapted for these non-protein targets. Lipopolysaccharide (LPS) nanodiscs were first used as a model system to evaluate selection strategies, including competitive and subtractive approaches to reduce non-specific binders, yielding peptide and single-chain variable fragment (scFv) binders that were affinity matured to improve binding signals. The same approach was subsequently used to select scFv antibodies that recognize lipid nanodiscs prepared from Yersinia pestis membrane lipid extracts. These antibodies show binding to lipid nanodiscs derived from Y. pestis, with evidence of selectivity relative to control nanodiscs. Overall, this work establishes a workflow for antibody selection against lipid-containing nanodisc antigens and highlights practical considerations associated with these targets. The approach may be useful for generating affinity reagents to membrane-associated lipids, although further characterization is required to define antigen specificity and functional activity. Full article

Heat stress occurs when total environmental and metabolic heat production is greater than an animal’s ability to dissipate that heat. Heat stress negatively impacts feeder cattle performance and welfare. Limited research has been conducted to determine if feeding cattle in the evening, thereby shifting their metabolic heat production to a cooler period of the day, can help mitigate heat stress. This pen-level randomized controlled trial evaluated the effects of evening feeding (PM; feedings at 2000, 2300, and 0200 h; n = 24 pens) versus morning feeding (AM; feedings at 0500, 0800, and 1200 h; n = 24 pens) on terminally sorted steer performance in a commercial feedyard in the Pacific Northwest. Data collection included feed delivery, water consumption, health events, open mouth breathing prevalence, and carcass traits. Linear and generalized linear mixed-effects models were used to determine potential differences between treatment group and temperature-humidity index (THI; <80 versus ≥80). Only 14% of the total study days had a THI ≥ 80, indicating little to no heat stress impacts. There were no differences found between PM and AM for any outcome (p < 0.05). Regardless of treatment group, water consumption tended (p = 0.07) to increase, and open mouth breathing significantly (p < 0.05) increased on days with THI ≥ 80. Further research is warranted to assess evening feeding as a heat stress mitigation strategy in a feedyard setting. Full article

The Terziali is a shear-hosted orogenic gold prospect located in the Central Anatolian Crystalline Complex, Türkiye. This study focuses on soil geochemistry, element correlations, background and threshold values, and evaluates exploration implications over a survey area of 35.5 km². A total of 1826 soil samples were collected from the B horizon using a grid of 100 × 50 m and were analyzed using ICP-AES, ICP-MS, and fire assay techniques. Statistical techniques of median + 2MAD threshold calculations, descriptive statistics, Kolmogorov–Smirnov tests, correlation analysis, hierarchical clustering, and Q–Q plots were carried out to identify geochemical anomalies. The data demonstrate Au threshold (28 ppb) and peak concentration (460 ppb), non-normal distributions characterized by strong positive skewness, revealing the outliers linked to mineralization. Soil geochemistry indicates a moderate association between Au and As in the four-acid dataset (r = 0.465), although the correlations between Au and Sb and Ag and W are relatively weak. The spatial analysis indicates that Au anomalies are predominantly linked to the NW–SE-oriented Demirli Thrust Fault. As displays extensive dispersion halos surrounding the gold anomalies; it establishes itself as an efficient pathfinder element. Conversely, Sb and W exhibit unique anomaly patterns, whereas Ag patterns are weak and dispersed. The Terziali prospect provides a substantial geochemical framework for identifying structurally controlled orogenic gold systems in Central Anatolia and the western Tethyan metallogenic belt. Full article

Global Navigation Satellite System Reflectometry (GNSS-R), with its all-weather observation capability and low-cost advantage, provides an innovative solution for dynamic sea ice monitoring. In this paper, multi-dimensional features, including the GNSS-R Normalised Integrated Delay Waveform (N-IDW), the scattering coefficient and incidence angle derived from FY-3F satellite data, and the Delay Doppler Map (DDM) bistatic radar cross-section coefficient, are jointly used as model inputs. Experimental results show that this method successfully integrates FY-3F satellite data for sea ice thickness (SIT) retrieval, confirming the viability of employing FY-3F GNSS-R data for this purpose. An assessment of different algorithms in terms of their retrieval performance is conducted—covering RF, DT, KNN, SVM, ET, GBR, XGBR, and LR—and uses these eight models as base learners to construct different stacking models. After comparison, the ensemble stacking model using ET, LR, XGBR, and GBR as base models achieves the best retrieval performance. The MSE of this model for sea ice thickness retrieval reaches 0.0112 m, the RMSE reaches 0.1026 m and the correlation coefficient reaches 0.8876. Full article

The genetic and antigenic diversity of H5Nx HPAI Gs/GD lineage continues to be a great challenge facing conventional inactivated vaccines. To overcome this challenge, a recombinant herpes virus of turkey (rHVT) vaccine expressing the viral protein 2 (VP2) of infectious bursal disease (IBD) and H5, rHVT+IBD+H5, was developed using computationally optimized broadly reactive antigen (COBRA) technology. In the current study, the protective efficacy of a commercially available vector trivalent vaccine rHVT+IBD+H5 using COBRA technology was assessed. A total of 120 commercial broilers were divided equally into six groups (G1B–G6B). The chickens in G1B–G3B were challenged with the most recent circulating HPAI-H5N1 clade 2.3.4.4.b Egyptian isolate (GenBank accession No. OQ933425) at 28 days old (DO), while the chickens in G4B and G5B were kept as vaccinated (as G1B and G2B, respectively) and non-challenged, and G6B was the non-vaccinated non-challenged group. In G1B, the chickens were vaccinated with Vaxxitek^® rHVT+IBD+H5 at 1 DO and boostered with a commercially available subunit Baculovirus bivalent inactivated H5+ND (Volvac^® B.E.S.T AI+ND) at 10 DO and had a 100% survival rate. The standalone vaccinated chicken G2B, using rHVT+IBD+H5 at 1 DO, had a highly significant survival rate (90%) vs. 0% (100% mortality) in the non-vaccinated challenged control, G3B. All the vaccinated groups had higher seroconversion at 45 DO especially using H5-coated antigen plates for the enzyme-linked immunosorbent assay (ELISA) test. The viral shedding titers and time were evaluated using a quantitative real-time polymerase chain reaction (RT-qPCR) in the collected oropharyngeal and cloacal swabs at 3, 5, 7, and 10 days post-challenge (DPC). In conclusion, vaccination with rHVT+IBD+H5 either as a standalone or when boostered with subunit Baculovirus bivalent inactivated ND+H5 resulted in 90 and 100% protection, respectively, without significant difference in the quantity and duration of viral shedding between both groups against HPAI-H5N1 clade 2.3.4.4.b experimental challenge in broilers. Full article

Optimizing harvest time and oil production requires accurate olive fruit quality characterization. Traditional chemical methods are costly and tedious, leading to poor monitoring resolution and reliance on subjective visual assessments. While spectroscopy offers a non-destructive alternative, standard equipment remains complex and prohibitively expensive for smallholder farmers. To address this, we propose a methodology using a custom-made, low-cost multispectral device. Built upon the AS7265x board, the system acquires 18 spectral bands in the visible and near-infrared range (410–940 nm). We used these spectral data to feed artificial neural network (ANN) models for estimating the quality of intact olives. During a two-season field experiment, we monitored ripening to acquire spectral signatures and ground-truth values for oil content per fresh weight (OCFW), oil content per dry matter (OCDM), moisture (M), and titratable acidity (TA). External validation showed high accuracy for OCFW (R²p = 0.86), OCDM (R²p = 0.86), and M (R²p = 0.89), proving the system’s reliability. However, TA estimation showed lower performance (R²p = 0.21), indicating limited spectral correlation. These findings pave the way for affordable, real-time smart farming tools for olive quality monitoring. Full article

Background/Objective: Caffeine has demonstrated ergogenic effects across various doses (2–9 mg·kg⁻¹). However, aerobic responses to caffeine vary substantially, with time-trial performance ranging from ~–3% to +16%. Given that higher doses may increase adverse effects without clear additional benefits, this review examined the effects of low (≤3 mg·kg⁻¹), moderate (4–6 mg·kg⁻¹), and high (>6 mg·kg⁻¹) caffeine doses on time-trial performance. Methods: A systematic review and meta-analysis of randomized, placebo-controlled trials was conducted using PubMed, Embase, and Virtual Health Library databases. Eligible studies included healthy adults (18–59 years) acutely ingesting oral anhydrous caffeine before aerobic time-trial tests, with performance outcomes measured exclusively as time-to-completion variables. Data were pooled using standardized mean differences (SMDs) and 95% confidence intervals under random-effects models, and risk of bias was assessed using the Cochrane Risk of Bias tool. Results: Forty-eight studies (689 participants) met the inclusion criteria. Both low and moderate caffeine doses significantly reduced time-trial completion time relative to placebo. Low doses produced a standardized mean difference of −0.27 (95% CI: −0.44 to −0.11; p = 0.001), whereas moderate doses resulted in an SMD of −0.52 (95% CI: −0.77 to −0.28; p < 0.0001). No studies evaluating high caffeine doses (>6 mg·kg⁻¹) and reporting time-to-completion outcomes met the inclusion criteria. Subgroup analyses demonstrated similar ergogenic effects in both trained and highly trained individuals consuming moderate caffeine doses. Conclusions: This is the first meta-analysis specifically focused on aerobic time-trial performance to suggest that pre-exercise ingestion of low caffeine doses (1.3–3 mg·kg⁻¹) may enhance endurance performance by reducing time-trial completion time. Notably, the use of moderate caffeine doses (4–6 mg·kg⁻¹) appears to produce a more consistent ergogenic effect. Full article

This review examines the emerging role of machine learning (ML) in pharmaceutical chemistry, with emphasis on molecular design, synthetic feasibility, and structure–property–performance (SPP) relationships. By enabling pre-synthesis prediction of physicochemical properties, reaction pathways, and pharmaceutical performance, ML can reduce empirical trial-and-error experimentation and support more efficient exploration of chemical space. A structured narrative review design with PRISMA-aligned systematic search elements was used to evaluate 101 studies, enabling transparent literature identification, eligibility screening, and thematic synthesis across heterogeneous ML applications in pharmaceutical chemistry. This review examines structure–property relationships (SPRs) and property–performance relationships (PPRs), with emphasis on key pharmaceutical endpoints such as solubility, permeability, stability, dissolution, and bioavailability. An integrated SPP framework is proposed to connect molecular structure, intermediate properties, and final performance outcomes while incorporating retrosynthetic analysis and experimental feedback and closed-loop optimization. Recent frontier developments are also discussed, including molecular foundation models, multimodal language–graph models, diffusion-based molecular generation, E(3)-equivariant models, and MolMIM-like latent-space optimization. This review also covers co-folding and joint ligand–protein modeling, Boltz-2-like affinity prediction, AlphaFold 3-related biomolecular interaction modeling, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction. Key limitations include dataset leakage, benchmark inconsistency, assay variability, conformational and protonation-state effects, reproducibility challenges, regulatory constraints, and the gap between computational prediction and prospective experimental validation. Future progress is expected to depend on hybrid physics–ML models, uncertainty-aware prospective validation, autonomous experimentation, explainable artificial intelligence, and sustainability-aware molecular design. Overall, ML is evolving from a predictive tool into a chemically informed decision-support framework for rational, synthesis-aware, and experimentally validated pharmaceutical development. Full article

The Gebel Shalman-Wadi Biarn (GSh-WB) area in Egypt’s South Eastern Desert hosts NYF-type rare-metal pegmatites with significant U, Th, Nb-Ta, and REEs mineralization. This study integrates field observations, petrography, mineralogy, whole-rock geochemistry, and gamma-ray spectrometry to characterize these pegmatites and evaluate their economic potential. The pegmatites occur as veins, dykes, and zoned pockets hosted entirely within syenogranites. Petrography, pegmatites, and syenogranites are primarily composed of K-feldspar, albite, and quartz with trace amounts of biotite and muscovite. The environmental scanning electron microscope (ESEM) revealed the presence of the following minerals: autunite, kasolite, thorite, monazite-(Ce), parisite, xenotime-(Y), ferrocolumbite, hydroxyplumbobrtafite, aeschynite-(Y), and zircon, which are the major U-Th, Nb-Ta, and REE-bearing minerals. Additionally, gold, cassiterite, wolframite, pyrrhotite, chalcopyrite, and brass alloy were identified as sources of precious and base metals. Both groups’ chondrite-normalized REE patterns, which display slightly elevated LREE patterns and negative Eu anomalies, point to fractional crystallization involving plagioclase fractionation. Consequently, pegmatite and syenogranites are believed to have mostly formed from the partial melting of a reconstituted juvenile crust and its weathered sediments associated with Neoproterozoic magmatism. The marginally positive Ce anomaly in the (GSh-WB) pegmatites (1.02–0.98) may be associated with monazite crystallization resulting from enhanced fractionation. The Th and U levels range from 101 to 28.6 ppm and from 51 to 5.8 ppm, respectively. The magnitude of the tetrad effect in the rare earth elements of the analyzed rocks exceeds one (T1 = 1.12–1.02, T3 = 0.92–1.08, and T1,3 = 1.01–1.05), suggesting an M-type tetrad effect. The presence of this tetrad effect is indicative of granite that has been significantly altered by hydrothermal processes and is extensively fractionated. Chondrite-normalized REE patterns of the pegmatites (average ΣREE = 439 ppm) and their host syenogranites (average ΣREE = 192 ppm) show similar trends characterized by enrichment of light rare earth elements (LREEs) relative to heavy rare earth elements (HREEs) and pronounced negative Eu anomalies (Eu/Eu* = 0.09–0.22). These features, together with negative Sr and Ba anomalies, likely reflect extensive fractional crystallization of feldspars and feature anorogenic rocks. Spectrometric analysis reveals eU values of 2.0–288 ppm and eTh values of 7.0–455 ppm in pegmatite samples, with eU/eTh ratios (0.49–0.39) exceeding the typical continental crust value of 0.25, indicating uranium enrichment. Both magmatic and hydrothermal processes contributed to the observed radioactivity. The spatial distribution of uranium shows lithological and structural controls. The GSh-WB pegmatites represent a potential target for uranium exploration. Full article