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Foreign Direct Investment (FDI, hereafter) as a determinant of economic growth has received significant attention in both the theoretical and empirical research literature due to its numerous benefits. However, the FDI–growth relationship is rarely researched for the economy of Saudi Arabia. Amid this backdrop in the literature, this paper focuses on Saudi Arabia to provide fresh, comprehensive evidence about the FDI–growth relationship. Our analysis is based on time series data for the period 1975–2023, which were collected from credible global sources. For estimation, the study adopted ARDL modeling, which is suitable for time series data as it produces both long-run relationships and short-run dynamics simultaneously. Our results show that FDI inflows have a positive and statistically significant influence on economic growth in the long run. Similarly, in the long run, both human capital and trade openness have also improved the long-run growth of Saudi Arabia. Furthermore, a positive and statistically significant influence of natural resources on economic growth is observed in the long run. Moreover, the results show that total factor productivity and domestic investment have not had the desirable influences on economic growth. The short-run results show that the growth performance of Saudi Arabia could be explained by natural resources, domestic investment and human capital. The causality analysis also confirmed a one-way relationship running from FDI inflows towards economic growth. Our results have a significant policy implication for the policymakers of Saudi Arabia. Full article

Although estrogen has been identified to play crucial roles in the development of melasma, the exact mechanism of estrogen’s effect on pigmentation is incompletely elucidated. Recent studies have highlighted the pivotal role of immune cells in melasma. Interestingly, infiltrated macrophages are significantly enhanced in melasma lesions. Estrogen could facilitate M2 polarization. However, whether estrogen could stimulate melanogenesis via skewing M2 phenotype remains unknown. This study attempted to determine the significance and molecular mechanism of estrogen-induced M2 phenotype in melasma. We found that M2 infiltration was significantly increased in melasma lesions compared with perilesional skin. Arginase 1 was identified as the hub gene, and its expression was positively correlated with that of microphthalmia-associated transcription factor and tyrosinase-related protein 1 in melasma through transcriptome analysis. Moreover, β-estradiol (E2) was confirmed to promote M2 skewing while inhibiting M1 polarization via activating STAT6 signaling. Importantly, E2-induced M2 polarization robustly increased melanogenesis by increasing tyrosinase activity and expression of microphthalmia-associated transcription factor and tyrosinase in melanocytes, which were profoundly inhibited by VEGF knockdown or antagonism both in vitro and in ex vivo skin. Furthermore, VEGF was revealed to enhance melanogenesis through activating p38 MAPK and ERK1/2 signaling pathways in melanocytes. Additionally, dermal VEGF was significantly increased, and most of it colocalized with M2 macrophages in melasma lesions. Crucially, E2 administration potently reversed ovariectomy-decreased M2 skewing and subsequently promoted dermal VEGF expression and epidermal melanogenesis in the mouse tail skin, which were significantly suppressed by macrophage depletion. These findings suggest that estrogen may stimulate melanogenesis in melasma through increasing M2 skewing and VEGF expression and secretion in macrophages. Full article

Equine osteoarthritis (OA) is a major cause of lameness and economic loss in horses. While platelet-rich plasma (PRP) has clinical potential, the biological effects of fresh PRP (F-PRP) and freeze-dried PRP (FD-PRP) remain insufficiently defined. This pilot study compared 25% and 50% F-PRP and FD-PRP in an interleukin-1β-induced equine cartilage-synovium explant co-culture model. PRP treatments reduced inflammatory responses, with significant downregulation of COX-2 and PGE2 expression, and 25% F-PRP showed the most consistent inhibition of nitric oxide production. PRP also significantly reduced glycosaminoglycan release and altered matrix-related gene expression; however, FD-PRP significantly upregulated MMP13, indicating a potential pro-catabolic response. Untargeted LC/MS metabolomics showed that F-PRP and FD-PRP were associated with changes in glucose, purine, amino acid, lipid, and nucleotide metabolism. Growth factor analysis further showed lower PDGF and TGF-β1 concentrations in FD-PRP than in F-PRP. Overall, F-PRP showed more consistent anti-inflammatory and matrix-protective effects, whereas FD-PRP requires further optimization and safety validation before clinical application. Full article

Modern agriculture faces increasing pressure from rising food demand, resource degradation, and biotic stress factors, highlighting the need for sustainable, non-chemical technologies. Cold atmospheric plasma (CAP) has emerged as a promising non-chemical seed-priming technology with potential applications in sustainable agriculture. The present study investigated the effects of dielectric barrier discharge (DBD)-generated CAP on seed germination and early seedling development in two Solanum lycopersicum genotypes (a common variety and an IdB hybrid) under controlled laboratory conditions. Seeds were exposed to CAP for 1, 2, 3, or 4 min, while untreated seeds served as controls. Early plant performance was evaluated after 47 days by determining germination rate, fresh biomass, dry biomass, and mineral biomass (ash content). CAP exposure duration significantly affected all gravimetric parameters in both genotypes. Among the tested treatments, 1 min exposure consistently produced the highest fresh, dry, and mineral biomass values, whereas longer exposure times (3–4 min) generally reduced seedling growth, indicating the transition from beneficial physiological stimulation to stress-induced inhibition. Despite the more pronounced response observed in the IdB hybrid, the statistical analysis demonstrated that treatment duration, rather than genotype, was the principal factor influencing biomass accumulation. The present results indicate that short-duration CAP treatment represents an effective seed-priming strategy for improving early tomato seedling development. Full article

Nitrogen (N) plays an important role in the growth and development of potatoes, but overapplication of the nutrient compromises environmental systems’ sustainability and limits tuber productivity and quality. A two-season study was carried out in 2022 and 2023 at Ofcolaco in the Mopane District of South Africa to determine the influence of N and nano micronutrients on tuber bulking rate (TBR), crop growth rate (CGR), and stomatal activities. A Randomized Complete Block Design (RCBD) fitted into a split-split plot arrangement with four replications was employed with the hypothesis that N and nano micronutrients applications will not have an effect on growth, stomatal activity, and bulking rate of potato cultivars. The main-plot factor was N rates (0, 80, 160, and 240) kg Nha⁻¹; the sub-plot factor was nano-zinc (Zn) and copper (Cu) micronutrients, while cultivar, Mondial, and Valor were the sub-sub-plot factors. The application of N and nano Zn and Cu significantly influenced dry matter accumulation, TBR, CGR, and stomatal activities of both Mondial and Valor cultivars. From our study, the application of 160 kg Nha⁻¹ in conjunction with nano micronutrients resulted in an increase in dry matter in the two cultivars, in comparison with the application of 240 kg Nha⁻¹ without nano micronutrients. This observation was consistent in TBR and CGR in Mondial during the 2023 season. In 2022, the CGR under 160 kg Nha⁻¹, along with nano micronutrients in Valor, achieved 90% of the CGC of sole 240 kg Nha⁻¹. The physiological and plant growth parameters’ response to treatment in the two cultivars were generally optimized, when nano micronutrients were applied in conjunction with higher N rates of 160 and 240 kg Nha⁻¹. Significant principal component factors influencing variability in growth and physiological parameters varied between seasons. The findings generally demonstrated that 160 kg Nha⁻¹, in conjunction with micronutrients, has the potential to downsize N application in potato growth and development. Full article

Ratoon rice cultivation is a significant practice for enhancing land productivity and food security. Ratooning ability is a key determinant of ratoon season crop (RC) yield and is influenced by genetic, agronomic, and hormonal factors. This study aimed to evaluate the effects of foliar-applied ratooning enhancers, formulated with plant hormones and botanical extracts, on the growth and regeneration of a japonica–indica hybrid rice cultivar, ‘Qingxiangyou 19 Xiang’. Treatments included gibberellin (GA), low, medium, and high concentrations of brassinosteroid (BR), each with or without jasmine extract (JE), alongside proline and zinc chloride (ZnCl₂) as supporting components. These solutions were applied twice at 5 and 15 days after flowering (DAF) of the main crop (MC). The results showed that GA treatment increased plant height and panicle length but reduced MC tiller number. BR treatments did not affect plant height but significantly increased the 1000-grain weight. Crucially, while BR alone had no significant effect on ratooning ability, the BR-JE combined application, particularly at medium (MBR-JE) and high (HBR-JE) concentrations, significantly increased ratoon tiller number and enhanced ratooning ability. However, the HBR-JE combination increased grain chalkiness. In conclusion, the foliar application of BR combined with JE during the flowering stage effectively promotes ratooning ability without compromising MC yield, offering a promising agronomic strategy for sustainable ratoon rice production. Full article

Auxin response factors (ARFs) are a pivotal class of transcription factors that mediate auxin signaling, playing critical roles in plant growth, development, and stress adaptation. Watermelon (Citrullus lanatus) is an economically important cucurbit crop, yet a comprehensive analysis of its ARF gene family under abiotic stresses is limited. In this study, we conducted a genome-wide identification of the ARF gene family in watermelon. A total of 16 ClARF genes were identified and unevenly distributed across nine chromosomes. Phylogenetic analysis classified these ClARF proteins into four distinct classes (I–IV), a categorization supported by conserved motif composition and exon-intron structures. Cis-element analysis revealed that ClARF gene promoters are enriched with motifs related to hormone response, light signaling, and various stresses, suggesting their involvement in diverse regulatory pathways. Syntenic analysis indicated that segmental duplication events have contributed to the expansion and evolution of the ClARF family. Tissue-specific expression profiling showed varied expression patterns across roots, stems, leaves, tendrils, and flowers, implying functional diversification. Furthermore, real-time quantitative PCR (RT-qPCR) analysis revealed stress-specific expression patterns of ClARF genes. Notably, ClARF6 was consistently upregulated across all three treatments and showed the highest induction under drought (~7-fold) and cold (~11-fold), while ClARF13 was most strongly induced under salt stress at 48 h (~10-fold), and ClARF1 was consistently downregulated across all treatments. This study provides a stress-oriented expression profiling of the ARF gene family in watermelon, establishing a foundation for future functional studies and offering candidate genes for further functional characterization of abiotic-stress responses in watermelon and related cucurbit crops. Full article

The Misery Index (MI), also known as the Economic Discomfort Index, is a macroeconomic gauge originally proposed by Arthur M. Okun. It is defined as the unweighted sum of inflation and unemployment rates. This indicator attempts to synthesize the main factors generating economic malaise and collective discomfort, although it has been criticized for being an oversimplification of the economic problems faced by average citizens. Consequently, researchers have modified this index by incorporating variables associated with informality, interest rates, and economic growth, among others. Despite its simplicity, the MI has been utilized to describe the behavior of numerous social phenomena, such as suicide, the inclination to gamble, and tourism. However, the index has also been criticized for the inherent difficulty of associating its behavior with specific policy actions. This paper presents the main criticisms that this index has received, as well as its main applications and the various modifications it has undergone over time. Full article

Biomass allocation patterns affect plant functions across all levels, ranging from plant growth and reproduction to the quality and energy flow of entire communities. Revealing the biomass allocation and allometric growth relationships among the dominant plant formations in alpine peat swamp wetlands not only can help elucidate the life history strategies of swamp plants, but also plays a crucial role in understanding the uncertainty of plant carbon sinks in peat swamp wetlands. Based on community surveys, this study employed analysis of variance (ANOVA) and standardized major axis estimation (SMA) to analyze the species composition, biomass allocation of different organs, and allometric growth relationships of the dominant plant formation in the alpine peat swamp wetlands of the Yellow River on the Gannon Plateau, Gansu Province, China. The results showed the following: (1) Peat swamp plants can be classified into six formations dominated by Carex muliensis, Blysmus sinocompressus, Carex atrofusca, Kobresia tibetica, Kobresia kansuensis, and Carex kansuensis. Environmental filtering was identified as the primary factor influencing the distribution of formations in this region. (2) The biomass allocation ratios of the dominant plant formations were ordered as follows: root mass ratio > leaf mass ratio > stem mass ratio. There were also significant differences in the biomass allocation of roots, stems, and leaves among different plant formations. (3) Isometric growth was observed between the leaf and stem biomass of the dominant plant formations (p > 0.05), while allometric growth relationships existed between root/leaf biomass and root/stem biomass (p < 0.05), with the growth rate of root biomass (RB) being higher than that of leaf biomass (LB) and stem biomass (SB). The biomass allocation patterns and allometric growth relationships among the roots, stems, and leaves of the dominant plant formations in peat swamp wetlands reflect the environmental plasticity mechanism of functional plant traits in heterogeneous habitats. Moreover, combining optimal allocation theory and allometric growth theory can better explain the biomass variation and adaptation mechanisms of dominant plant formations in peat swamp wetlands, providing a theoretical basis for understanding the habitat adaptation patterns of plants in alpine peat swamp wetlands. Full article

Global warming is associated with an increased frequency and intensity of heat waves, which severely threaten crop production and sustainable agriculture. As sessile organisms, plants evolved complex heat stress memory mechanisms to cope with recurring heat waves. Heat shock transcription factors (HSFs) are at the core of plant heat stress responses and memory. They regulate basal thermotolerance, acquired thermotolerance, and the maintenance of acquired thermotolerance. These processes involve multiple mechanisms, including temperature perception, activation of heat shock protein expression, and integration of hormonal and epigenetic signals. Here, we review the pivotal role HSFs play in the formation of heat stress memory, their structural characteristics, functional differentiation, and signal perception and transcriptional regulatory mechanisms. We further discuss the functional conservation and the diversity of HSFs across multiple species—for instance, HSFA2 acts as a conserved regulator of heat stress memory in Arabidopsis, tomato, wheat, and barley—and outline future research directions, including the functional characterization of heat shock transcription factor (HSF) subfamilies, investigation of their roles under stress combination, and strategies to balance stress tolerance with growth and development. We hope that our review will provide a theoretical foundation for the genetic improvement of crop thermotolerance as well as contribute to efforts directed at ensuring food security in the face of climate change. Full article

This study investigates the relationship between economic growth, health expenditure, institutional quality, gross fixed capital formation, and foreign direct investment in EU countries outside the euro area over the period 2000–2024. The analysis is grounded in neoclassical and endogenous growth theory, with particular emphasis on the role of institutional quality as a conditioning factor in the growth process. Methodologically, this study employs an integrated empirical time-series framework focusing on selected health, institutional and investment-related determinants of growth, including linear and nonlinear unit root tests, structural break analysis, and an Autoregressive Distributed Lag/Error Correction Model (ARDL/ECM) approach to capture both long-run equilibrium relationships and short-run dynamics. ECM-based Granger causality tests are further applied to examine the direction of causal interactions. The results confirm the existence of a long-run cointegration relationship across all countries, although the magnitude and direction of the effects vary considerably. Gross fixed capital formation exerts a robust positive influence on economic growth, while foreign direct investment mainly affects growth in the short run and is highly sensitive to external shocks. Health expenditure contributes to growth through human capital formation, with predominantly lagged effects. Institutional quality is associated with growth dynamics, although the direction and strength of this relationship vary across countries and should be interpreted in light of feedback effects identified in the causality analysis. Overall, the findings highlight significant cross-country heterogeneity and underscore the importance of institutional quality in enhancing the effectiveness of investment and public spending for sustainable economic growth. Full article

Complex sex determination and a large genome hinder conventional spinach breeding. To address this challenge, a biotechnological approach could be used to establish a reliable protocol for somatic embryogenesis and apply genetic tools such as CRISPR. However, spinach is recalcitrant to somatic embryogenesis, with substantial inter- and intrapopulation variability in embryogenic capacity. In this study, we assessed the impact of environmental conditions during donor plant growth on the embryogenic capacity of the resulting seedlings. Seed populations, selected for differing embryogenic capacities, were sown in greenhouses at two distinct locations, and cross-pollination was only permitted between plants of the same origin. The resulting seeds were aseptically sown, and the embryogenic capacity of the seedlings’ root apices was determined. Root explants from seedlings originating from Ukraine and Poland showed low regenerative capacity regardless of cultivation locality, with a maximum of 22.71% regenerating explants and 1.3 somatic embryos per explant. Conversely, seedlings originating from Slovenia exhibited high regeneration potential, with significant differences between cultivation localities: 89.36% vs. 59.72% regenerating explants and 12.04 vs. 3.77 somatic embryos per explant. Therefore, the embryogenic capacity in spinach is strongly influenced by environmental conditions during donor plant growth and could be further increased by manipulating these factors. Full article

Rice cultivation is a major source of methane (CH₄) emission in the agricultural sector, with a significantly higher global warming potential than carbon dioxide. Accurate and scalable quantification of CH₄ from rice paddies is essential for carbon accounting. This study presents an automated framework for estimating rice CH₄ emissions from irrigated paddies in the central plain of Thailand, integrating multi-sensor Synthetic Aperture Radar (SAR) observations with the IPCC methodology. The framework combines Sentinel-1 C-band SAR time series for phenological detection, ALOS-2 PALSAR-2 L-band full-polarimetric SAR for water regime classification, and IPCC water-scaling factors corresponding to Continuous Flooding, Single Drainage, or Multiple Drainage regimes. Evaluated across five stratified holdout sets, the phenology detection algorithm achieved planting and harvesting date Mean Absolute Errors of 6.1 ± 1.4 and 8.3 ± 1.7 days, with a 97.0% ± 2.7% operational detection rate. Water regime classification employed rice growth stage-specific Support Vector Machine classifiers with Radial Basis Function kernels (SVM-RBF), achieving per-stage test Balanced Accuracy ranging from 0.59 to 0.89. End-to-end integration using a four-track counterfactual decomposition yielded a full-pipeline mean absolute error of 18.5 ± 4.5 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$ (21.4% of the mean ground-based CH₄ calculation) and a mean bias of 3.5 ± 5.8 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$. Water level classification was confirmed as the dominant algorithmic uncertainty source, while the IPCC Tier 1 emission factor structural range (−32% to +48% of the default) exceeded all algorithmic errors combined. The proposed framework provides a spatially explicit approach for integrating multi-frequency SAR data into IPCC-compliant methane estimation, supporting Monitoring, Reporting, and Verification applications. Full article

The Growth-Regulating Factor (GRF) family and their co-activators, GRF-Interacting Factors (GIFs), are key players in the trade-off between plant development and stress adaptation, functioning as canonical targets of the highly conserved miR396 family, which mediates responses to environmental stressors including high temperatures and water deficits. The “starlet” phenomenon in the allotetraploid Coffea arabica L. is a developmental disorder that results in malformed flowers, frequently associated with environmental stress and floral sterility. Since their underlying molecular mechanisms remain uncharacterized, we performed a genome-wide identification of the CaGRF and CaGIF families and quantified their transcriptional profiles in shoot apical meristems (SAMs) and across multiple stages of floral bud development. Our findings reveal significant differential expression of the GRF-GIF module between typical and starlet tissues throughout development, including the SAM. Intriguingly, these results do not correlate with the levels of a representative member of the miR396 family, indicating that the GRF-GIF expression shifts in starlet-flowers may be uncoupled from miR396 levels. This work provides the first molecular insights into the enigmatic starlet phenomenon in Coffea arabica L., addressing an understudied aspect of coffee reproductive development and its implications for the reproductive stability (and productivity) of this important tropical crop species. Full article

Sustainable agricultural development requires regional agricultural systems to balance output growth, resource efficiency, ecological protection, and long-term resilience. In mountainous and ecologically sensitive regions, identifying the development constraints and statistically derived marginal contribution thresholds of agriculture is essential for promoting green transformation and sustainable land use. Taking Yunnan Province, China, as a representative plateau mountainous agricultural region, this study uses provincial annual data from 1990 to 2023 to quantitatively identify the key drivers and threshold characteristics of agricultural development under multidimensional constraints. A multidimensional indicator system was constructed covering fiscal and investment support, agricultural production inputs, rural infrastructure, and labor and population conditions. Ridge regression was employed to address multicollinearity among explanatory variables, Bootstrap approximate inference was used to improve the robustness of coefficient estimation, and the SHAP interpretation framework was introduced to rank key driving factors and identify marginal contribution thresholds. By integrating ridge regression, Bootstrap approximate inference, SHAP-based contribution ranking, and threshold identification, the proposed framework advances prior agricultural sustainability studies by linking coefficient-based factor analysis with interpretable marginal contribution thresholds under conditions of high multicollinearity and multidimensional resource constraints. The results show that agricultural development in Yunnan is characterized by multidimensional resource and infrastructure constraints. Rural electricity consumption, total reservoir storage capacity, fixed asset investment in agriculture, forestry, animal husbandry and fisheries, local public fiscal budget expenditure, and agricultural population generally act as positive supporting factors. Rural electricity consumption is the most stable and core driver across the aggregate and three sectoral models. In contrast, pesticide and fertilizer inputs show significant negative associations in most models, suggesting that future agricultural development in Yunnan is unlikely to be sustainably supported by continued expansion of high-intensity chemical inputs. Sectoral heterogeneity is also evident: agriculture and animal husbandry are more dependent on energy, water resources, and mechanization, whereas forestry shows a more distinct operational structure. The SHAP dependence analysis identifies several statistically derived marginal contribution thresholds, including rural electricity consumption of approximately 6.055 billion kWh, total reservoir storage capacity of approximately 10.395 billion m³, total agricultural machinery power of approximately 19.8324 million kW, pesticide use of approximately 37,500 tons, and fertilizer application of approximately 1.5238 million tons. These values should be interpreted as empirical transition points in the modeled marginal contributions rather than definitive biophysical ecological limits. They indicate that the sustainability-related constraint structure of agricultural development in Yunnan is not a single output ceiling but a composite interval shaped by infrastructure support capacity, factor allocation conditions, and the declining marginal contribution of high-intensity chemical inputs. The findings provide directional quantitative evidence for sustainable agricultural governance, agricultural green transformation, and differentiated policy discussion in mountainous agricultural regions and offer reference implications for advancing SDG 2 and SDG 15 through the coordination of food-related production, resource use efficiency, and ecosystem conservation. The identified thresholds should be interpreted as model-derived marginal contribution transition points rather than operational policy cutoffs or directly enforceable ecological standards. Full article