Search Results (3,148)

Understanding the reproductive ecology of birds and the factors influencing nest predation is essential for developing scientifically sound and effective bird conservation strategies. Certain pheasant species sensitive to environmental changes are vulnerable to threats and face survival pressures such as habitat destruction and human activities. However, research related to their reproductive ecology is lacking. Here for the first time we reported information on breeding biology of the Chinese francolin (Francolinus pintadeanus). This study was conducted during the breeding seasons of the Chinese francolin in 2021, 2023, 2024, and 2025, combining traditional survey and infrared camera technology to monitor its reproductive ecology and nest predators in the Datian and Bangxi Reserves and to identify its potential predators through artificial nest experiments. All nests were open-ground nests located at the roots of dwarf shrubs and grasses. Our findings revealed that the breeding season of the Chinese francolin was mainly in March–September, peaking in May; its clutch size was 4.09 ± 1.27 (N = 22), reproductive success was 27.27%, and 16 nests were failed; and all failed nests were predated, with abandoned nests accounting for 93.75% of the failed nests. In artificial nest experiments, the predation rates of Datian Reserve and Bangxi Reserve were 70.91% (N = 55) and 60.00% (N = 30), respectively, with no significant difference in predation rates between the fully covered and exposed groups (Datian: χ² = 0.258, p = 0.612; Bangxi: p = 0.710). Natural nest monitoring and artificial nest experiments on the Chinese francolin identified snakes and the small Indian civet (Viverricula indica) as the main predators in Datian Reserve, as well as the greater coucal (Centropus sinensis) and wild boar (Sus scrofa) as potential predators. In contrast, the main predators in Bangxi Reserve were snakes and rodents. These findings indicate differences in nest predator taxa between the two reserves. We recommend prioritizing the restoration of dwarf scrub vegetation and optimizing the habitat management strategy in these reserves to better protect the breeding habitats of pheasants while promoting long-term stability and continuation of their populations. Full article

Urban carbon reduction is instrumental in enabling cities to realize their developmental sustainability objectives. However, regional disparities in economic development pose significant challenges to low-carbon transitions. This study utilizes panel data from 282 cities in China spanning 2006–2021, considering the energy saving and emission reduction (ESER) fiscal policy as an external shock. Using a multi-period difference-in-differences approach, we assess how ESER impacts urban carbon emissions. Our findings indicate that ESER significantly reduces municipal carbon emissions by an average of 23.3% compared to non-pilot cities. Mechanism analyses suggest that this effect operates through reduced energy consumption, improved industrial structure, and enhanced green innovation. ESER’s impact exhibits heterogeneity across cities with different levels of economic development, population size, innovation capacity, and industrial composition. Moreover, we find evidence of spatial spillover effects, as ESER benefits extend to neighboring regions. These results confirm the effectiveness of ESER in promoting low-carbon development and offer practical implications for enhancing environmental governance through green fiscal instruments. Full article

Background/Objectives: Spasticity is a common and disabling sequela of stroke that limits voluntary movement and functional recovery. Vibration therapy (VT) has been proposed as a non-invasive neuromodulatory intervention, but the existing studies report inconsistent outcomes due to methodological heterogeneity. This study aimed to evaluate the overall effectiveness of VT in reducing post-stroke spasticity and to identify optimal stimulation parameters via meta-analytic and meta-regression approaches. Methods: A systematic review and meta-analysis were conducted following the PRISMA 2020 guidelines. Standardized effect sizes (Hedges’ g) were calculated based on the within-group pre–post changes and compared across the groups. Meta-regression and subgroup analyses explored seven potential moderators, including the vibration frequency, amplitude, and time since stroke onset. Results: Thirteen randomized controlled trials (RCTs) involving whole-body or focal vibration interventions in stroke populations were included. Vibration therapy significantly reduced spasticity, yielding a moderate overall effect size (Hedges’ g = −0.50; 95% CI: −0.65 to −0.34; p < 0.001). The greatest treatment effects were observed when VT was applied during the late subacute to early chronic phase (6–12 months post-stroke), with low-frequency (<20 Hz) and low-amplitude (≤0.5 mm) stimulation. The frequency, amplitude, and stroke onset emerged as significant moderators (p < 0.05). Conclusions: Vibration therapy is an effective and clinically meaningful intervention for post-stroke spasticity, particularly when delivered with low-intensity parameters during the optimal recovery window. These findings support the development of individualized VT protocols and provide evidence to guide future rehabilitation strategies. Full article

The southern region of Kazakhstan represents the northernmost boundary of the natural habitat of five wild almond species, among which Amygdalus communis L. is of particular interest due to a range of favorable traits for use in breeding programs and cultivation in the region. The current distribution range of common almond growth was clarified using GPS to determine precise coordinates, and a schematic map was developed. Monitoring revealed a significant reduction in population size. In the surveyed areas, 54 trees were selected and described. Seed material was collected from 34 genotypes and characterized according to a descriptor. Genotypes A3, A8, and A15 were identified as having favorable trait combinations. To restore populations and preserve the gene pool of Amygdalus communis L., a method of clonal micropropagation was employed. The composition of the nutrient medium was optimized for establishment, multiplication, and rhizogenesis. It was determined that Murashige and Skoog (MS) medium without phytohormones is effective for in vitro establishment (70% regeneration rate). For multiplication, MS medium with 0.5 mg/L BAP (6-benzylaminopurine) was used (with a multiplication rate of 3.5 per explant). For rhizogenesis, MS medium with 0.5 mg/L BAP, 0.02 mg/L gibberellic acid (GA), and 0.1 mg/L IBA (indole-3-butyric acid) was used. A total of 340 clonal Amygdalus communis L. plants with closed root systems were grown for field collection. The research results can be applied for the restoration, propagation, and conservation of populations both in vitro and in situ, as well as for the inclusion of selected high-performing genotypes in breeding programs. Full article

We report the RAD@home citizen science discovery of two rare spiral-host radio galaxies (NGC 3898 and WISEA J221656.57-132042434.1 or RAD-“Thumbs up” galaxy), both exhibiting asymmetric radio lobes extending over 30 to 220 kiloparsec scales. We present a multi-wavelength image analysis of these two sources using radio, optical, and ultraviolet data. Both host galaxies are young, star-forming systems with asymmetric or distorted stellar disks. These disks show similarities to those in galaxies undergoing ram pressure stripping, and the radio morphologies resemble those of asymmetric or bent FR-II and wide-angle-tailed radio galaxies. We suggest that non-uniform gas density in the environment surrounding the ram pressure-stripped disks may contribute to the observed asymmetry in the size, shape, and brightness of bipolar radio lobes. Such environmental effects, when properly accounted for, could help explain many of the non-standard radio morphologies observed in Seyfert galaxies and in recently identified populations of galaxies with galaxy-scale radio jets, which are now being revealed through deep and sensitive radio surveys with uGMRT, MeerKAT, LOFAR, and, in the future, SKAO. These findings also underscore the potential of citizen science to complement professional research and data-driven approaches involving machine learning and artificial intelligence in the analysis of complex radio sources. Full article

Although genomic selection can accelerate livestock breeding, its application in many countries is hindered due to the limited size of reference populations. To address this issue, researchers have explored methods of combining multiple breeds to create reference populations, aiming to enhance the accuracy of genomic prediction. The main objective of this study was to evaluate the impact of the construction of mixed reference populations at different genetic distance levels on the accuracy of multi-breed genome prediction in multi-breed beef cattle populations using three evaluation methods: GBLUP, ssGBLUP, and wGBLUP. In order to study the effect of genetic correlation on multiple populations and to resolve the optimal mixing ratio, we considered six scenarios, including (1) population A as the main body, where the nearest 10% of individuals in populations B and C were added; (2) population A was the main body, where the 15% of individuals with the closest genetic distance in groups B and C were added; and (3) population A as the main body, where the 20% of individuals in populations B and C with the closest genetic distance were added. Our results suggest that the wGBLUP model can be enhanced when the mixing ratio is 15%, and the wGBLUP model shows higher accuracy in predicting populations with different LD decay patterns. Among them, whether combined with PopB or PopC, the wGBLUP model shows better prediction ability than the GBLUP and ssGBLUP models. However, when the mixing ratio is 10% or 20%, the accuracy of the three models is less than 15%, and the wGBLUP and ssGBLUP models show high and stable accuracy. Our results highlight the importance of considering the proportion of mixing between different populations when using genetic assessment models to predict accuracy, especially for endemic beef cattle breeds with different genetic structures and LD patterns and limited resources. However, this study also has some limitations. First, the determination of the optimal mixing ratio still needs further exploration, especially for populations with different genetic structures and LD patterns. Second, future studies can introduce more advanced models to further improve prediction accuracy. Full article

Writing is essential across disciplines, yet undergraduate programs must balance writing instruction with discipline-specific content. To support writing development, we piloted an embedded writing tutor (WT) in two core public health courses serving primarily first-generation, low-income students of color. In this model, a tutor familiar with course content is integrated into the classroom to supplement traditional writing center support. Our aims were to examine (1) students’ perceptions of the WT compared to the university’s writing center, (2) the WT’s experiences and effective tutoring strategies, and (3) the instructor’s perspective on implementing the program. Using qualitative methods, the WT recorded field observations, the instructor compared course progression to prior semesters without embedded support, and students completed end-of-semester evaluations. Thematic analysis indicated that students valued the tutor’s accessibility, patience, and direct feedback, though perceived usefulness varied by course, likely due to differences in assignment structure. Challenges included role confusion and inconsistent feedback. Suggested improvements included requiring draft submissions, clarifying the tutor’s role, and aligning tutor and instructor feedback. Quantitative ratings of satisfaction were higher for the WT than for the writing center. Although the sample size was moderate (N = 79), these findings suggest embedded tutoring is a promising, equity-focused strategy for discipline-specific writing instruction. In the context of budget constraints in higher education, exploring alternative tutoring and pedagogical support models remains essential, particularly for underserved populations. Full article

Parkinson’s disease (PD) is a common neurodegenerative disorder caused by progressive loss of dopaminergic neurons in the substantia nigra and the presence of Lewy bodies. While PD is most recognized by its motor symptoms (resting tremor, rigidity, bradykinesia, and postural instability), cognitive decline (CD) may become apparent as PD progresses, leading to Parkinson’s disease dementia (PDD). Type 2 diabetes mellitus (T2DM) and insulin resistance (IR) are risk factors for dementia, especially Alzheimer’s disease; however, their influence on dementia in PD is underexplored. Therefore, we sought to determine the effect of T2DM and IR on dementia in PD. A systematic search of articles from 2005 to March 2025 was undertaken using Embase, PubMed, Scopus, Web of Science, and citation searching. Case–control, cross-sectional, longitudinal, and non-human population studies assessing cognitive outcomes in individuals with PD, with and without T2DM and IR, were included (PROSPERO registration number CRD420251013367). In total, 27 studies met the inclusion criteria, with clinical sample sizes ranging from 23 to 544,162 participants. Among the 23 clinical studies, 15 identified T2DM as a contributor to cognitive decline (CD) in PD, and 4 specifically examined insulin resistance (IR). Elevated HbA1c was consistently associated with poorer cognitive performance and increased risk of Parkinson’s disease dementia (PDD); HbA1c ≥ 7% independently predicted cognitive impairment (OR = 4.25, 95% CI: 1.59–11.34). Vascular and inflammatory markers, including elevated LDL-C, fibrinogen, and hs-CRP, further exacerbated CD. MoCA and MMSE scores were the most common cognitive measures, consistently showing worse outcomes in PD patients with T2DM. Preclinical studies supported these associations, showing that high-fat-diet-induced T2DM and IR aggravated dopaminergic neuronal loss by 38–45%, increased α-synuclein by 35%, and heightened microglial activation, providing mechanistic evidence for the observed clinical associations. This systematic review, the first to examine the impact of T2DM and IRs on the occurrence and advancement of CD in PD patients, demonstrates a possible association between the two. However, these results demonstrate the need for larger sample sizes and the inclusion of additional clinical variables, such as HbA1c levels and pharmacological interventions, providing further information about the link between metabolic dysfunction and CD in PD. To further strengthen this link, longitudinal studies with systematic follow-ups are essential to establish causal links and avoid misdiagnosis in clinical practice. Full article

The growing population and increasing concerns about food security and sustainability demand innovative solutions to minimize food waste and transform by-products into functional ingredients valuable to the food sector. Brewery by-products, including brewer’s spent grain (BSG) and brewer’s spent yeast (BSY), are underutilized resources despite their high protein contents and potential as sustainable food ingredients. This study aimed to transform BSG and BSY into protein hydrolysates (BSGH and BSYH, respectively) through enzymatic hydrolysis and thus add value to these brewery industry by-products to be used in the food industry. These protein hydrolysates were incorporated into non-alcoholic malt beverages at three different concentrations, and their effects on the physicochemical properties, including color, kinematic viscosity, turbidity, foaming capacity and foam stability, of the non-alcoholic malt beverages were evaluated. Both BSGH and BSYH exhibited higher water solubility (WS) and lower water binding capacity (WBC) values when compared to their native non-hydrolyzed forms, enhancing their suitability as ideal ingredients for protein supplementation of a wide range of food and beverage products. The production of peptides of varying sizes underscored the effectiveness of enzymatic hydrolysis which resulted in an increase in cysteine and methionine levels in BSYH but a decrease in BSGH. The addition of BSGH and BSYH increased the kinematic viscosity and turbidity but reduced the lightness values in color of the non-alcoholic malt beverages. When the properties of the protein hydrolysates were compared, BSYH was more effective than BSGH in forming foams and maintaining their stability for longer periods. These findings highlight the potential of brewery by-products, after enzymatic hydrolysis, as protein-rich ingredients that can support more sustainable food systems and contribute to the nutritional enhancement of various low-protein food and beverage products. Full article

Background/Objectives: Propofol and Thiopental are widely used anesthetic agents, yet their cumulative and high-dose effects on hepatic metabolism remain insufficiently characterized. This study aimed to evaluate the impact of supra-therapeutic concentrations of these agents on carnitine and amino acid metabolism in AML12 hepatocytes, with a focus on their toxicometabolic profiles. Methods: AML12 mouse hepatocytes were exposed to escalating concentrations (2.5–500 µg/mL) of Propofol and Thiopental to assess cytotoxicity. IC₅₀ values (~255 µg/mL for both) were determined, and two high-dose concentrations (100 µg/mL and 200 µg/mL) were selected for metabolic profiling. Cell viability was assessed via the MTT assay. Intracellular carnitine and amino acid levels were quantified using LC-MS/MS. Statistical analyses included one-way ANOVA with post hoc tests, unpaired t-tests, and effect size estimations (Cohen’s d). Results: Propofol significantly suppressed carnitine metabolism in a dose-dependent manner, with a 79% reduction in free carnitine (C0), indicative of impaired mitochondrial β-oxidation. Thiopental, however, preserved or partially restored several acylcarnitines, including C16:1. While both agents reduced intracellular amino acid levels, 200 µg/mL Thiopental partially restored key metabolites such as glutamine, alanine, and histidine. Propofol exhibited broader metabolic suppression. Effect size analysis further confirmed the stronger inhibitory impact of Propofol. Conclusion: Although the concentrations used exceed typical clinical plasma levels, they may reflect prolonged or high-dose exposure scenarios observed in ICU settings. The findings highlight distinct toxicometabolic signatures for each agent and underscore the utility of metabolite profiling in modeling anesthetic-induced hepatic stress and guiding anesthetic selection in vulnerable populations. Full article

Ovarian aging is characterized by a gradual decline in both reproductive and endocrine functions, ultimately culminating in the cessation of ovarian activity around the age of 50, when most women experience natural menopause. The decline begins early, as follicular attrition is initiated in utero and continues throughout childhood and reproductive life. Most follicles undergo atresia without progressing through substantial stages of growth. With increasing age, a pronounced reduction occurs in the population of resting follicles within the ovarian reserve, accompanied by a decline in the size of growing follicular cohorts. Around the age of 38, the rate of follicular depletion accelerates, sometimes resulting in diminished ovarian reserve (DOR). The subsequent menopausal transition involves complex, irregular hormonal dynamics, manifesting as increasingly erratic menstrual patterns, primarily driven by fluctuations in circulating estrogens and a rising incidence of anovulatory cycles. In parallel with the progressive depletion of the follicular pool, the serum concentrations of anti-Müllerian hormone (AMH) decline gradually, while reductions in inhibin B levels become more apparent during the late reproductive years. The concomitant decline in both inhibin B and estrogen levels leads to a compensatory rise in circulating follicle-stimulating hormone (FSH) concentrations. Together, these endocrine changes, alongside the eventual exhaustion of the follicular reserve, converge in the onset of menopause, which is defined by the absence of menstruation for twelve consecutive months. The mechanisms contributing to ovarian aging are complex and multifactorial, involving both the oocyte and the somatic cells within the follicular microenvironment. Oxidative stress is thought to play a central role in the age-related decline in oocyte quality, primarily through its harmful effects on mitochondrial DNA integrity and broader aspects of cellular function. Although granulosa cells appear to be relatively more resilient, they are not exempt from age-associated damage, which may impair their hormonal activity and, given their close functional relationship with the oocyte, negatively influence oocyte competence. In addition, histological changes in the ovarian stroma, such as fibrosis and heightened inflammatory responses, are believed to further contribute to the progressive deterioration of ovarian function. A deeper understanding of the biological processes driving ovarian aging has facilitated the development of experimental interventions aimed at extending ovarian functionality. Among these are the autologous transfer of mitochondria and stem cell-based therapies, including the use of exosome-producing cells. Additional approaches involve targeting longevity pathways, such as those modulated by caloric restriction, or employing pharmacological agents with geroprotective properties. While these strategies are supported by compelling experimental data, robust clinical evidence in humans remains limited. Full article

Objectives: Hepatocellular carcinoma (HCC) remains a major indication for liver transplantation (LT), but accurate pretransplant risk stratification is critical to improve long-term outcomes. Traditional morphometric criteria such as tumor size and number are limited in predicting recurrence and survival. The HALP (hemoglobin, albumin, lymphocyte, platelet), gamma-glutamyl transpeptidase to platelet ratio (GPR), and FIB-4 indices are emerging systemic inflammatory and nutritional biomarkers that may provide additional prognostic value in HCC patients undergoing LT. Materials and Methods: This retrospective, two-center cohort study included 200 patients who underwent LT for HCC between 2012 and 2023. Preoperative HALP, GPR, and FIB-4 scores were calculated, and their associations with overall survival (OS) and recurrence-free survival (RFS) were assessed using ROC analyses and Cox proportional hazard models. Cut-off values were determined for each biomarker, and survival outcomes were analyzed using Kaplan–Meier methods. Results: A low HALP score (≤0.39) was independently associated with reduced OS but not with RFS. Conversely, low GPR (≤0.45) and FIB-4 (≤3.1) values were significantly associated with both poor OS and higher recurrence risk. Tumor size, number of lesions, and microvascular invasion also independently predicted poor outcomes. Multivariate analysis confirmed HALP, GPR, and FIB-4 as significant preoperative predictors of prognosis in this population. Conclusions: HALP, GPR, and FIB-4 are readily available, cost-effective indices that provide significant prognostic information in HCC patients undergoing LT. Their integration with morphometric criteria may improve pretransplant risk stratification and support individualized clinical decision-making. Full article

Sustainability performance varies significantly across countries, yet global assessments overlook the underlying structural trends. This study bridges this gap using machine learning to uncover meaningful clustering in global sustainability outcomes based on the 2025 Sustainable Development Goals (SDG) Index. We applied K-Means clustering to group 166 countries into five standardized indicators: SDG score, spillover effects, regional score, population size, and recent progress. The five-cluster solution was confirmed by the Elbow and Silhouette procedures, with ANOVA and MANOVA tests subsequently indicating statistically significant cluster differences. For the validation and interpretation of the results, six supervised learning algorithms were employed. Random Forest, SVM, and ANN performed best in classification accuracy (97.7%) with perfect ROC-AUC scores (AUC = 1.0). Feature importance analysis showed that SDG and regional scores were most predictive of cluster membership, while population size was the least. This supervised–unsupervised hybrid approach offers a reproducible blueprint for cross-country benchmarking of sustainability. It also offers actionable insights for tailoring policy to groups of countries, whether high-income OECD nations, emerging markets, or resource-scarce countries. Our findings demonstrate that machine learning is a useful tool for revealing structural disparities in sustainability and informing cluster-specific policy interventions toward the 2030 Agenda. Full article

Whether there is a correlation between sunspots and an impact on insects has long been a subject of debate. As a worldwide pest, the cotton bollworm can feed on a variety of plants and cause great harm to agriculture. Clarifying the pattern of sunspots’ influence on it is of great significance for the integrated management of pests. Therefore, we analyzed the sunspot data from 1989 to 2018, as well as the cotton bollworm data from three counties: Maigaiti and Bachu in southern Xinjiang (with 29 and 25 years of data, respectively) and Shawan in northern Xinjiang (with 23 years of data), China. The population size of cotton bollworms increased with the rise in annual mean temperature (T_mean) in the three regions. The impacts of sunspots on annual T_mean in Maigaiti and Bachu were not significant, while in Shawan, there was a lagged effect. Sunspot activity was significantly negatively correlated with the number of moths in Maigaiti and Shawan, while the influence of sunspots on the Bachu population exhibited a certain degree of lag. The fluctuation cycles of moth numbers in these three regions were not consistent with those of sunspots. In Maigaiti and Shawan, the increase in annual, monthly, and daily sunspot numbers was negatively correlated with the rise in annual, monthly, and daily moths captured, respectively, while in Bachu, they were positively correlated. The cycle of sunspots was not synchronized with the cycles of annual T_mean in the three regions. When the number of sunspots exceeded 100, the relative catch (RC) of moths rose in Bachu, while the RC of moths decreased in Maigaiti and Shawan. The RC of moths did not at all increase as the number of sunspots rose. The abrupt changes in the annual T_mean and moth numbers both occurred later than the abrupt change in sunspots, indicating that the influence of sunspots on them had a certain degree of lag and was not synchronous. Full article

Background/Objectives: Individuals with posttraumatic stress disorder (PTSD) tend to show patterns of elevated cardiovascular disease (CVD) risk earlier in life than the general population. The need for effective interventions for CVD risk-reduction in PTSD is increasingly evident. In this paper we present preliminary results from a longitudinal study of a health behavior intervention, as an adjunct to standard trauma therapy in PTSD. The health behavior intervention addresses CVD-related heath behaviors (physical activity, nutrition, sleep, and stress) in a 12-week program delivered individually in 90-min sessions. Behavior change recommendations included: increased aerobic activity; establishing a balanced diet, enhancing consumption of fruits and vegetables and reducing sugars and fat/saturated fat; incorporating strategies to enhance sleep and lower PTSD-related disruptions (e.g., nightmares); and relaxation and cognitive coping skills to reduce general stress. Methods: Participants were randomized to the health behavior intervention plus standard trauma therapy experimental condition or a standard trauma therapy control group. Outcomes were measured at baseline and after the 12-week intervention phase. Sleep efficiency was measured from actigraphy watches. Physical activity was assessed by self-report and blood pressure was measured using an automated device. The preliminary outcomes are for 29 participants to date who have pre-post data. Results: Sleep efficiency was improved in the intervention group compared to controls (p < 0.05). The intervention group also evidenced significant pre-post increases in moderate physical activity compared to the control group (p < 0.05). Changes in vigorous physical activity did not reach statistical significance in this preliminary sample but the pattern of results are similar to those for moderate activity. Trends toward significance were also observed for pre-post changes in systolic (p = 0.06) and diastolic blood pressure (p = 0.07), with small reductions for the intervention group and increases for the control group. Conclusions: These findings provide preliminary information about the effectiveness of the health behavior intervention on multiple parameters for adults with PTSD. The findings suggest that focusing on health behavior change in multidisciplinary treatments for PTSD may enhance outcomes such as sleep and physical activity and potentially result in greater quality of life. However, the small preliminary sample size reported here should be considered when interpreting the outcomes. Further research may also determine how improvements in health parameters impact other indices of long-term cardiovascular health. Full article