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Conversion of microglia to a branching state is considered a potential strategy to ameliorate neuroinflammation. Inhibition of histone deacetylases (HDACs) may convert microglia to a branching state and thus prevent neuroinflammation. Drugs that inhibit HDACs could be used to alleviate neuroinflammation. Here, we hypothesize that 4-phenylbutyric acid (4-PBA), an HDAC inhibitor, could shift microglia to an anti-inflammatory phenotype by promoting microglial process elongation. As expected, our results showed that 4-PBA induced reversible elongation of branching processes in primary cultured mouse microglia and in microglia in the prefrontal cortex of mice. Pretreatment with 4-PBA also prevented lipopolysaccharide (LPS)-induced shortening of branching processes in microglia under both in vitro and ex vivo conditions, LPS-induced pro-inflammatory responses in cultured microglia and prefrontal cortex, and LPS-induced sickness behavior in mice. Short-term incubation with 4-PBA led to a significant increase in phosphorylation levels of protein kinase B (Akt) in cultured microglia. 4-PBA did not induce microglial process elongation in vitro or ex vivo when cultured microglia or mice were treated with the Akt signaling inhibitor LY294002, suggesting that the pro-elongation effect of 4-PBA on microglial processes require activation of Akt signaling. Moreover, 4-PBA did not prevent LPS-induced inflammatory responses in cultured microglia and prefrontal cortex or LPS-induced sickness behaviors when cultured microglia or mice were treated with LY294002. Altogether, these results indicate that 4-PBA induces microglial process elongation in an Akt-dependent manner, which may underlie the anti-neuroinflammatory properties of 4-PBA.

Seven new saponins (1-7) isolated from Stenocereus eruca (Cactaceae) and four new saponins (8-11) isolated from Polaskia chichipe (Cactaceae)　are described. Their structures were elucidated using high-resolution mass spectrometry and nuclear magnetic resonance analysis including ¹H and ¹³C NMR, DEPT, HMQC, HMBC, H2BC, DQF-COSY, HSQC-TOCSY, phase sensitive TOCSY, 1D-TOCSY, phase sensitive NOESY, and ROESY experiments. One saponin required J-resolved spectroscopy experiments due to its complex ¹H NMR spectrum. The inhibitory activity of Aβ aggregation, and protective effects on SH-SY5Y neuroblastoma cells against Aβ toxicity, were evaluated. Only 7 showed weak inhibitory activity of Aβ aggregation at 100 µM compared to the control group. No compounds showed obvious protective effects, but 8 possessed a very weak protective effect on SH-SY5Y cells. The acetylation of the C-16, C-22, and C-30 hydroxyl groups could be important for inhibitory activity of Aβ aggregation and protective effects on SH-SY5Y cells against Aβ toxicity.

Ethylenediaminetetraacetic acid (EDTA), extensively used across multiple industries, has long been discussed for its potential to enhance heavy metal mobility in aquatic systems, with studies yielding contradictory results. This study examines the remobilization of particle-bound lead from suspended particulate matter (SPM) in the Innerste River (Lower Saxony, Germany), which is affected by historical mining and known for substantial Pb contamination. Using real river water containing its native SPM to preserve the chemical matrix of the system, we assessed Pb partitioning between total and dissolved phases to evaluate EDTA's remobilization potential. Baseline dissolved lead concentrations reached up to 1.8 µg L^-1 (median 0.69 µg L^-1). Across all batch experiments, a measurable increase in the dissolved Pb fraction occurred only at EDTA concentrations far exceeding those measured in the river (0.68-3.8 µg L^-1). Bayesian concentration-response modelling yielded no-effect concentrations (NEC) between 210 and 530 µg L^-1. Complementary speciation modelling showed that shifts in Pb speciation occur only at EDTA concentrations near the experimentally derived NEC values. These findings show that current EDTA concentrations in the Innerste are unlikely to remobilize Pb from SPM. The study also provides a statistically supported NEC estimate based on batch experiments using unaltered river water containing its naturally present SPM. To our knowledge, this is the first application of Bayesian NEC modelling to EDTA-induced Pb remobilization.

Glioblastoma (GB) is the most aggressive and lethal primary brain tumor, characterized by high proliferative, migratory, and invasive capacities, as well as marked resistance to apoptosis. Despite standard therapy with temozolomide (TMZ), prognosis remains poor, underscoring the need for novel therapeutic strategies. In this study, we investigated the antitumor potential of centratherin, a sesquiterpene lactone, in established GB cell lines and patient-derived GB cells (GBM02, GBM95). Centratherin significantly reduced cell viability in a dose-dependent manner, with IC50 values varying across GB cells, while exhibiting no cytotoxicity to healthy human astrocytes. Functional assays revealed that centratherin impairs cell proliferation, migration, and invasion, and alters cytoskeletal architecture, as evidenced by morphological changes, reduced actin and tubulin organization. Additionally, centratherin induced double-strand DNA breaks, increased γH2AX levels, and triggered cell death predominantly via necrosis, as demonstrated by LIVE/DEAD staining, Annexin V/PI flow cytometry, and ultrastructural analysis. Notably, this cytotoxic effect did not involve necroptosis, as RIP1 expression and Nec-1 sensitivity were unchanged. Furthermore, centratherin failed to sensitize GB cells to TMZ, suggesting distinct mechanisms of action, in spite of its remarked effect on inducing cell death in GB cancer stem-like cells. Overall, our findings highlight centratherin as a promising selective cytotoxic agent against GB, capable of inducing cell death and disrupting key malignant phenotypes, which may be advantageous for GB treatment.

The genetic basis of agronomic traits is critical for enhancing yield, quality, and disease resistance in tomato. In this study, genome-wide association study (GWAS) was performed on a diverse panel of 72 tomato accessions to identify genomic regions linked to 18 agronomic, processing, and disease resistance traits. Phenotypic data were collected over two growing seasons, and genotyping was conducted using genotyping-by-sequencing (GBS) on the Illumina platform. A total of 78,828 high-quality single nucleotide polymorphisms (SNPs) were identified, primarily located in intergenic (54.66%), upstream (15.46%), downstream (14.35%), intronic (10.73%), and exonic (2.90%) regions. After stringent filtering, 7751 SNPs were retained for GWAS, leading to the identification of 47 significant quantitative trait loci (QTLs) associated with 13 traits. Fruit length exhibited the highest number of QTLs (23), while chromosomes 1 and 4 contained the most QTLs (9 each). Several candidate genes were identified for key traits, including F-box protein CPR1-like and transcription factor bHLH162-like for fruit weight, F-box protein At5g49610 for fruit length, transcription factor TGA9 for fruit diameter, F-box protein CPR1-like and Beta-D-xylosidase 2 for fruit yield, Cinnamoyl-CoA reductase-like SNL6 and UDP-glucosyltransferase, as well as stress-induced protein KIN2-like and serine/threonine-protein kinase BLUS1 for ToLCV resistance. Population structure and phylogenetic analyses indicated variation among ancestral populations (K = 3). These findings provide valuable genomic resources and identify candidate genes for key traits, supporting genomics-driven breeding in tomato.

Alzheimer's disease (AD), a major neurodegenerative disorder, lacks effective early diagnostic and therapeutic strategies. This study aimed to investigate the diagnostic utility of Long non-coding RNAs HLA Complex Group 18 ( HCG18) in AD and elucidate its molecular mechanisms in neuronal injury. Eighty-three AD patients and 83 healthy controls (HC) were enrolled. Serum samples were analyzed for HCG18 expression using qRT-PCR and cerebrospinal fluid (CSF) samples were analyzed for AD biomarkers by ELISA. Diagnostic performance was assessed using ROC analysis. Aβ1-42-treated HT22 cells (Immortalized murine hippocampal neuronal-like cell line) were employed to model neuronal injury, with HCG18 knockdown and miR-425-3p inhibition experiments conducted to validate functional interactions. HT22 cell apoptosis, oxidative stress markers (SOD, GSH-Px, MDA, ROS), and HCG18/miR-425-3p interactions were evaluated through flow cytometry, biochemical assays, and dual-luciferase reporter systems. Serum HCG18 levels were significantly elevated in AD patients compared to HC (P < 0.001), exhibiting strong diagnostic accuracy (AUC = 0.889). HCG18 expression correlated negatively with CSF Aβ1-42 (r=-0.709) and MMSE scores (r=-0.657), but positively with t-tau (r = 0.591) and p-tau181 (r = 0.582). In Aβ1-42-treated HT22 cells, HCG18 knockdown reduced apoptosis, suppressed ROS, and normalized oxidative stress markers. Mechanistically, HCG18 directly bound to and acted as a molecular sponge for miR-425-3p, sequestering its function; the downregulation of miR-425-3p mediated by a synthetic inhibitor reversed the protective effects of HCG18 silencing. HCG18 serves as a potential non-invasive biomarker for AD, exacerbating neuronal injury via sponging miR-425-3p to disrupt redox balance. Targeting the HCG18/miR-425-3p axis may offer new therapeutic strategies for AD.

As a core metric for climate policy, the scientific estimation of carbon social costs is crucial for formulating mitigation strategies. However, traditional integrated assessment models predominantly focus on the global aggregate, failing to adequately account for regional heterogeneity, sectoral characteristics, and strategic interactions between regions. They also lack systematic integration of ESG principles. To address this, this paper examines regional and sectoral carbon social costs driven by ESG development. Through cooperative and non-cooperative games, we improve the integrated economic-environmental-climate development model, take the eight economic regions in China as an example, get the carbon social cost of each economic region and typical important industries, and obtain the key parameters and the evolution law of carbon social cost. The model categorizes the carbon emissions after the implementation of emission reduction policies under the ESG perspective into direct and indirect emissions. It studies the economic impacts of the two types of emissions before and after the implementation of emission reduction policies, and conducts research on the top four typical important industries (industry, construction, transportation, and power) that rank among the top four global CO₂ emitters, to obtain the analytical solution of the social cost of carbon in the region and the typical important industries. In addition, this paper numerically simulates the social cost of carbon for the four industries under the baseline scenario, cooperative game scenario, non-cooperative game scenario, and temperature limitation scenario. The study shows that the social cost of carbon in the northern, southern and eastern coastal economic regions is higher than that in other economic regions, the social cost of carbon in the industrial and electric power industries in each economic region is higher than that in the building and transportation industries, and the more stringent the temperature limit is, the higher the social cost of carbon is in the economic regions.

Objective: This study aims to examine the relation between daily maximum exposure to Particulate Matter (PM_2.5), high wind speed, and minimum visibility, and COVID-19 cases in El Paso County, Texas, a dust-prone region. A time-series analysis using a generalized linear model with a Poisson model was employed to analyze relative risks of COVID-19 cases in El Paso (March 2020 to November 2021). A total of 156,299 cases were diagnosed during the study period. A 10 μg/m³ increase in PM_2.5 levels was linked with higher risk ratio (RR) of COVID-19 (Lag Days 1 to 3) [lag1: RR = 1.004; 95% CI: (1.003-1.005), lag2: RR = 1.006; 95% CI: (1.005-1.007), & lag 3: RR = 1.004; 95% CI: (1.003-1.005)], followed by a decrease in cases. Similarly, a 4.47 m/s rise in maximum wind speed was associated with an elevated RR of cases on Lag Day 4 [lag4: RR = 1.009; 95% CI: (1.003-1.014)], after which numbers begin to drop. Finally, a 4.83 km decrease in minimum daily visibility was correlated with an increased RR of cases on Lag Days 1 and 2 [lag1: RR = 1.031; 95% CI: (1.023-1.039), & lag2: RR = 1.018; 95% CI: (1.011-1.024)], with a decrease on Lag days 3, 4 and 5 and resurgence on Lag days 6 and 7 [lag6: RR = 1.028; 95% CI: (1.021-1.036), & lag7: RR = 1.046; 95% CI: (1.038-1.055)]. PM_2.5, wind speed, and visibility influencing COVID-19 cases in El Paso highlight the need for evidence-based interventions, including information, education, and communication programs, early-warning systems, cross-border air-quality management, real-time monitoring, and stricter emission controls.