Search Results (98)

A critical yet frequently overlooked factor is the tumor’s metabolic profile. Diabetes and chronic moderate hyperglycemia are known risk factors for triple-negative breast cancer (TNBC) that do not respond to hormonal therapy. So, identifying novel therapeutic targets and developing more effective treatments is needed. One of the key pathways involved in the aggressive nature of TNBC is the Toll-like receptor 4 (TLR4) signaling cascade. To this end, curcumin (CUR) has shown effects consistent with modulating inflammatory stress by inhibiting TLR4/MD-2. This study evaluated CUR at concentrations observed in the bloodstream (0.025–25 ng/mL) in MDA-MB-231 TNBC cells under different glucose conditions (normal, moderate, and severe hyperglycemia) and inflammatory states (LPS-induced), using cell viability assays and molecular docking. A zinc complex (Zn–CUR) was also used. Results were validated through cell viability assays. Under severe hyperglycemia, CUR unexpectedly increased cell viability in a dose-dependent manner, while Zn–CUR had no activity across all glucose levels. In LPS-induced inflammation, CUR exhibited a biphasic, dose-dependent response, being protective at mid-level doses but cytotoxic at higher doses, whereas Zn–CUR showed more consistent effects, consistent with modulation of inflammatory stress. Molecular docking suggests that Zn–CUR binds more stably within the MD-2 hydrophobic pocket than CUR, particularly when bound to LPS, with binding energies of −8.7 and −8.3 kcal/mol, respectively. However, better in silico affinity did not always translate into improved cellular effects. These findings indicate that metabolic context significantly influences CUR’s biological activity and that forming a zinc complex offers a safer, more reliable profile. This positions Zn–CUR as a candidate warranting further investigation for TNBC, particularly in the context of hyperglycemia. Full article

Supply chain risk management has become a core element of corporate strategy, yet systematic evidence on how innovation information disclosure affects supply chain risk remains scarce. We study how innovation information disclosure in firms’ MD&A sections affects supply chain risk. Using data on Chinese A-share listed firms from 2012 to 2023, we find that firms disclosing more innovation-related content face significantly a lower supply chain risk. This result remains true following instrumental variable estimation, propensity score matching, entropy balancing, and controlling for province- and industry-specific time trends. We provide supportive evidence for three circumstances: firms that disclose more have a broader and more diverse set of supply chain partners; they engage in more joint patenting with partners, consistent with higher switching costs and more stable relationships; and they exhibit stronger reputations and commercial credit capacity, consistent with partnerships reinforced through both trust and financial ties. The effect is concentrated among non-SOEs, high-tech firms, firms in competitive industries, and firms outside the digital economy, all settings in which information asymmetry is more severe and alternative channels for conveying innovation capabilities are limited. We also document asymmetric vertical spillovers: downstream customers’ innovation disclosure prompts upstream suppliers to become more transparent, but the reverse does not hold. Supply chain risk, by contrast, affects connected firms in both directions. These findings extend the literature on the economic consequences of innovation disclosure from capital markets to supply chain management. Full article

CCCH zinc-finger proteins constitute a unique class of transcription factors that play vital roles in mediating plant tolerance to biotic and abiotic stresses and regulating various physiological and developmental processes. This study systematically identified and characterized the apple (Malus domestica) CCCH (MdC3H) gene family, aiming to elucidate its evolutionary patterns, functional characteristics, and regulatory mechanisms under drought stress. Genome-wide analysis revealed 85 MdC3H genes, which were unevenly distributed across chromosomes and exhibited significant differences in physiochemical properties, suggesting functional divergence. Phylogenetic analysis classified these genes into 9 subfamilies with distinct conservation. Collinearity analysis indicated a close evolutionary relationship between apple and Malus sieversii, with 150 collinear gene pairs identified, highlighting the conservation of the C3H gene family during speciation. Cis-acting element prediction in promoter regions uncovered abundant stress-responsive elements (e.g., ABRE, DRE, MYB), implying the potential of MdC3H genes in coordinating environmental signals. Functional verification demonstrated that MdC3H49, a key member of the family, is localized in the nucleus and possesses transcriptional activation activity. Overexpression of MdC3H49 in Arabidopsis and apple calli significantly enhanced drought tolerance, characterized by reduced malondialdehyde (MDA) content, relative electrical conductivity, and increased proline accumulation. Mechanistic studies revealed that MdC3H49 directly regulates the expression of MdP5CS, a core gene in proline biosynthesis, thereby strengthening the cellular antioxidant capacity and mitigating drought-induced damage. Collectively, this study establishes MdC3H49 as a critical regulator in apple drought stress response, providing valuable insights into the molecular mechanisms underlying abiotic stress tolerance in perennial plants and laying a foundation for genetic improvement of drought resistance in apple breeding. Full article

Financial disclosure occurs through multiple channels with fundamentally different legal constraints. Mandatory SEC filings undergo extensive legal review under Sarbanes–Oxley Section 302, while the earnings call Q&A segments represent comparatively spontaneous communication protected by safe harbor provisions. This structural difference creates a natural experiment for detecting management of information asymmetry through emotional consistency analysis. This paper presents Cross-Document Emotion Consistency (CDEC), a framework measuring emotional alignment between Management’s Discussion and Analysis (MD&A) sections and earnings call Q&A using domain-adapted 28-dimensional emotion classification. The framework jointly analyzes MD&A and Q&A for cross-channel emotion alignment, linking 8-K filings as external event validation. Neither CDEC nor financial fundamentals alone achieve meaningful risk separation; their interaction does. The integrated framework achieves approximately twice the risk separation of the strongest 3-class sentiment baseline tested (27.4 percentage points vs. 14.6 pp for RoBERTa-based consistency and 8.7 pp for FinBERT), indicating that 28-dimensional emotion granularity captures disclosure risk not detected by standard sentiment classification. The Financial Health Indicator (FHI) achieves an out-of-sample Area Under the Curve (AUC) = 0.671, distinguishing firms likely to beat Standardized Unexpected Earnings (SUE) expectations (62.8% beat rate among large-cap sector-representative firms) from those likely to miss (35.4%). The framework serves as a risk-screening tool for due diligence, internal audit, and regulatory oversight among large-cap firms, identifying firms warranting scrutiny rather than generating trading signals. Full article

Whether firms translate climate risk perception into energy-related operational productivity remains unclear. Panel data on non-financial Chinese firms (2012–2023) are used to examine the association between climate risk perception (CRP) and energy productivity (EE). Firm-level CRP is constructed from management discussion and analysis (MD&A) sections using a term frequency–inverse document frequency (TF–IDF)-weighted, Word2Vec-expanded climate-risk lexicon. Energy productivity (EE) is measured as the natural logarithm of operating revenue per total energy consumption unit converted into tons of coal equivalent, capturing the economic value generated per energy input unit. Two-way fixed-effects models with firm-level clustered standard errors show a positive CRP–EE association. Digital transformation, proxied by an annual report text-based index across five digital technology domains, partially mediates this association, which is stronger when analyst coverage is higher and weaker when financing constraints are more severe. The results are robust to an alternative CRP proxy based on raw keyword frequency, dynamic specifications, and an instrumental-variable approach exploiting province-year extreme-weather exposure (share of days meeting extreme temperature or precipitation thresholds), using leave-one-province-out aggregation as the instrument and systematic heterogeneity across state ownership, pollution intensity, and high-tech status. This study extends CRP research from disclosure-oriented to energy-productivity outcomes, and highlights how digital capabilities, information scrutiny, and financial friction shape climate-aware energy productivity improvements. Full article

Despite stringent environmental regulations, the divergence between private costs and social benefits frequently induces symbolic rather than substantive firm compliance. This study investigates Executive Green Cognition (EGC) as an internal mechanism to mitigate this distortion. Using a text-based index derived from Management Discussion and Analysis (MD&A) disclosures of Chinese listed firms (2010–2024), we demonstrate that higher EGC significantly facilitates corporate green transition by enhancing both green innovation output and Total Factor Productivity. Supporting the micro-foundations of the Porter Hypothesis, we find that these productivity gains coincide with reduced Carbon Emission Intensity (CEI), thereby ruling out scale expansion effects. Mechanism tests indicate that EGC reduces agency costs by reallocating resources from non-productive defensive expenditures to substantive green investments. Furthermore, digital transformation positively moderates this relationship by lowering implementation costs. These findings highlight EGC as a critical micro-foundation for shifting firms from passive compliance to endogenous sustainable development. Full article

Background: Hepatic ischemia-reperfusion injury (HIRI) is a major complication in liver surgery with limited therapeutic options. Houttuynia cordata polysaccharide (HCP), a key bioactive component of the traditional anti-inflammatory herb, has demonstrated immunomodulatory potential, but its effect on HIRI remains unclear. Methods: A murine model of 70% hepatic ischemia for 60 min followed by reperfusion was established. Mice were administered low-dose (50 mg/kg) or high-dose (100 mg/kg) HCP or the positive control N-acetylcysteine (150 mg/kg). Liver injury was assessed by serum ALT/AST levels, histopathology, oxidative stress markers, and inflammatory cytokines. Macrophage polarization and the TLR4/NF-κB pathway were analyzed using flow cytometry, qPCR, and Western blot. The TLR4 inhibitor TAK-242 was used for reverse validation, and molecular docking was performed to predict HCP binding to the TLR4/MD-2 complex. Results: HCP significantly attenuated HIRI-induced liver injury, as shown by reduced ALT/AST, improved histopathological scores, decreased MDA, increased SOD, and lower TNF-α and IL-6 levels. Mechanistically, HCP promoted a shift from M1 to M2 macrophage polarization, with increased CD206⁺ cells and Arg-1/IL-10 expression and decreased CD86⁺ cells and iNOS/IL-1β expression. HCP also suppressed TLR4/MyD88/NF-κB pathway activation, inhibiting NF-κB p65 phosphorylation and nuclear translocation. These protective effects were largely reversed by TAK-242 in vivo and in vitro. Molecular docking indicated stable binding between HCP and TLR4/MD-2. Conclusions: HCP protects against HIRI by targeting TLR4 to inhibit NF-κB signaling, thereby reprogramming macrophage polarization toward the M2 phenotype and alleviating inflammation and oxidative stress. These findings highlight HCP as a promising natural agent for HIRI intervention. Full article

Despite growing interest in sustainable supply chains, we still know relatively little about how environmental requirements transmitted from key customers along the supply chain affect firms’ productivity and long-run economic sustainability. To address this gap, we introduce the notion of green supply chain pressure, downstream customers’ explicit green and low-carbon requirements on suppliers, and examine its implications for firm-level productivity and the mechanisms involved. Using a panel of Chinese A-share listed firms over 2014–2024, we construct a novel text-based index of green supply chain pressure by combining supply-chain relationship data with MD&A disclosures of major customers. Firm-level economic sustainability is measured by Levinsohn–Petrin total factor productivity, with Olley–Pakes estimates used for robustness. Fixed-effects regressions with industry–year and city–year controls show that stronger green supply chain pressure is associated with significantly higher productivity. Mediation analysis reveals that this effect operates partly through three resource-intensive adjustment channels: (i) a higher share of green patents in total innovation, (ii) capital deepening via a higher share of digital and intelligent fixed assets in total net fixed assets, and (iii) human capital upgrading through a larger proportion of highly educated employees. Interaction models further indicate that financing constraints critically condition these gains: the productivity effect of green supply chain pressure is stronger for firms with greater financial slack, and for high-tech, green-attribute and larger firms. Overall, the results highlight supply chain-based governance as a powerful complement to formal regulation for promoting long-run economic sustainability at the firm level. Full article

Building a resilient and efficient supply chain system is critical for sustaining firm operations in an increasingly uncertain global environment. This study examines whether the firm-level exposure to industry-wide robot penetration mitigates firm-level supply chain risks. By adopting Bartik’s instrumental variable approach to decompose industry-level robot data to the firm level (from the International Federation of Robotics, IFR), and using a novel text-mining-based supply chain risk index, constructed via a tailored “supply chain risk” dictionary, to quantify sentences containing both keywords from firms’ annual report MD&A sections, we apply a fixed effects model, and find that robot adoption significantly reduces supply chain risk by enhancing firms’ discourse power and improving supply chain coordination. The effect is more pronounced in firms with higher capital intensity, greater international exposure, stronger regulatory oversight, and better ESG (Environmental, Social, and Governance) performance. By integrating automation adoption with supply chain risk management, this study extends the literature on production economics and supply chain resilience. Our findings reveal that industrial robots, beyond enhancing productivity, function as a risk-mitigating technology that strengthens supply chain stability and operational continuity in volatile global production networks. Full article

Solar ground-layer adaptive optics (GLAO) is widely recognized as a key technology for achieving high-resolution, wide-field imaging in ground-based solar telescopes. However, the accuracy differences among various wavefront sensing methods in solar GLAO remain unclear. In this study, Monte Carlo simulations and indoor GLAO experiments were conducted to perform, for the first time, a comparative analysis of two representative wavefront sensing methods: multi-direction averaging (MD-A) and wide-field correlation (WF-C). The results demonstrate that WF-C consistently achieves higher detection accuracy than MD-A, although the differences between the two methods are small. With an increasing field of view (FoV), the detection accuracy of MD-A improves but remains lower than that of WF-C. In terms of correction performance, significant improvements in central FoV imaging were achieved using WF-C within narrow-to-moderate FoVs, whereas in wide and ultra-wide FoVs, MD-A produced more uniform image quality enhancements. Using the 1 m New Vacuum Solar Telescope (NVST) GLAO system as an example, MD-A is better suited to wide and future ultra-wide field imaging (over 80″), whereas WF-C is more appropriate for high-precision wavefront sensing within narrow to moderate fields (20″–60″). These findings provide both theoretical guidance and practical insights for the optimization of GLAO systems and wavefront sensing strategies in 1-meter-class wide-field solar telescopes. Full article

Acute kidney injury (AKI) is characterized by rapid loss of renal function due to oxidative stress, inflammation, and apoptosis, with limited targeted therapies. Alpha-mangostin (AM), a natural compound from Garcinia mangostana, exhibits antioxidant and anti-inflammatory properties in preclinical studies, but its efficacy in AKI has not been reviewed. This systematic review and meta-analysis, registered on the Open Science Framework and adhering to PRISMA guidelines, analyzed in vivo and in vitro studies on AM’s effects in AKI models through searches of PubMed, Scopus, Embase, and Web of Science. Primary outcomes included serum creatinine and cell viability, while secondary outcomes encompassed oxidative stress markers (malondialdehyde (MDA), glutathione (GSH), reactive oxygen species (ROS)), inflammatory cytokines, apoptosis indicators, and histopathology. Data were extracted independently and assessed using the Toxicological Data Reliability Assessment Tool (ToxRTool). AM significantly reduced serum creatinine (mean difference (MD) = −0.67 mg/dL; 95% confidence interval (CI): −1.28 to −0.06; p = 0.03) and improved cell viability (MD = 28.26%; 95% CI: 17.25 to 39.26; p < 0.0001). It markedly decreased MDA and ROS, increased GSH, and enhanced antioxidant enzymes (glutathione peroxidase (GPx), glutathione reductase (GR), superoxide dismutase (SOD)). In vivo, tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) were lowered, and histopathology showed reduced tubular necrosis and structural damage. Subgroup analyses indicated dose- and model-dependent effects, with lower doses often yielding greater benefits. Sensitivity analyses confirmed robustness despite heterogeneity. Preclinical evidence supports AM’s nephroprotective potential and underscores the need for dose optimization, mechanistic validation, and clinical translation. Full article

Tomato pomace (TP) is a waste product from tomato processing. This study explored its use as a food ingredient by creating an encapsulated TP extract (ETPE). TP was extracted with ethanol using a microwave-assisted method prior to encapsulating with either gum arabic (GA) or maltodextrin (MD) via spray drying. MD was selected for further studies based on its lower moisture content with higher radical scavenging ability, assessed by DPPH assay. Spray drying at 160 °C was chosen due to highest radical scavenging ability (≈14.02%), although lycopene content was not the highest. Application of ETPE in reduced nitrite sausages did not negatively impact the cooking yield, expressible moisture, and textures of samples. The redness and yellowness of sausage were improved significantly (p < 0.05). In addition, a reduction in TBARS from approximately 0.46 to 0.31 mgMDA/kg was found during cold storage for two weeks. In conclusion, the encapsulation of tomato pomace extract can serve as a functional ingredient to produce healthier sausage. Full article

Background: Acute lung injury (ALI) and its severe form, acute respiratory distress syndrome (ARDS), remain major causes of morbidity and mortality, yet no targeted pharmacological therapy is available. Excessive neutrophil and macrophage infiltration drives reactive oxygen species (ROS) production and cytokine release, leading to alveolar–capillary barrier disruption and fatal respiratory failure. Methods: We applied an integrative multi-omics strategy combining single-cell transcriptomics, peripheral blood proteomics, and lung tissue proteomics in a lipopolysaccharide (LPS, 10 mg/kg)-induced mouse ALI model to identify key signaling pathways. Harpagide, an iridoid glycoside identified from our natural compound screen, was evaluated in vivo (40 and 80 mg/kg) and in vitro (0.1–1 mg/mL). Histopathology, oxidative stress markers (SOD, GSH, and MDA), cytokine levels (IL-6 and IL-1β), and signaling proteins (HIF-1α, p-PI3K, p-AKT, Nrf2, and HO-1) were quantitatively assessed. Direct target engagement was probed using surface plasmon resonance (SPR), the cellular thermal shift assay (CETSA), and 100 ns molecular dynamics (MD) simulations. Results: Multi-omics profiling revealed robust activation of HIF-1, PI3K/AKT, and glutathione-metabolism pathways following the LPS challenge, with HIF-1α, VEGFA, and AKT as core regulators. Harpagide treatment significantly reduced lung injury scores by ~45% (p < 0.01), collagen deposition by ~50%, and ROS accumulation by >60% relative to LPS (n = 6). The pro-inflammatory cytokines IL-6 and IL-1β were reduced by 55–70% at the protein level (p < 0.01). Harpagide dose-dependently suppressed HIF-1α and p-AKT expression while enhancing Nrf2 and HO-1 levels (p < 0.05). SPR confirmed direct binding of Harpagide to HIF-1α (KD = 8.73 µM), and the CETSA demonstrated enhanced thermal stability of HIF-1α. MD simulations revealed a stable binding conformation within the inhibitory/C-TAD region after 50 ns. Conclusions: This study reveals convergent immune–microenvironmental regulatory mechanisms across cellular and tissue levels in ALI and demonstrates the protective effects of Harpagide through multi-pathway modulation. These findings offer new insights into the pathogenesis of ALI and support the development of “one-drug, multilayer co-regulation” strategies for systemic inflammatory diseases. Full article

In the context of contemporary climate change, drought is widely recognized as a major stressor affecting plant growth. While numerous studies have demonstrated that Serendipita indica enhances stress resistance in host plants and is widely used in agriculture, research on its symbiotic interactions with woody plants for improving drought tolerance remains limited. This study investigated the effects of S. indica inoculation on the growth of Phoebe sheareri seedlings under varying drought conditions—well-watered (WW), moderate drought (MD), and severe drought (SD)—and explored the physiological mechanisms underlying improved drought resistance. The results showed that under WW conditions, S. indica inoculation promoted seedling growth and development. Under MD and SD conditions, although drought stress inhibited growth, inoculation significantly increased plant biomass, root parameters, chlorophyll content, and photosynthetic efficiency. Additionally, it alleviated drought-induced damage by reducing REC, MDA, H₂O₂, and O₂⁻ levels, while enhancing SOD, POD, and CAT activities, and increasing root ABA, GA, IAA, and CTK content. Under MD stress, adaptive changes in root architecture and hormone levels were observed, including increases in total root length, surface area, volume, average diameter, and elevated IAA and CTK levels—all of which were further enhanced by S. indica inoculation. In conclusion, symbiosis with S. indica improved drought tolerance in P. sheareri seedlings likely through enhanced photosynthesis, antioxidant enzyme activity, and hormone regulation. Full article

The textual analysis of Management Discussion and Analysis (MD&A) reveals valuable insights into corporate operational performance and future risks. However, techniques for accurately extracting sentiment from unstructured Chinese MD&A texts still lack comprehensiveness. Existing studies related to sentiment analysis often use lexicon-based methods, which rely on predefined, context-agnostic word lists and accurate Chinese word segmentation and struggle with domain-specific terminology, leading to limited accuracy and interpretability. Although research has attempted to develop context-aware lexicons and language models, these methods still face limitations when applied to long and complex financial texts. To address the limitations, we propose MDARisk, a novel framework for corporate misconduct prediction. The core of MDARisk is a MultiSenti module, which leverages a multi-agent LLM approach to extract comprehensive and contextual sentiment from MD&A. Unlike lexicon methods, our LLM-based module interprets words based on their surrounding semantic context, allowing it to decipher nuanced expressions and specialized financial language. We first conduct an econometric validation using fixed-effects logit models to test whether the MultiSenti-derived MD&A sentiment is significantly associated with subsequent corporate misconduct. We then evaluate out-of-sample predictive utility by adding this sentiment feature to multiple classifiers and assessing its incremental gains over the baseline model. Empirical results demonstrate that our approach provides a more reliable sentiment-based indicator for misconduct risk, achieves higher predictive accuracy, and outperforms the traditional financial sentiment analysis approach. Our MDARisk framework provides a cost-efficient approach for automated disclosure screening, benefiting auditors, regulators, and investors in assessing potential misconduct risks. Full article