Search Results (8,222)

A simple and efficient QuEChERS-HPLC-DAD method was developed and validated for the simultaneous determination of benzoic acid, sorbic acid, and eight parabens in diverse food matrices. The sample preparation procedure was systematically optimized by evaluating the extraction solvent composition, salting-out conditions, and dispersive solid-phase extraction clean-up to achieve satisfactory recoveries while minimizing matrix interferences. Chromatographic separation was accomplished using isocratic elution on a C18 column with dual-wavelength ultraviolet detection, enabling the simultaneous determination of both authorized preservatives and non-authorized parabens within a single analytical run. The validated method exhibited excellent linearity (R² > 0.996), low to moderate matrix effects (within ±20%), satisfactory recoveries (79–112%), and good precision (RSD < 7.3%), meeting the performance criteria for routine residue analysis. The applicability of the method was demonstrated by analyzing commercial food samples from six food categories. Benzoic acid and sorbic acid were the most frequently detected preservatives, whereas only methylparaben and propylparaben were identified among the investigated parabens. No non-authorized parabens were detected in the analyzed samples. Owing to its simplicity and reliability, the proposed QuEChERS-HPLC-DAD method represents a practical analytical approach for routine multi-matrix monitoring of food preservatives in quality control and food safety laboratories. Full article

Small penetrator probes have been proposed regularly as low(er) cost landing elements, particularly for network science. This study reviews such a concept with regard to its soil penetration capability with numerical and experimental investigations. A reference micro Mars lander (MML) is considered to deliver a 10 kg payload to the Martian surface. It decelerates the penetrator probe with a mechanical decelerator to 40–60 m/s before impact. The remaining kinetic energy is distributed to the soil and an internal load limiter on impact, which restricts the maximum g-load acting on the payload. A semi-empirical force–displacement law and a discrete element method simulation were used to describe penetration behavior. Major impact force constituents are the velocity-dependent, drag-like displacement of the soil particles and the compaction of soil along the penetration path. Based on the simulation results, a test penetrator was designed and tested by impacting it on different soil conditions with a maximum impact velocity of 10 m/s. Cohesive Mars soil simulant, non-cohesive quartz sand, and stones of various sizes were used to assess different impact conditions. The comparison of test and simulation data identifies their respective capabilities and limitations. Recommendations for use and findings for further research are deduced therefrom. Full article

Background: Intracellular Ca²⁺ dysregulation and neurovascular dysfunction are increasingly recognized as important mechanisms underlying neurodegenerative disorders, including Alzheimer’s disease (AD). Restoration of pathological Ca²⁺ imbalance has therefore emerged as a potential therapeutic strategy. Although ginsenoside compound K (CK) has demonstrated neuroprotective and anti-inflammatory properties, its role in Ca²⁺ homeostasis remains unclear. Methods: SH-SY5Y neuronal cells, U373 astrocytes, BV2 microglia, bEND brain endothelial cells, and MOVAS vascular smooth muscle cells were exposed to trimethyltin chloride (TMT, 5 μM, 24 h). Cell viability, real-time cell confluence, intracellular Ca²⁺ influx, and endoplasmic reticulum (ER) Ca²⁺ store release were evaluated. Ca²⁺ dynamics were analyzed using Fura-2 fluorescence, and signaling associated with CK-mediated Ca²⁺ regulation was investigated using pharmacological inhibitors. Orai1 protein expression was evaluated by Western blot analysis in SH-SY5Y and U373 cells. Results: TMT increased store-operated Ca²⁺ entry (SOCE)-mediated Ca²⁺ influx in SH-SY5Y neuronal cells without significant cytotoxicity. In contrast, TMT reduced both Ca²⁺ influx and cell viability in U373 astrocytes, BV2 microglia, and MOVAS cells, whereas bEND cells showed minimal changes. CK restored abnormal Ca²⁺ responses in a cell type-specific manner, reducing elevated Ca²⁺ influx in neuronal cells while restoring suppressed Ca²⁺ signaling in astrocytes. Consistent with these functional findings, Orai1 protein expression was increased by TMT in SH-SY5Y cells and attenuated by CK, whereas TMT reduced Orai1 expression in U373 cells, which was restored by CK. Pharmacological analyses suggested involvement of PKA- and LTCC-associated signaling in neuronal cells and PLC- and PLD-associated signaling in astrocytes. In both cell types, CK-associated Ca²⁺ responses were sensitive to NAC and the SOCE inhibitor BTP2, supporting ROS- and SOCE-associated mechanisms. Additional controls showed no significant inhibitor effects under control or CK-only conditions, strengthening the pharmacological interpretation of responses under TMT-containing conditions. Conclusions: TMT-induced Ca²⁺ dysregulation differed markedly by cell type. CK restored disrupted Ca²⁺ homeostasis in association with distinct pharmacological signaling profiles in neuronal and astrocytic cells. These findings suggest that CK may function as a cell type-specific Ca²⁺ homeostatic regulator under neurotoxic stress conditions and highlight the importance of differential Ca²⁺ regulation in neurodegenerative disease models. Full article

Immunohistochemistry (IHC) of ER, PR, HER2, and Ki67 are established prognostic and predictive markers in breast cancer. Gene expression assays such as PAM50 and Oncotype DX are increasingly used for molecular subtyping and recurrence risk calculation. The APIS Breast Cancer Subtyping Kit (BCSK) quantitatively measures the mRNA expression of these markers (ER, PR, HER2, and Ki67) and includes a novel four-gene BCSK Proliferation Signature (PS) designed for subtype classification and risk stratification. This exploratory retrospective cohort study compares the BCSK with established molecular assays in an age-stratified cohort. We aimed to compare BCSK subtype classification in distinguishing Luminal A versus Luminal B subtypes with IHC and with PAM50. We have also aimed to assess correlations between the BCSK PS and the Oncotype DX Recurrence Score (RS) as well as the PAM50 Risk of Recurrence (ROR) score in patients stratified by age (<65 versus ≥65 years). Formalin-fixed, paraffin-embedded (FFPE) tumor specimens from 59 patients with ER+/HER2− breast cancer (33 < 65 years, 26 ≥ 65 years), diagnosed between 2020 and 2022 at the Cantonal Hospital Baselland and University Hospital Basel, were analyzed using IHC, BCSK, and PAM50 (Prosigna^®). All patients received adjuvant therapy and had ODx scores available. Patient, disease and treatment characteristics were compared between age groups using the Fisher exact test. We assessed concordance in luminal subtype classification across IHC, BCSK, and PAM50 assays pairwise and stratified by age groups descriptively. We used Spearman’s rank correlation to examine associations between BCSK PS, RS, and ROR. Differences between age groups regarding PS were analyzed using the Mann–Whitney U test. In the ≥65-year cohort, subtype classification concordance between the BCSK and PAM50 was higher (84.6%) than in those aged <65-years (60.6%). In patients aged <65 years, the PS was significantly correlated with both RS (ρ = 0.5745, p < 0.0005) and ROR (ρ = 0.391, p = 0.024), whereas RS and ROR were not significantly correlated. In patients ≥65 years, PS correlated significantly with ROR (ρ = 0.603, p = 0.001), while there were no significant correlations between PS and RS (ρ = 0.134, p = 0.514) and between RS and ROR (ρ = 0.149, p = 0.466). Median PS values did not significantly differ between age groups (0.589 versus 0.602, p = 0.97). In this exploratory retrospective age-stratified analysis, the BCSK demonstrated descriptive concordance with PAM50 subtype classifications, especially in patients aged ≥65 years. PS showed significant but moderate correlation with the established molecular recurrence scores RS and ROR, however these differed across age groups. Our findings should be considered hypothesis-generating because this study did not include outcome metrics and was based on a relatively small cohort. Larger prospective studies incorporating clinical outcomes are necessary to determine the diagnostic and prognostic utility as well as comparative cost-effectiveness of the BCSK and its utility across age groups. Full article

Chilo sacchariphagus is a destructive sugarcane borer worldwide, and frequent extreme high temperatures disrupt its field populations. Clarifying larval thermal response mechanisms provides theoretical support for pest risk prediction under climate warming. Previous work has illustrated moderate heat induces canonical HSP activation, but the molecular responses of this pest to 41 °C extreme heat remain unclear. As such, we conducted non-reference transcriptome sequencing and 11 physio-biochemical assays on fifth-instar larvae exposed to 41 °C for 12 h (26 °C as control) to characterize its thermal regulatory network. De novo assembly yielded a comprehensive transcriptome resource, and analysis of differentially expressed genes revealed enrichment in energy metabolism, ER protein processing, MAPK signaling and autophagy pathways. Core HSP70/40 transcripts were significantly down-regulated while HSP80 showed stable transcription, suggesting that 41 °C may exceed the heat-shock protective threshold and potentially trigger heat damage. qRT-PCR validation of seven core stress genes confirmed the RNA-seq trends. Catalase (CAT) activity increased significantly; however, none of the annotated catalase genes showed transcriptional changes, whereas elevated CarE and AchE activities also lacked corresponding transcriptional shifts, implying post-translational or alternative regulatory mechanisms. Our data showed coordinated transcriptional and physiological changes under extreme heat. These findings provide a basis for further investigation into how C. sacchariphagus may respond to extreme heat under climate warming scenarios. Full article

Uremic conditions are common in end-stage kidney disease (ESKD) patients. Accelerated vascular diseases in uremic patients lead to heart failure, stroke, and hypertension. To investigate the effects of uremia on porcine arterial smooth muscle cells (aSMCs), bulk RNA sequencing was used to identify uremia-induced alterations in signaling pathways of aSMCs that might explain the aggressive cardiovascular diseases seen in patients with chronic kidney disease (CKD) and ESKD. Bulk RNA sequencing was performed on porcine aSMCs cultured with serum from normal or uremic pigs. Differentially expressed gene (DEG) analysis revealed that 295 genes were upregulated and 138 genes were downregulated after uremic serum exposure. Gene Ontology molecular function analysis demonstrated that ATP-dependent activity, translation factor activity, and ATP-dependent protein folding chaperones were predicted to be negatively enriched after uremic serum exposure, while proton transmembrane transporter activity, antioxidant activity, and glutathione peroxidase activity were predicted to be positively enriched. Gene set enrichment analysis indicated that the cell cycle was predicted to be negatively enriched after uremic serum exposure in aSMCs. Overrepresentation analysis found that focal adhesion, protein processing in the endoplasmic reticulum (ER) and cell senescence were predicted to be negatively enriched, while lysosome, phagosome, apoptosis, and autophagy were predicted to be positively enriched after uremic serum exposure. This study suggests that the signaling pathways that regulate cellular redox homeostasis, the cellular waste disposal system, ER stress and autophagy are major signaling pathways involved in aSMCs’ responses to uremic serum exposure. These pathways may contribute to the severe arterial-specific clinical symptoms observed in CKD/ESKD patients, such as arterial stiffness, vascular calcification and cardiovascular disease. Full article

Background/Objectives: Alternative splicing (AS) contributes substantially to transcriptomic diversity and has emerged as an important regulator of cancer progression. However, the genome-wide characterization of AS events specific to estrogen receptor (ER)-positive breast cancer remains limited. This study aims to comprehensively profile AS in ER-positive breast cancer and identify a prognostic AS signature associated with patient outcome. Methods: Clinical and splicing data (Percent Spliced In values) were obtained from The Cancer Genome Atlas (TCGA) for 737 ER-positive samples. Prognostic AS events were identified using Cox regression analysis. The Least Absolute Shrinkage Selection Operator (LASSO) model was used to construct an AS-based prognostic signature, and a standardized risk score was calculated for each sample. The signature was then evaluated by Kaplan–Meier (KM) analysis and receiver operating characteristic (ROC) curves, in addition to other methods to validate model performance. Furthermore, transcript-level annotation and RNA expression correlation were performed to evaluate biological relevance. Results: Profiling identified 6276 AS events across 4457 genes, with exon skipping (ES) representing the most prevalent class (34.4%). Model analysis established a novel five-event AS prognostic signature (comprising DNAJC14, BAZ2B, PCDHAC1, PCDHA7, and DAPL1). The signature significantly stratified patients into high-risk and low-risk groups for both disease-free survival (DFS; p < 0.001) and overall survival (OS; p < 0.001). HER2-specific analysis demonstrated more consistent performance in HER2-negative patients for both DFS (p < 0.001) and OS (p = 0.018). The model achieved area under the curve (AUC) of 0.804 for 60-month follow-up supporting long-term prognostic performance. Additionally, the signature demonstrated stable and reliable discrimination with a concordance index (C-index) of approximately 0.73 across multiple validation methods. Conclusions: The study identified AS signature with promising prognostic value in ER-positive breast cancer. This highlights the potential of splicing-based models to refine risk stratification beyond conventional gene expression analysis. Full article

Background/Objectives: Breast cancer exhibits substantial molecular heterogeneity, resulting in diverse therapeutic vulnerabilities and limiting the efficacy of single-agent therapies. Although multi-target strategies may offer improved therapeutic benefit, the systematic identification of synergistic higher-order target combinations remains challenging. This study aimed to identify and validate effective higher-order target combinations for heterogeneous breast cancer. Methods: DeepMDS, a previously developed deep learning-based multi-compound synergy prediction model, was used to prioritize candidate target combinations for breast cancer. Exhaustive two-target and three-target combinations were ranked in the gene-expression contexts of ER-positive luminal-like MCF-7 and triple-negative MDA-MB-231 breast cancer cells. The top-ranked target combinations were evaluated using single, pairwise, and triple small interfering RNA (siRNA) perturbations. Representative inhibitors were subsequently assessed in fixed-ratio combinations in MCF-7, MDA-MB-231, and 4T1 cells and in a 4T1 syngeneic mouse experiment. Results: BIRC5-NAMPT-TOP1 ranked first in both cell lines. Triple siRNA co-transfection targeting BIRC5, NAMPT, and TOP1 produced the strongest antiproliferative effects, with inhibition rates of 62.94% in MCF-7 cells and 55.62% in MDA-MB-231 cells. The corresponding inhibitors, LQZ-7I, FK866, and topotecan, exhibited synergistic antiproliferative activity at multiple molar ratios, with combination index values below 1. The optimized 2.5:10:1 molar ratio showed strong synergy in MCF-7, MDA-MB-231, and 4T1 cells, with combination index values of 0.26, 0.19, and 0.15, respectively. In tumor-bearing mice model, the triple-inhibitor regimen achieved a tumor inhibition rate of 62.05%. Topotecan-containing groups showed hematological alterations, whereas no statistically detectable elevations were observed in the measured terminal serum hepatic or renal biomarkers. Conclusions: The BIRC5-NAMPT-TOP1 combination showed reproducible phenotypic activity in the tested genetic and pharmacological models. These findings support the use of DeepMDS as a hypothesis-generation tool for higher-order target prioritization. Full article

Fluorinated pesticides are an emerging class of environmental contaminants owing to their widespread agricultural use, high persistence, and ability to generate highly stable per- and polyfluoroalkyl substances (PFAS) during environmental degradation. Active ingredients containing fluorinated moieties undergo photolytic, hydrolytic, and microbial transformation, producing persistent metabolites such as trifluoroacetic acid (TFA), TFNA, TFNG, AMTT, and FM-6-1, which are highly mobile substances and may enter the food chain. To address this challenge, complementary LC–MS/MS and GC–MS/MS methods combined with QuEChERS and methanol extraction, and a modified QuPPe-based procedure for TFA and DFA were developed and validated for the determination of 76 fluorinated analytes, including fluorinated pesticides and selected transformation products with diverse physicochemical properties. Validation of the analytical workflow included the assessment of limits of quantification (LOQs), recovery, precision, expanded measurement uncertainty, and matrix effects at three spiking levels. LOQs ranged from 0.002 to 0.050 mg kg⁻¹. Recoveries were 63.9–114.7% for GC–MS/MS and 40.3–109% for LC–MS/MS. The validated analytical workflow is suitable for monitoring fluorinated pesticides and selected transformation products in potatoes, onions, pears, watermelons, carrots, and cauliflower and may support routine food-safety control. Full article

In this paper, we introduce and systematically investigate several classes of localized Baer-type rings associated with a fixed idempotent element e, namely e-Baer, e-quasi-Baer, e-p.q.-Baer, e-PP, and e-APP rings. We develop a unified structural framework relating these localized annihilator classes to weak localized zero-product conditions, including weak e-symmetric, weak e-reversible, weak e-reflexive, and weak e-semicommutative properties. We establish the principal implication relations among these classes and, under suitable hypotheses, obtain equivalence results connecting several localized and global conditions. Examples and counterexamples are provided to distinguish the classes and to demonstrate the failure of converse implications in general. We further study the behavior of localized annihilator conditions under various algebraic constructions and infinite operations. In particular, we establish permanence and transfer results for left e-APP rings under matrix, polynomial, Laurent polynomial, monoid, skew monoid, and skew polynomial extensions, as well as under Morita equivalence. For formal power series extensions, where the left APP property is not preserved in general, we obtain two sufficient conditions on the corner ring eRe that ensure preservation of the left e-APP property. We also establish structural equivalences between left e-APP and left e-p.q.-Baer rings under suitable finiteness assumptions. These results provide a systematic connection between classical annihilator theory and its localized counterpart and extend the study of localized regularity and Baer-type properties in ring theory. Full article

Chinese hamster ovary (CHO) cells are the principal platform for manufacturing recombinant biopharmaceuticals, but sustained production can exceed the protein-folding capacity of the endoplasmic reticulum (ER). Binding immunoglobulin protein (BiP/GRP78), encoded by Hspa5, is a major ER chaperone that supports folding and modulates unfolded protein response (UPR) signaling, yet increasing BiP abundance has produced beneficial or inhibitory outcomes depending on the recombinant product. Here, we introduced an additional Chinese hamster Hspa5 coding sequence under the constitutive EEF1A1 promoter into a CHO line producing a dulaglutide analogue comprising a modified GLP-1 peptide fused to human IgG4 Fc and compared the resulting stable DUL-BiP population with an empty-vector DUL-Neo control. At constant 37 °C, the two populations showed similar viable cell density and viability trajectories, whereas DUL-BiP cells continued extracellular GLP-1–Fc accumulation for approximately two days after accumulation in DUL-Neo cells had slowed and reached a 40% higher final titer in this experiment. Two independent temperature-shift experiments showed the same direction of the final-titer difference, although the increases were smaller and were accompanied by reduced peak viable cell density. Semi-quantitative immunoblot analysis of samples from the constant-temperature experiment showed a comparatively stable total BiP signal in DUL-BiP cells and a pronounced late increase in DUL-Neo cells, together with temporal changes in cleaved ATF6, eIF2α phosphorylation, and CHOP in both populations. Intracellular GLP-1–Fc did not progressively accumulate. Because the immunoblot time courses were derived from one biological fed-batch experiment, they are interpreted descriptively rather than as independent quantitative biological replicates. Stable constitutive expression of host-derived BiP was therefore associated with prolonged late-stage GLP-1–Fc accumulation in the producer population examined. These kinetics are compatible with a model in which the timing of ER chaperone supply influences the maintenance of productive output, while the underlying mechanism and generality to other producer populations or recombinant products remain to be established. Full article

Background/Objectives: Estrogen receptor immunohistochemistry (ER-IHC) exhibits heterogeneous staining and substantial class imbalance, complicating segmentation of ordered expression categories. We evaluated whether class weighting, minority-focused crop sampling, adaptive minority curriculum (AMC), and Focal–Tversky optimization improved a common ResUNet-DS backbone for segmenting background/non-target pixels and C1 ER-negative, C2 weak-positive, C3 moderate-positive, and C4 strong-positive foreground categories. Methods: The dataset comprised 220 paired $512\times 512$ image–mask patches organized into 44 recovered five-patch source groups. A source-group-preserving nested five-fold design used outer folds of 45, 45, 45, 45, and 40 patches. Six controlled training conditions were compared, with four independently selected inner models ensembled for each condition and outer fold. Results: Unweighted random training achieved the best numerical mean for all five primary endpoints: foreground Dice ($0.7479\pm 0.0123$), C2–C4 Dice ($0.7098\pm 0.0128$), foreground IoU ($0.6074\pm 0.0147$), foreground quadratically weighted kappa ($0.9761\pm 0.0040$), and foreground-ordinal MAE ($0.0446\pm 0.0062$). Weighted random training was the strongest weighted/minority-sensitive condition but did not exceed the unweighted reference. None of 25 paired outer-fold comparisons reached $p<0.05$; the minimum raw p-value was $0.0625$, and all Holm-adjusted p-values were $0.3125$. A 20,000-replicate paired source-group bootstrap preserved the same overall ordering. Conclusions: More complex imbalance-handling strategies did not improve aggregate segmentation over unweighted training. Post hoc analyses showed scope-dependent probability quality and error ranking. IHC4BC provided expression-ordering consistency but not direct external segmentation validation. The findings support preliminary source-group-preserving methodological evidence rather than patient-level, whole-slide, or clinical validity. Full article

Diabetic nephropathy (DN) is a major complication of chronic hyperglycemia. Although fish gelatin hydrolysate has antioxidant, anti-inflammatory, and antihypertensive properties, its renoprotective effects in DN remain unclear. This study investigated its effects on renal oxidative stress, inflammation, fibrosis, and endoplasmic reticulum (ER) stress in diabetic rats. Thirty male Wistar rats were fed a normal chow diet or a high-fat diet for 4 weeks. Diabetes was induced in high-fat-diet-fed rats by a single intraperitoneal injection of streptozotocin (30 mg/kg). Diabetic rats were randomly assigned to receive no treatment (untreated diabetes), gelatin hydrolysate at 250 or 500 mg/day, or metformin at 100 mg/kg/day groups (n = 6/group), while normal-chow-fed rats served as controls. Treatments were orally administered for 8 weeks. High-dose gelatin hydrolysate improved metabolic disturbances and renal dysfunction, whereas low-dose gelatin hydrolysate and metformin more effectively reduced oxidative stress, as indicated by decreased 8-OHdG expression. All treatments reduced renal injury, fibrosis, and inflammatory markers. ER stress-related proteins were also attenuated, with the greatest changes observed in IRE1/XBP1-associated markers. These findings provide in vivo evidence that GLH treatment is associated with improved renal outcomes and reduced markers of oxidative stress, inflammation, fibrosis, and ER stress in DM rats. Full article

This study examines the relationship between “image” (xiang 象) and “simulation” (xiang2 像) in Qian Yiben’s theory of “simulating images” (xiangxiang 像象) and argues that this relationship constitutes a reconstruction of how cosmic principle (li 理) becomes manifested in human affairs. The central problem this study addresses is the precise meaning of “image” and “simulation” in Qian Yiben’s thought: what does it mean for “images” to “simulate,” and how does this bridge the gap between the hidden dao of Heaven and Earth and human affairs? Qian opposes both the view of taking “images” as “imaginable approximation,” and “principles abstract truths to be grasped apart from images.” Instead, he insists that “images” and “simulation” form a unity: “images” refer to simulations, and “simulation” is the process by which principles are embodied in human life. Therefore, Qian Yiben proposes his theory of “simulating images” on three interconnected perspectives. Cosmologically, “images” are generated throughout the interaction of yin and yang and realized through the human heart/mind (xin 心). From the perspective of cultivation, “knowing images as simulations” guides the practitioner from observation to profound, inscrutable and wondrous insight as divinities. Practically, “simulation” culminates in the practitioner’s active embodiment of the dao through participation in the three powers (sancai 三才, Heaven, Earth, Humanity); one “establishes the dao through oneself” (dao zi wo er li 道自我而立), thereby participating in the ceaseless creation and generation of the cosmos. Qian’s theory thereby reveals the religious and metaphysical dimensions of late-Ming Yijing scholarship. Full article

Digital pathology and computational analysis of breast cancer require datasets that connect microscopic images with clinically meaningful diagnostic, morphological and immunohistochemical information. But images are often provided separately from pathomorphological reports, tumour profiles, biomarker assessments and segmentation masks, which limits their use for interpretable machine learning. This data descriptor presents a structured dataset of de-identified breast cancer cases that integrates H&E images, immunohistochemical images for ER, PR, HER2/neu and Ki-67, PNG cell segmentation masks and JSON-based clinical and morphological metadata. The dataset was formed from archival histological material, digitised microscopic fields of view and expert-verified diagnostic information. Each JSON record links the patient-level description, tumour profile, staining type, image file, mask file and marker-specific assessment, including Allred score fields for relevant immunohistochemical images. The proposed structure provides traceability from the diagnostic conclusion to individual image fields and associated masks. The dataset is intended to support research on tumour classification, cell segmentation, immunohistochemical marker quantification, HER2-related image analysis, Allred score modelling and explainable artificial intelligence in computational pathology. Full article