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Correction: Morphometric analysis of the human common hepatic artery reveals a rich and accessible target for sympathetic liver denervation

Janus Palladium Membrane Electrode Enables Competent Hydrodehalogenation via Hydride Transfer

Phytochemical profiling and in vitro biological activity evaluation of Lavandula angustifolia flower essential oil

Expression of Concern: An Improved Migratory Birds Optimization Algorithm for Closed- Loop Supply Chain Network Planning in a Fuzzy Environment

Developing Dynamic Ion Transport Channels in Polymer Solid Electrolytes for High-Performance Lithium Metal Batteries

Effective removal of dyes from aqueous systems by waste-derived carbon adsorbent: physicochemical characterization and adsorption studies

Abstract Due to their cost-effectiveness and high surface area, activated carbons are commonly used for the adsorption of dyes from aqueous solutions. In this study, activated carbon was synthesized from walnut shell waste via KOH activation (1:3 ratio), yielding a surface area of 2347.4 m²/g. Reactive Blue 19 and Reactive Red 195 adsorption behavior were studied under varying experimental conditions. These included natural pH values (6.8–7.2), dye concentrations between 50 and 1250 mg L⁻¹, and adsorbent dosages ranging from 0.1 to 1.0 g. Adsorption equilibrium was achieved within 150 min. The maximum adsorption capacities were found to be 1227.17 mg g⁻¹ for RB 19 and 235.74 mg g⁻¹ for RR 195. Isotherm modeling was conducted using Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich models, with Freundlich providing the best fit for both dyes, indicating multilayer adsorption on heterogeneous surfaces. Thermodynamic analysis revealed that the adsorption processes were spontaneous and endothermic, with negative Gibbs free energy (ΔG°), positive enthalpy (ΔH°), and positive entropy (ΔS°) values. These results highlight the high adsorption performance and practical potential of walnut shell-derived activated carbon for dye removal from wastewater.

Homocysteine induces ferroptosis in cardiomyocytes by disrupting β-catenin/GPX4 pathway

Background Homocysteine can cause damage to cardiomyocytes, but the exact mechanism underlying that injury is unknown. And, ferroptosis contributes to both the initiation and progression of cardiac diseases. This study aims to focus on homocysteine to investigate the involvement of β-catenin/GPX4 signaling in ferroptosis of cardiomyocytes. Methods In this study, C57BL/6 mice were utilized to establish an experimental model. Hyperhomocysteinemia was induced in the animal model by administering homocysteine at a concentration of 1.8 g/L in the drinking water. Model mice received the treatment of deferoxamine (DFO) and ferrostatin-1 (Fer-1) as therapeutic interventions. Western blot was utilized to detect β-catenin, FTH1, and GPX4. Lipid ROS, Fe2+, and GSH were detected by biochemical assays. In addition, β-catenin and GPX4 expression were assessed by immunostaining techniques. Cell viability was assessed using CCK-8 assay, and mitochondrial damage was examined by transmission electron microscopy. ChIP combining dual luciferase reporter gene assay was performed to analyze the interaction between β-catenin protein with the promoter of GPX4 gene. Results Homocysteine inhibited β-catenin activity and GPX4 expression, and promoted cardiomyocytes ferroptosis in vitro and in vivo. Overexpression of β-catenin promoted the expression of GPX4 and subsequently inhibited homocysteine-induced ferroptosis in cardiomyocytes. Further, results from the ChIP assay and dual-luciferase reporter assay indicated that GPX4 acted as a target gene of β-catenin. Conclusion Homocysteine induces ferroptosis in cardiomyocytes by disrupting β-catenin activity, subsequently downregulating its target gene, GPX4.

Au-Catalyzed Aerobic Dehydrogenative Aromatization to <i>m</i>-Phenylenediamine Derivatives via Product Selectivity Control

Light-Off Salient Effect: Thermal Phase Transitions of Molecular Crystals Controlled by Photoirradiation

Uracil derivatives/ursolic acid hybrids - naturally derived compounds as anticancer agents

Limited predictive value of traditional comorbidities for readmission in acute decompensated heart failure

Background Common comorbidities in heart failure (HF), including chronic kidney disease (CKD), diabetes mellitus (DM), ischemic heart disease (IHD), and atrial fibrillation, are frequently presumed to predict hospital readmission. However, recent studies have challenged their predictive strength, raising questions about their clinical utility for risk stratification. Methods We conducted a retrospective cohort study of 7,652 patients admitted with acute decompensated heart failure (ADHF) at a tertiary center between 2007 and 2017. Associations between comorbidities and readmission at 30 and 100 days were assessed using Fine-Gray competing risk models, with death as a competing event. Subdistribution hazard ratios (sHRs) were reported. Model performance was evaluated using receiver operating characteristic (ROC) analysis and area under the curve (AUC) values, assessing individual comorbidities and incremental combinations. All comorbidities were included irrespective of univariable significance, based on clinical relevance. Results Several comorbidities were significantly associated with readmission, including CKD (sHR 1.16–1.23), DM (sHR 1.18–1.27), IHD (sHR 1.10–1.15), and anemia (sHR 1.11). However, predictive power was poor. For 30-day readmission, AUC values ranged from 0.516 (COPD) to 0.529 (CKD), with a maximal AUC of 0.555 when combining the four strongest predictors. For 100-day readmission, AUC values ranged from 0.528 (DM) to 0.545 (CKD), with a maximal combined AUC of 0.593. Conclusions Despite consistent statistical associations, common comorbidities perform poorly as predictive tools for identifying individual patients at risk of HF readmission. These findings highlight the need for more robust risk models integrating dynamic clinical, laboratory, and patient-centered factors.

Inverse Trans Influence and Uranium-Arene σ-Bonding Drive Molecular Geometry: Ligand Modification from Hard to Soft Flips the Oxide from Axial to Equatorial

Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records

HU to RGB transformation with automatic windows selection for intracranial hemorrhage classification using ncCT

This work focuses on preprocessing for classifying five categories of Intracranial Hemorrhage (ICH) using non-contrast computed tomography (ncCT). It involves assigning suitable values to window-width (WW) and window-level (WL) parameters to map Hounsfield Units on ncCT to compatible color components like RGB for display. However, clear visualization is hindered by brain component variations, individual patient conditions, and time elapsed since stroke onset. This paper introduces a preprocessing technique called HU to RGB Transformation (HRT), aimed at enhancing the visualization of hemorrhage on ncCT scans. HRT dynamically selects optimal WW and WL values from predefined settings to accentuate hemorrhage visibility. Furthermore, it leverages multiple brain components, including cerebrospinal fluid and white-and-gray matter, to further refine the delineation of hemorrhagic regions. Experimental results from a deep neural network-based image classification model are utilized to evaluate the effectiveness of the proposed method. This method, serving as an image preprocessing step, demonstrates remarkable capability in classifying five distinct types of Intracranial Hemorrhage and normal slice, achieving an average sensitivity of 89.35% and an average specificity of 96.03%. Moreover, direct assessment of HRT preprocessed images leads to enhanced type classification accuracy by residents, with a sensitivity of 97.39% and a specificity of 96.19%. These results surpass those obtained from reading DICOM files achieving 93.31% sensitivity and 94.81% specificity.

Chemically Inducible Cyclic Dinucleotides as Self-Deliverable STING Agonists with Enhanced Antitumor Immunity

Green synthesis of Mn-doped iron oxide nanoparticles using sugarcane juice for magnetic hyperthermia applications

Abstract In this study, ecofriendly un-doped (0%), 5%, and 9% Mn-doped iron oxide nanoparticles were synthesized using sugarcane juice as reducing agents. X-ray diffraction (XRD) confirmed the high purity and crystalline nature of the undoped and Mn-doped iron oxide nanoparticles. Fourier transform infrared spectroscopy (FTIR) was used to investigate the surface functional groups involved during the reducing and capping process. The internal structure of the particles was examined using high resolution transmission electron microscope (HRTEM). The particles exhibited semi-spherical shapes, with mean particle size of 9.3, 9.5 and 13.5 nm for the 0, 5 and 9% Mn-doped samples, respectively. The magnetic properties of the nanoparticles were measured by studying the magnetic field dependence of magnetization at 300 K and 2 K up to 4 T. The samples displayed hysteretic behavior characteristic of ferromagnetic materials at 2 K and typical superparamagnetic features at 300 K. The magnetic heating properties under AC magnetic fields were investigated to assess the feasibility of the synthesized NPs for magnetic hyperthermia application. The specific absorption rate (SAR) values of the iron oxide nanoparticles increased with the Mn-doping level. The results suggest that the green synthesis of un-doped and Mn-doped iron oxide nanoparticles holds promising potential for magnetic hyperthermia treatment.

Impact of the COVID-19 pandemic on pregnancy complications and conceptions resulting in births following spontaneous conception and in-vitro fertilization in British Columbia: A population-based study

Objectives To investigate the impact of the COVID-19 pandemic’s onset on clinical and demographic characteristics, pregnancy complications, and monthly conception rates resulting in births through spontaneous conceptions and in-vitro fertilization (IVF) in British Columbia (BC), Canada. Materials and methods This retrospective population-based cohort study examined individuals who gave birth (both live births and stillbirths) in BC between June 1, 2010, and March 31, 2021, with estimated conception dates from January 1, 2010 to June 30, 2020. Data were obtained from the BC Perinatal Data Registry. Two groups were identified based on the estimated conception date: the pre-pandemic conception group (conception from January-1–2010 to February-29–2020) and the pandemic conception group (conception from March-1–2020 to June-30–2020). A time series forecasting method (ARIMA) was employed to observe trends in conception rates during the study period. Results 304,244 individuals with pregnancies resulting in live births or stillbirths during the study period were evaluated. A total of 429,843 such conceptions were included in the study: 417,753 (97.2%) occurring before the onset of the pandemic and 12,090 (2.8%) in the pandemic period. In June 2020, conceptions resulting in births decreased by 26.6% compared with June 2019. Trends in conceptions resulting in live births were similar, with a conception rate of 235.2 per 100,000 women of reproductive age in June 2020, compared with the expected rate of 305.0 per 100,000. In March 2020, 0.5% of conceptions that resulted in births ended in stillbirths, compared to 1.7% in March 2019. IVF conceptions ending in births declined during the pandemic, dropping to 2.5 and 2.8 per 100,000 in March and April 2020, respectively, compared with the expected 13.1 per 100,000. However, by June 2020, these rates began to recover toward the expected levels. Rates of gestational diabetes mellites (GDM), gestational hypertension (GHTN), and postpartum intensive care unit (ICU) admissions were similar before and during the COVID-19 pandemic. Conclusions During the challenging period of the COVID-19 pandemic in BC, couples may have chosen to delay conception. Rates of conceptions resulting in stillbirths remained relatively unchanged. IVF conception rates were impacted by the suspension of elective procedures. Preterm birth rates slightly exceeded expected levels but remained within normal fluctuations, and small increases in GDM and GHTN prevalence were also observed.

Enantio- and Diastereoselective Reductive Propargylic Sulfinamidation Enabled by Synergistic Bimetallic Catalysis

Author Correction: Activated α2-macroglobulin binding to cell surface GRP78 induces trophoblastic cell fusion

Radioactive contamination and climate warming affect physiological performance of Chornobyl barn swallows

Global warming and degradation of natural habitats are the two main factors causing ecophysiological stress on individuals and risk for biodiversity. Hyperthermia is a common response to stress in homeothermic animals, in particular to heat, pathogens and environmental contamination. Resilience of biological systems to global warming may be deteriorated in polluted habitats. Here we investigated how body temperature of a wild bird, the barn swallow (Hirundo rustica), responded to global warming while simultaneously exposed to radioactive contamination from the Chernobyl accident. Our results showed that both high air temperatures (t = 15.55, df = 335, p &lt; 0.0001) and elevated environmental radioactive contamination (t = 5.18, df = 8.09, p = 0.0008) increased internal body temperature of individuals. The additive effect suggests that birds might suffer hyperthermia in locally contaminated habitat (1.47% body temperature increase) while simultaneously exposed to globally rising temperatures (1.95% body temperature increase), potentially reducing the fitness of individual and the maintenance of breeding colonies. The cumulative and interactive negative effects of multiple stressors, such as those emerging from increasing habitat degradation and climate change, will likely contribute to biodiversity losses globally.