Browse Articles

Tumor necrosis associates with aggressive breast cancer features, increased hypoxia signaling and reduced patient survival

Abstract In the growing tumor, hypoxia may lead to tumor necrosis which is associated with more aggressive tumor features and reduced patient survival. However, there are shortcomings in our understanding of biological features and clinical significance linked to tumor necrosis. We therefore analyzed transcriptome mRNA expression profiles from primary breast tumors from TCGA and METABRIC (n = 2289) including TCGA mutational data (n = 409). We employed bioinformatics analysis and independent literature-based signatures for validation to identify alterations unique to necrosis. Necrosis was associated with aggressive tumor features and strongly predicted the basal-like breast cancer phenotype. Increased tumor cell proliferation, hypoxia, stemness, and epithelial-to-mesenchymal transition (EMT) were observed in tumors with necrosis. From gene expression data, we constructed a novel Breast Cancer Necrosis Signature (BCNS) score that was a strong predictor of the basal-like phenotype but also conveyed information relevant to the luminal subtypes of breast cancer, including prognosis. Mutational profiling pointed to enrichment of TP53 and PIK3CA mutations in tumors with and without necrosis, respectively. This study confirms the association of breast cancer necrosis with aggressive tumor features and reduced survival, and points to the BCNS score as a potential biomarker that should be further explored and validated to improve breast cancer diagnosis and management.

A noninvasive machine learning model using a complete blood count for screening of primary vitreoretinal lymphoma

Experimental study of a cryogenic pneumatic thrower for launching soft projectiles in avalanche protection

Abstract A novel cryogenic pneumatic launcher for remote avalanche initiation has been developed and experimentally investigated. The system uses liquid nitrogen as a working medium, with its explosive evaporation triggered by the heat of a thermite reaction. The rapid phase transition of the cryofluid generates high pressure without sharp shock waves and enables smooth acceleration of soft-bodied projectiles without structural damage. This approach eliminates key drawbacks of conventional avalanche control methods, such as artillery and gas-dynamic Avalauncher systems. A laboratory-scale prototype was built (a 4-meter-long steel barrel with an outer diameter of 89 mm ) equipped with an optical chronograph to measure projectile velocity (~ 1 kg ). The internal ballistics were studied for thermite charges of 3–6 g and liquid nitrogen volumes of 0–200 ml . It was found that with 3 g of thermite, the optimal performance was achieved by adding ~ 100 ml of liquid N₂ , resulting in a projectile speed of ~ 55 m/s , maintained up to barrel exit. Increasing the charge to 6 g of thermite and 200 ml of liquid N₂ raised the peak velocity to over 90 m/s and extended the acceleration phase. The results confirm the feasibility and advantages of the proposed. Method projectiles accelerate without damage, and the system ensures high mobility, environmental safety (no fragments), and a controlled pressure profile with sufficient delivery range. The combination of gentle acceleration and operational mobility makes the launcher promising for avalanche control and other applications.

Associations of sleep duration and sleep quality with lifestyle inflammation score in a nationwide Korean survey

Orbital angular momentum- and frequency-dependent high-capacity encrypted hologram through multi-dimensional multiplexing acoustic metasurface

Reinforcing the physical properties of PVA/PVP with ferrous chloride for optoelectronic and antibacterial applications

Abstract The present study investigated the composition, physical characteristics, and antibacterial efficacy of Polyvinyl alcohol/Polyvinylpyrrolidone (PVA/PVP) composite films containing different percentages (0–12%) of ferrous chloride (FeCl₂) by the solution casting method. XRD and FT-IR measurements indicate a significant increase in amorphous and substantial interactions between the polymer and filler with the addition of FeCl 2 . The composites exhibited enhanced thermal stability as evidenced by TGA, with the residual weight at 800 °C increasing from 0.21% for the pure sample to 6.28% for the sample containing 12 wt% FeCl 2 . The optical analysis reveals a significant decrease in the direct band gap, diminishing from 5.09 eV for the pure sample to 2.76 eV at 12% FeCl 2 , hence improving its applicability in optoelectronic applications. The films exhibit paramagnetic characteristics, with a saturation magnetization (Ms) of 0.055 emu/g at a 12 wt% FeCl 2 concentration. Hopping conduction and dielectric analyses reveal a marked improvement in both the dielectric constant and AC conductivity, attaining their highest values at a FeCl₂ concentration of 10 wt%. The barrier height decreases as the temperature and FeCl₂ content increase. Impedance spectroscopy exhibited an angled spike at low frequencies and a semicircular arc at high frequencies, indicating non-Debye relaxation behavior consistent with equivalent circuit models. Furthermore, the composites showed potent antimicrobial efficacy against both Gram-negative bacteria (Klebsiella pneumoniae and Escherichia coli) and Gram-positive strains (Staphylococcus aureus and Bacillus subtilis), suggesting their potential for multifunctional optoelectronic and antimicrobial applications.

Eco-friendly inhibitors for sustainable corrosion protection of mild steel under oilfield acidizing conditions

Abstract This study investigates the effect of temperature (30–60 °C) on the corrosion behavior of mild steel in 15% hydrochloric acid, in the absence and presence of four novel, eco-friendly corrosion inhibitors derived from ethanolic extracts of agro-industrial and botanical wastes. Electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, adsorption isotherm, and activation parameter determination were employed, alongside surface morphology analysis using scanning electron microscopy (SEM). All extracts acted as mixed-type inhibitors, achieving high efficiency at low concentrations (0.010–0.600 g/L), with inhibition rates decreasing slightly from 85.8 to 78.4% at 30 °C to 81.9–61.8% at 60 °C. SEM confirmed the formation of a protective surface film, while adsorption followed Langmuir, Flory–Huggins, and Temkin isotherms. Thermodynamic analysis indicated a spontaneous process involving both physisorption and chemisorption. These findings highlight the thermal stability, strong adsorption capability, and practical potential of the studied plant-based extracts as sustainable, non-toxic alternatives to conventional inhibitors for use in harsh oilfield acidizing and descaling operations.

Achieving high-efficiency and stable refrigeration performance through composition modulation inducing non-twinned martensite

Breast density classification using frequency-based features in microwave imaging

Abstract Breast cancer remains one of the leading causes of death among women worldwide. One major challenge in early and accurate detection is breast density. High breast density not only obscures tumors on current imaging modalities, making them harder to identify, but also significantly increases the likelihood of diagnostic errors, both by medical professionals and automated detection systems. As a result, accurately classifying the breast density is crucial, and can lead to better, more tailored screening approaches and reduce the chances of error. This is especially critical for younger women, who are usually excluded from national screenings due to concerns such as radiation exposure. Microwave imaging offers a promising solution to this problem. Unlike traditional imaging methods, it uses safe, non-ionizing radiation, making it suitable for women of all ages. Beyond its safety, microwave imaging has the potential not only to detect breast cancer, but also to classify breasts into high or low density. This dual capability allows for more personalized and accurate cancer detection based on breast density, improving outcomes and reducing diagnostic uncertainty. Our microwave imaging prototype called MammoWave works by scanning the breast using a wide range of low-power electromagnetic signals captured from multiple positions around the breast. This approach provides a rich set of data that helps create an internal map of breast tissue without exposing patients to harmful radiation. This technique makes it possible to extract frequency-based characteristics from both the spatial and spectral domains, taking advantage of not just the signal’s magnitude but also its phase information. These rich features can offer deeper insights into tissue composition and improve the accuracy of breast density classification. Our analysis shows that by fusing features from both the magnitude and phase of the signals—and focusing on approximately the first 40 components of the fast Fourier transform (FFT)—it’s possible to achieve an accuracy of around 70% in classifying breast density using a support vector machine (SVM) with a radial basis function (RBF) kernel. Furthermore, instead of using the full frequency range (1 to 9 GHz), selecting specific sub-bands (1, 3, 4, 5, and 6 GHz) can improve the accuracy to approximately 73%. Importantly, the results also reveal that when breast density is correctly identified and taken into account, the performance of machine learning models in detecting breast cancer improves significantly boosting specificity and sensitivity by around 10% and 5%, respectively for low-density breasts, and by 15% and 10% respectively for high-density breasts.

Multi-GeV electron beam generation via two-stage laser wakefield acceleration

Nonlinear chiral light generation from resonant metasurfaces

Gate engineering Fabry-Pérot resonance in altermagnetic junctions

Abstract Electrically generating and controlling spin-polarized transport is a central objective in spintronics. Altermagnets, which exhibit compensated magnetic order and symmetry-protected spin splitting, offer a promising route toward this goal without requiring net magnetization, magnetic fields, or spin-orbit coupling. Here, we investigate coherent spin transport in a two-dimensional d -wave altermagnetic junction connected to normal metal leads. The anisotropic exchange field induces spin-dependent effective masses, resulting in distinct Fabry-Pérot resonance conditions for spin-up and spin-down electrons. When the junction length matches half-integer multiples of the spin-dependent wavelength, one spin channel is resonantly transmitted while the other is suppressed, yielding fully spin-polarized transport. Employing the quantum scattering formalism, we show that the spin polarization of the transmitted current can be controlled by tuning (i) the gate potential in the altermagnet, (ii) the interfacial barrier strength, and (iii) the orientation of the altermagnetic field. These control parameters enable electrically tunable spin filtering and provide a diagnostic to distinguish between distinct d -wave altermagnetic symmetries. In particular, we show that the $$d_{x^2 - y^2}$$ -wave altermagnet supports robust gate-controlled spin-polarized current even in the high-barrier tunneling regime, a behavior absent in its $$d_{xy}$$ -wave counterpart. Our results establish a field-free, gate-controlled mechanism for spintronic functionality rooted in the crystalline anisotropy of altermagnetic materials.

Hybrid modeling and rapid prototyping technology based on the geomagic system

CRISPR vs cholesterol: can gene editing prevent heart disease?

Epigenetic age acceleration, telomere length, and neurocognitive function in long-term survivors of childhood cancer

Abstract Survivors of childhood cancer are prone to neurocognitive impairment and premature aging, raising concerns about early onset dementia. In this cross-sectional study, 1413 survivors of childhood cancer complete a neuropsychological battery. Mean leukocyte telomere length residual (mLTL) and epigenetic age acceleration (EAA) from five different epigenetic clocks, are derived from linear regression of mLTL or epigenetic age on chronological age. Among survivors treated with CNS-directed therapy, higher EAA, measured by PCGrimAge, or DunedinPACE is associated with worse performance on multiple measures of attention, processing speed, and executive functions (p’s < 0.05). Among non-CNS-treated survivors, results are similar for PCGrimAge, however, DunedinPACE is specifically associated with attention variability (p < 0.05). mLTL is not associated with neurocognition. EAA is associated with worse neurocognitive function and may identify survivors at risk for accelerated cognitive aging or serve as an efficacy biomarker for neurocognitive interventions.

Genetic diversity and geographic distribution of Fasciola species from cattle in eight provinces of South Africa

Overestimates of social media addiction are common but costly

Loss of vegetation functions during the Paleocene–Eocene Thermal Maximum

Abstract The Paleocene–Eocene Thermal Maximum (PETM) around 56 million years ago was a 5–6°C global warming event that lasted for approximately 200 kyr. A warming-induced loss and a 70–100 kyr lagged recovery of biospheric carbon stocks was suggested to have contributed to the long duration of the climate perturbation. Here, we use a trait-based, eco-evolutionary vegetation model to test whether the PETM warming exceeded the adaptation capacity of vegetation systems, impacting the efficiency of terrestrial organic carbon sequestration and silicate weathering. Combined model simulations and vegetation reconstructions using PETM palynofloras suggest that warming-induced migration and evolutionary adaptation of vegetation were insufficient to prevent a widespread loss of productivity. We conclude that global warming of the magnitude as during the PETM could exceed the response capacity of vegetation systems and cause a long-lasting decline in the efficiency of vegetation-mediated climate regulation mechanisms.

Social network, perceived satisfaction with neighborhoods and depressive symptoms among older adults in Korea

Abstract The coronavirus disease 2019 (COVID-19) pandemic has significantly affected social networks and perceived satisfaction with neighborhoods, potentially affecting the mental health of older adults. This study investigated the changes in these factors and their association with depressive symptoms among Korean older adults before and during the COVID-19 pandemic. The prevalence of depressive symptoms slightly increased during the pandemic (4.7–4.9%). Social networks weakened, whereas perceived neighborhood satisfaction improved. Notably, the protective effect of social networks against depressive symptoms became stronger during the pandemic, particularly among low-income individuals and those living in rural areas. Maintaining social networks is essential for promoting mental health resilience among older adults, especially during crises. Policymakers should thus prioritize interventions that strengthen community cohesion, provide governmental support, and facilitate social networking opportunities for vulnerable populations.

Optimization of Aspergillus Niger fermentation for enzyme production and enzymatic hydrolysis of wheat bran for total ferulic acid via RSM