Search Results (16,826)

Background. Axillary lymph node biopsy (ALND) has traditionally been considered the gold standard for axillary staging and treatment in clinically node-positive breast cancer patients. However, in patients with nodal disease, the therapeutic benefit of ALND is uncertain. This study, based on a large cohort, aims to evaluate breast cancer-specific survival depending on the extent of axillary surgery in non-metastatic breast cancer using real-world data from the Surveillance, Epidemiology, and End Results (SEER) database. Methods. This retrospective cohort study comprised 825,240 patients diagnosed with breast cancer between 2000 and 2020. Results. ALND was associated with a worse survival outcome in pN0 and pN1 populations (respectively, hazard ratio [HR] 1.16; 95% confidence interval [CI] 1.12–1.2; p < 0.001 and HR 1.38; 95%CI 1.3–1.46; p < 0.001). In pN2 and pN3 populations, there was ~4.3% relative reduction in the hazard of breast cancer-related death for each additional node removed; and higher positive-to-removed lymph node ratio was associated with worse prognosis (HR 3.450; 95%CI 2.99–3.98; p < 0.001). Conclusions. SLNB is associated with significantly better specific survival compared to ALND in negative/low axillary involvement, in higher axillary involvement categories extensive axillary surgery was associated with better prognosis. Full article

Political polarization in Western democracies has accelerated in the last decade, with negative social consequences. Research across disciplines on antecedents, manifestations and societal impacts is hindered by social systems’ complexity: their constant flux impedes tracing causes of observed trends and prediction of consequences, hampering their mitigation. Social physics models exploit a characteristic of complex systems: what seems chaotic at one observation level may exhibit patterns at a higher level. Therefore, dynamic modeling of complex systems allows anticipation of possible events. We use this approach to anticipate 2024 US election results. We consider the highly polarized Democrats and Republicans, and Independents fluctuating between them. We generate average group-stance scenarios in time and explore how polarization and depolarization might have affected 2024 voting outcomes. We find that reducing polarization might advantage the larger voting group. We also explore ways to reduce polarization, and their potential effects on election results. The results inform regarding the perils of polarization trends, and on possibilities of changing course. Full article

In the context of the global climate transition, managerial climate attention is influencing the risk posture of new energy vehicle firms as a key non-economic cognitive factor. This paper investigates the mechanism of managerial climate attention (MCA) on the systemic risk of firms using panel data from 111 listed NEV firms in China from 2013 to 2022. The results show that first, the systemic risk of NEV firms is significantly reduced as managerial climate attention increases. Second, the negative influence of MCA on the systemic risk of NEV firms is more significant among state-owned enterprises, firms in non-first-tier cities and in the machinery, equipment and computer communication sub-sectors. Third, MCA negatively affects the systemic risk of NEV firms by increasing market competition, environmental performance and investor sentiment. The difference-in-differences analysis based on the Paris Agreement shows that the systemic risk of the treatment group enterprises increased significantly after policy implementation, confirming the link between climate-related policies and risk. The management of NEV firms should be concerned about climate change, thus providing practical implications for financial stability and sustainable economic development. Full article

Emerging arboviruses of the Orthoflavivirus genus such as West Nile virus (WNV) and Usutu virus (USUV), primarily transmitted by Culex mosquitoes, pose significant public health threats due to their ability to cause severe neurological diseases in humans and animals. While studies in North America and Central Europe have shown that these viruses can persist in overwintering mosquitoes, their role in viral maintenance during the cold season in northeastern France remains unknown. This study aimed to assess whether overwintering female mosquitoes in this region could harbor WNV or USUV during the cold season, potentially maintaining viral circulation until the following transmission season. Between October 2021 and February 2024, a total of 10,617 overwintering female mosquitoes were collected in various types of habitats across five departments in northeastern France. The most common species was Culex pipiens (88%). Mosquitoes were grouped into 1121 pools (1–10 individuals each) and tested by real-time RT-PCR for WNV, USUV, and other flaviviruses using a pan-Flavivirus NS5-targeting assay. All pools tested negative, indicating no evidence of viral RNA in overwintering females. These results suggested that overwintering female mosquitoes in northeastern France do not act as reservoirs for WNV or USUV, and do not contribute to their overwintering maintenance. Full article

Hemp (Cannabis sativa L.) is a high-yielding crop cultivated for fiber and seed production, generating substantial lignocellulosic residues such as hurds. These byproducts can be valorized through pyro-gasification, a thermochemical process that offers a sustainable alternative to combustion and produces biochar—a promising soil amendment due to its ability to enhance soil quality and mitigate drought stress. This research explores the viability of utilizing industrial hemp hurds as a direct feedstock for biochar production within the context of agricultural exploitation. The study specifically focuses on assessing the feasibility of converting raw, unprocessed hemp hurds into biochar through pyrolysis. A comprehensive characterization of the resulting biochar is conducted to evaluate its properties and potential applications in agriculture, establishing a foundational understanding for future agronomic use. Specific analysis included proximate and ultimate analysis, thermogravimetric analysis (TGA), SEM-EDS, and phytotoxicity testing. The biochar exhibited an alkaline pH (≥9), a low H/C ratio (0.37), and suitable macro- and micronutrient levels. Microstructural analysis revealed a porous architecture favorable for nutrient retention and water absorption. Germination tests with corn (Zea mays L.) showed a germination index above 90% for substrates containing 0.5–1% biochar. These findings establish a foundation for future research aimed at thoroughly exploring the agricultural potential of this material. Full article

Background/Objectives: Neisseria meningitidis is a human-specific pathogen capable of causing life-threatening illnesses. Occasionally, it is recovered from unusual sites, other than the bloodstream or the central nervous system. Herein, we describe two rare manifestations due to N. meningitidis within a year (2024) in Greece. Methods: Atypical infection due to N. meningitidis was diagnosed in two different patients: Case-1 presented with an inflammatory swelling in the mid-line of the neck, and Case-2 presented with swelling of the left knee. Both patients had high fever and no neurological signs at admission; Case-2 progressed to meningoencephalitis. Phenotypic and genotypic identifications were carried out in both cases. Results: Case-1 and Case-2 isolates were identified as follows: MenX: 18, 25-44, F5-5, ST-823; 198cc and MenB: 7-1, 1, F3-3, ST-7460; 32cc for PorA, FetA and MLST, respectively. MenX was identified for the first time in Greece and finetyping revealed rare genotypic characteristics. Both isolates were susceptible to cefotaxime, ceftriaxone and rifampicin, while Case-2 isolate expressed reduced susceptibility to penicillin and resistance to ciprofloxacin. Both patients recovered fully. Conclusions: Although uncommon, N. meningitidis may be isolated from atypical sites and specimens. Clinicians and microbiologists should remain aware that meningococcus is a potential cause of infections beyond meningitis and septicaemia. Full article

Background/Objectives: The concurrent circulation of SARS-CoV-2 with influenza A and B viruses and respiratory syncytial virus (RSV) represents a new diagnostic challenge in the post-COVID-19 area, especially considering that these infections have overlapping clinical presentations but different approaches to treatment and management. Multiplexed molecular testing on point-of-care platforms that focus on the simultaneous detection of multiple respiratory viruses in a single tube constitutes a useful approach for diagnosis of respiratory infections in decentralized clinical settings. This study evaluated the analytical performances of the VitaSIRO solo™ SARS-CoV-2/Flu/RSV Assay performed on the VitaSIRO solo™ Instrument (Credo Diagnostics Biomedical Pte. Ltd., Singapore, Republic of Singapore). Methods: With a view to accreditation, the criteria of the 2022-revised EN ISO 15189:2022 norma were applied for the retrospective on-site verification of method using anonymized respiratory specimens collected during the last 2024–2025 autumn–winter season in France. Results: Usability and satisfaction were comparable to current reference point-of-care platforms, such as the Cepheid GeneXpert^® Xpress System (Cepheid Diagnostics, Sunnyvale, CA, USA). Repeatability and reproducibility (2.34–4.49% and 2.78–5.71%, respectively) demonstrated a high level of precision. The platform exhibited a low invalid rate (2.9%), with most resolving on retesting. Analytical performance on 301 clinical samples showed high overall sensitivities: 94.8% for SARS-CoV-2 (Ct ≤ 33), 95.8% for influenza A and B viruses, 95.2% for RSV, and 95.4% for all viruses. Specificities were consistently high (99.2–100.0%). False negatives (2.6%) were predominantly associated with high Ct values. Agreement with the comparator reference NeuMoDx™ Flu A-B/RSV/SARS-CoV-2 Vantage Assay (Qiagen GmbH, Hilden, Germany) was almost perfect (Cohen’s κ 0.939–0.974), and a total of 91.1%, 94.8%, and 100.0% of Ct values were within the 95% limits of agreement for the detection of SARS-CoV-2, influenza A and B viruses, and RSV, respectively, by Bland–Altman analyses. Passing–Bablok regression analyses demonstrated good Ct values correlation between VitaSIRO solo™ and NeuMoDx™ assays, with a slight, non-significant, positive bias for the VitaSIRO solo™ assay (mean absolute bias +0.509 to +0.898). Conclusions: These findings support VitaSIRO solo™ Instrument as a user-friendly and reliable point-of-care platform for the rapid detection and differentiation of SARS-CoV-2, influenza A and B viruses, and RSV responding to the EN ISO 15189:2022 criteria for accreditation to be implemented in hospital or decentralized settings. Full article

Drying is ubiquitous. However, its influence on surface speciation has been seldom studied. Through an in situ Attenuated Total Reflection–Infrared (ATR-IR) spectroscopy analysis of the drying of molybdate solutions on a lepidocrocite particle film, the change in surface speciation is followed. No formation polymolybdates nor precipitate are observed upon drying at pH 8. An in situ washing of the dried solid/solution interface unveils the existence of surface outer-sphere and inner-sphere complexes. Decreasing the molybdate concentration highlights a saturation effect of the surface upon drying. Moreover, the careful analysis of substrate IR bands showed non-uniform drying which is an important insight to understand dehydration chemistry. The remaining molybdate ions at the surface as inner-sphere complexes are present as binuclear monodentate complexes stabilized by sodium. Full article

Nicotinamide adenine-dinucleotide (NAD⁺) supplementation is a promising strategy to delay cellular aging in different areas, including cosmetic dermatology. However, low bioavailability and stability of NAD⁺ formulations are the main factors limiting its effectiveness as an anti-aging treatment. In light of the above, a liposomal formulation of NAD⁺ (LF-NAD⁺) was tested in this study and compared to NAD⁺ alone in primary human aortic endothelial cells (HAECs) and primary human epidermal keratinocytes (HEKas). Intracellular NAD⁺ was measured using a colorimetric assay. Cell survival was derived from lactate dehydrogenase release in supernatants. Cell senescence was measured by senescence-associated β-galactosidase staining. Molecular mechanisms underlying the reported effects were analyzed by Western blot. Skin penetration of NAD⁺ was measured ex vivo in skin explants, using infrared spectroscopy. Compared to control NAD⁺ alone, the LF-NAD⁺ formulation increased the intracellular NAD⁺ content and cell survival in HAECs, but not in HEKas. Instead, a significant reduction in the number of senescent cells was observed in both HAECs and HEKas. LF-NAD⁺ treatment was associated with a reduced expression of p16 in both HAECs and HEKas, and to a significant reduction in p21 in HEKas alone. Finally, LF-NAD⁺ increases the skin penetration of the active substance NAD⁺ by 30% compared to the application of NAD⁺ alone. LF-NAD⁺, enhances the anti-aging effects of NAD⁺ on vascular and skin cells. Such in vitro findings might indicate a potential anti-aging role in the microcirculation and in the epidermidis. Full article

In recent decades, technological developments in archaeological geophysics have led to growing data volumes, so that an important bottleneck is now at the stage of data interpretation. The manual delineation and classification of anomalies are time-consuming, and different methods for (semi-)automatic image segmentation have been proposed, based on explicitly formulated rulesets or deep convolutional neural networks (DCNNs). So far, these have not been used widely in archaeological geophysics because of the complexity of the segmentation task (due to the low contrast between archaeological structures and background and the low predictability of the targets). Techniques based on shallow machine learning (e.g., random forests, RFs) have been explored very little in archaeological geophysics, although they are less case-specific than most rule-based methods, do not require large training sets as is the case for DCNNs, and can easily handle 3D data. In this paper, we show their potential for geophysical data analysis. For the classification on the pixel level, we use ilastik, an open-source segmentation tool developed in medical imaging. Algorithms for object classification, manual reclassification, post-processing, vectorisation, and georeferencing were brought together in a Jupyter Notebook, available on GitHub (version 7.3.2). To assess the accuracy of the RF classification applied to geophysical datasets, we compare it with manual interpretation. A quantitative evaluation using the mean intersection over union metric results in scores of ~60%, which only slightly increases after the manual correction of the RF classification results. Remarkably, a similar score results from the comparison between independent manual interpretations. This observation illustrates that quantitative metrics are not a panacea for evaluating machine-generated geophysical data interpretation in archaeology, which is characterised by a significant degree of uncertainty. It also raises the question of how the semantic segmentation of geophysical data (whether carried out manually or with the aid of machine learning) can best be evaluated. Full article

Human population growth and increasing transportation demands have led to rising global tire consumption and associated waste. In response, various material and energy recovery strategies, such as pyrolysis, have been developed to produce high-value-added products such as pyrolysis oils, which can be reused as materials or fuels. However, these oils often contain heteroatom-containing compounds (e.g., nitrogen, oxygen, sulfur) that can hinder their valorization and must therefore be identified and removed. To characterize heteroatomic compounds present in distillation fractions of pyrolysis oils, GC×GC/TOFMS and GC/HRMS were employed. For non-target analysis, data processing parameters were optimized using a Central Composite Design (CCD). The most influential parameters for GC×GC/TOFMS were the minimum number of mass-to-charge ratio (m/z) signals kept in the deconvoluted spectra (minimum stick count) and peak signal-to-noise ratio (S/N), while for GC/HRMS, optimization focused on the m/z S/N threshold, peak S/N, and total ion current (TIC). Under optimal conditions, 129 and 92 heteroatomic compounds were identified via GC×GC/TOFMS and GC/HRMS, respectively, within a single distillation fraction, with 57 compounds identified using both techniques. Notably, GC×GC/TOFMS exclusively identified 72 compounds, while there were only 5 unique to GC/HRMS. These results highlight the effectiveness of GC×GC/TOFMS in characterizing heteroatomic compounds in complex mixtures, while also underlining the complementary value of GC/HRMS. Full article

Background: Hypertension remains the leading global risk factor for cardiovascular morbidity and mortality, with suboptimal control rates despite guideline-directed therapies. Digital health and artificial intelligence (AI) technologies offer novel approaches for improving diagnosis, monitoring, and individualized treatment of hypertension. Objectives: To critically review the current landscape of AI-enabled digital tools for hypertension management, including emerging applications, implementation challenges, and future directions. Methods: A narrative review of recent PubMed-indexed studies (2019–2024) was conducted, focusing on clinical applications of AI and digital health technologies in hypertension. Emphasis was placed on real-world deployment, algorithmic explainability, digital biomarkers, and ethical/regulatory frameworks. Priority was given to high-quality randomized trials, systematic reviews, and expert consensus statements. Results: AI-supported platforms—including remote blood pressure monitoring, machine learning titration algorithms, and digital twins—have demonstrated early promise in improving hypertension control. Explainable AI (XAI) is critical for clinician trust and integration into decision-making. Equity-focused design and regulatory oversight are essential to prevent exacerbation of health disparities. Emerging implementation strategies, such as federated learning and co-design frameworks, may enhance scalability and generalizability across diverse care settings. Conclusions: AI-guided titration and digital twin approaches appear most promising for reducing therapeutic inertia, whereas cuffless blood pressure monitoring remains the least mature. Future work should prioritize pragmatic trials with equity and cost-effectiveness endpoints, supported by safeguards against bias, accountability gaps, and privacy risks. Full article

Background/Objectives: Increased dehydroepiandrosterone sulfate (DHEAS) is used as a diagnostic marker of hyperandrogenism in women with polycystic ovary syndrome (PCOS). The mechanisms of adrenal hyperandrogenism in PCOS include hyperinsulinism as a potential stimulator, but results of studies associating insulinemia with DHEAS in PCOS are conflicting. The objective of this study was to evaluate the factors associated with DHEAS levels in PCOS, focusing on insulinemia. Methods: We performed a cross-sectional retrospective study in a total of 257 patients with PCOS (Rotterdam criteria) evaluated in our tertiary center of endocrinology. Clinical and biochemical parameters included body mass index (BMI), serum DHEAS, total testosterone and sex hormone-binding globulin (SHBG), insulin and glycaemia at fasting and 2 h during the oral glucose tolerance test (OGTT), and homeostasis model assessment for insulin resistance (HOMA-IR) was calculated. Results: The comparative analysis of PCOS divided into DHEAS tertiles revealed that patients in the upper tertile were younger (p < 0.05) and had higher 2 h insulin in the OGTT (p < 0.05) than the lower tertile, while fasting insulin and HOMA-IR were not different. DHEAS correlated negatively with age (r = −0.146, p < 0.05) and positively with 2 h insulinemia (r = 0.246, p < 0.001), while fasting insulin and HOMA-IR did not correlate with DHEAS in all PCOS. In stepwise linear regression models, 2 h insulin remained a positive independent predictor for DHEAS only in non-obese PCOS (p < 0.0001). Conclusions: Our data indicate a positive association between stimulated insulin and DHEAS in PCOS. Two-hour insulin in OGTT was an independent predictor of DHEAS in non-obese PCOS, suggesting that DHEAS might be a reliable marker for the stimulatory insulin effect on adrenal steroidogenesis in non-obese PCOS patients. Full article

This study investigates how energy consumption and foreign direct investment (FDI) influenced economic growth in BRICS+ countries from 1990 to 2021, using a two-step System GMM estimator to address endogeneity and dynamic effects. While the results show that both energy and FDI positively affected growth, disaggregated analysis revealed that renewable energy promoted growth, whereas non-renewables hindered it. Similarly, FDI directed toward gross fixed capital formation (FDI_GFCF) consistently boosted growth, unlike aggregate FDI. Financial development moderated these effects, amplifying the benefits of energy use but dampening FDI’s growth impact in more developed financial systems. The effects of energy and FDI remained stable before and after the Paris Agreement, supporting the robustness of the findings. These results underscore the importance of tailored energy and FDI strategies, financial sector reforms, and supportive policy environments to advance sustainable growth in BRICS+ economies. Full article