Browse Articles

Green synthesis of gold nanoparticles utilizing Raphanus sativus root extract: characterization and in vitro investigation of its antioxidant, antimicrobial and anticancer impact

Abstract Gold nanoparticles (AuNPs) are recently investigated as substantial tools in cancer therapy due to their biocompatibility and tunable surface properties. Raphanus sativus or red radish root (RRR), a Cruciferaceae vegetable, has notable medicinal and nutritional value owing to its highly polyphenolic content and antioxidant property. The aim of this study is to synthesize the gold nanoparticles by a green method using the Raphanus sativus root extract and to study its antioxidant, antimicrobial and anticancer impact. The resultant RRR-AuNPs were characterized by TEM, UV/Vis spectroscopy, DLS, Zeta potential, XRD, AFM, BET and pore size analysis and assessed for antioxidant, antimicrobial and anticancer activity. The greenly synthesized gold nanoparticles showed ruby red color with a distinct absorption peak at 526 nm. The resultant AuNPs were spherical with an average size of 31 nm and average zeta potential of -36.8 mV. Results clearly demonstrated that the RRR-AuNPs possess high total polyphenolic content and potent antioxidant activity (DPPH). Moreover, RRR-AuNPs exhibited a considerable antibacterial efficacy against Staphylococcus aureus (80.9% inhibition) and Escherichia coli (78.22% inhibition) with a uniform MIC value of 0.977 µg/mL. Furthermore, RRR-AuNPs reduced the viability of Caco-2 and HepG2 cancer cells to 31.9% and 26.4%, respectively, at 250 µg/mL. Notably, a remarkable Antimicrobial Selectivity Index (SI) of 303.04 was established, confirming a toxicity over 300-fold higher toward bacterial pathogens than toward normal HEK-293 cells. These findings highlight RRR-AuNPs as a promising, biocompatible platform with potent antioxidant, antimicrobial, and anticancer properties for biomedical applications.

Experimental sepsis causes SERCA2 expression in white adipose tissue but not classical browning

Abstract Sepsis causes muscle wasting and cachexia but mechanisms remain unclear. Cachexia in cancer and burn injury is partly attributed to ‘browning’; where white adipose tissue (WAT) develops a catabolic, thermogenic brown adipose tissue-like phenotype. We hypothesised that sepsis-induced muscle wasting is caused by browning. 58 male Wistar rats were randomised to sham (n = 17) or experimental sepsis induced by intraperitoneal zymosan (n = 41). Tibialis anterior mass was measured on Days 3 and 14. Browning was sought using whole body and WAT respirometry, RNA-sequencing, immunoblot, thermal imaging and multi-photon microscopy of WAT. Fourteen-day mortality in rats receiving zymosan was 17%. In survivors, body mass loss peaked at day 3 and persisted to day 14 with associated tibialis anterior muscle mass loss. Zymosan peritonitis caused hypermetabolism during the late recovery phase (Days 11–14), but no difference in epididymal white adipose tissue temperature nor oxygen flux. At Day 14 transcriptomics showed inflammation but no increase in uncoupling protein (UCP)-1 at transcript or protein levels. SERCA2 protein was however increased fourfold in retroperitoneal WAT at day 14 ( p  = 0.016). Rats recovering from zymosan peritonitis developed muscle wasting and cachexia associated with WAT inflammation and whole-body hypermetabolism. No evidence of browning was seen at functional, transcriptomic or protein levels, therefore our data do not support the hypothesis of classical browning as a driver of sepsis-induced muscle wasting and cachexia. SERCA2 protein expression was however increased in retroperitoneal WAT at day 14.

Seismic performance of a novel bracing system including cable-ring-arc together with MR damper in a steel frame

Anemia and risk of dementia in the general population: a propensity-score based cohort study

Study on the internal leakage pneumatic noise acoustic characteristics of spring-loaded full-lift safety valve

Piezoresistive and mechanical performance of nano-TiO₂-modified 3D-printed cementitious composites

TSG-6 protects orbital fibroblasts via anti-inflammation and anti-fibrosis effects in thyroid eye disease

A blockchain-enabled IoT framework for smart electro-medical waste management

Comparative evaluation of international and population-specific risk prediction models for type 2 diabetes: evidence from the kharameh cohort of the PERSIAN study

Hypertension and incidence of kidney stones: a prospective study based on the data of the Rafsanjan cohort study

A network analysis of personality traits, mentalizing, and psychological health in Chinese college students

Abstract The rising prevalence of anxiety and depression among college students constitutes a significant public mental health challenge. While personality traits (e.g., neuroticism) and impairments in mentalizing capacity are recognized as key vulnerability factors, their complex interplay in contributing to psychological distress remains inadequately elucidated. Network analysis offers a novel paradigm for visualizing this intricate system as an interconnected web of symptoms and traits. This study employed a network approach to investigate the interrelationships among personality traits, mentalizing, and psychological distress in a large sample of Chinese college students. The primary aims were to identify the most central (influential) elements within the network and, crucially, to detect bridge nodes that connect different psychological domains, thereby pinpointing potential targets for precise intervention. A cross-sectional survey was conducted among 5,140 Chinese undergraduates. Assessments included the Symptom Checklist-90 (SCL-90), Mentalizing Questionnaire (MZQ), Reflective Functioning Questionnaire-8 (RFQ-8), Eysenck Personality Questionnaire (EPQ), and University Personality Inventory (UPI). Regularized partial correlation networks were estimated using the LASSO-EBIC method (γ = 0.5), which inherently controls for multiple comparisons through regularization. Node centrality was indexed by expected influence (EI), and bridge centrality by bridge expected influence (bEI). Non-parametric bootstrap tests with 20,000 resamples were used to evaluate network accuracy and stability. Depressive symptoms (SCL-3) and neuroticism (EPQ-2) showed the highest centrality. Neuroticism (EPQ-2) was the strongest bridge node (bEI = 0.93), with the strongest edge in the network linking to impaired mentalizing (MZQ-1; weight = 0.474). Mean node predictability was 0.51. Network stability was excellent (CS coefficient = 0.75). Mentalizing constructs were represented by MZQ subscales, which also reflect the conceptual content of the RFQ-8: hypermentalizing (MZQ-2) corresponds to RFQ-C (certainty), and hypomentalizing (MZQ-3) corresponds to RFQ-U (uncertainty). Findings highlight robust concurrent associations between neuroticism, mentalizing impairment, and psychological distress in Chinese college students. Neuroticism is strongly associated with distress partly through its link to reduced mentalizing capacity. These cross-sectional results provide a framework for targeted preventive strategies in student populations, although causal inferences cannot be drawn from this observational design.

Serum integrative omics reveals predictive signatures for coronary artery disease

Abstract Identifying serum biomarkers that accurately reflect the progression of coronary artery disease (CAD) remains a major challenge. Integrative proteomic and metabolomic profiling can provide novel insights into disease pathogenesis and improve clinical prediction. We conducted a four-phase study. In the discovery phase, serum from 40 patients (controls, stable CAD, and acute coronary syndrome (ACS)) was analyzed using data-independent acquisition (DIA) proteomics and liquid chromatography-tandem mass spectrometry (LC–MS)/gas chromatography–mass spectrometry (GC–MS) metabolomics to identify differentially expressed proteins (DEPs) and metabolites. In the verification phase, selected DEPs were validated by parallel reaction monitoring (PRM) in an independent 40-patient cohort. In the derivation phase, six validated proteins were measured by ELISA in 207 angina patients to assess their association with coronary obstruction (≥ 50% stenosis). In the validation phase, a support vector machine (SVM) model incorporating clinical risk factors and these biomarkers was developed in the derivation cohort and tested in an independent 97-patient cohort. Model performance was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. Coronary obstruction is defined as ≥ 50% luminal diameter stenosis in at least one major coronary artery on angiography. Proteomic analysis identified 97 DEPs, and metabolomic profiling revealed 322 DEMs (including 289 from LC–MS and 33 from GC–MS analyses). Seven proteins showed consistent changes in both DIA and PRM validation. Among these, thrombospondin-1 (TSP-1) was significantly upregulated in stable CAD compared with controls, while serum amyloid A1 (SAA1) was markedly elevated in ACS compared with stable CAD. In an independent angina cohort ( n  = 207), serum levels of TSP-1 and SAA1 were significantly higher in patients with coronary obstruction. Multivariate logistic regression adjusted for conventional cardiovascular risk factors (including age, sex, homocysteine, and other clinical variables) demonstrated that TSP-1 remained independently associated with coronary artery occlusion (OR = 1.424, 95% CI 1.057–1.918, P  = 0.020). A support vector machine (SVM) model incorporating conventional clinical risk factors was constructed, and the addition of TSP-1 and SAA1 significantly improved diagnostic performance for CAD severity (AUC = 0.919 in derivation, 0.992 in validation). In conclusion, our dual-omics approach identified novel biomarkers and pathways in CAD progression. The SVM-based prediction model offers a promising non-invasive tool for early CAD detection, potentially reducing unnecessary invasive procedures.

Global burden of environmental heat and cold exposure 1990–2021 projected to 2035 reveals temporal trends and socio-demographic inequalities

Gut barrier integrity biomarkers are associated with increased inflammation and predict disease status in hospitalized COVID-19 patients

SELAM: selective ECC-based lightweight authentication for the internet of medical things

Abstract Secure authentication in the Internet of Medical Things (IoMT) must ensure strong security while maintaining minimal computational overhead, especially for resource-constrained medical devices. This study introduces SELAM, a lightweight multifactor authentication framework optimized for critical IoMT applications. Unlike traditional designs, SELAM selectively confines elliptic-curve cryptography (ECC) to user/device registration, while relying on lightweight primitives (XOR, hashing/HMAC, and timestamp-freshness checks) in online operation to minimize runtime cost. The scheme is validated using the CICIoMT-2024 dataset through Python-based cryptographic simulation and ns-3 network emulation. Under standardized 16-byte online field accounting, SELAM reduces payload-only online communication to 6,144 bits/device versus 7,680 bits/device for a Heavy+Verify ECC baseline; in ns-3 header-inclusive accounting, this corresponds to 39,416 versus 45,703 bits/device at $$\:N=136$$ . At 1 Mb/s, SELAM achieves 6.24 ms total per-device authentication overhead (communication + computation) compared to 31.27 ms for Heavy+Verify, while reducing online computation from 23.59 ms to 0.10 ms per device. Across cohort sizes $$\:N=136$$ – $$\:2000$$ over 20 seeds (mean ± 95% CI), SELAM maintains attack-regime authentication success ratio (ASR) at 0.88–0.90 (baseline: 0.90–0.92), with protocol-level FAR=0 (no accepted replay/impersonation) and benign FRR=0 observed in PhaseLogs. Security analysis using BAN logic confirms mutual authentication and key confirmation on a fresh session key in Phases 4–5, with replay/impersonation resistance under the stated Dolev–Yao adversary and standard MAC/AEAD assumptions. The results indicate that confining ECC to registration preserves strong authentication while removing public-key operations from the performance-critical online path.

Quantitative analysis of representation asymmetry in human cadaveric white matter dissection literature

A disambiguation framework for refining and answering ambiguous questions

Using ensemble learning and Gaussian mixture model to predict petrophysical properties and hydraulic flow units in carbonate reservoirs

A calreticulin-linked HPV-16 E7 minigene DNA vaccine elicits strong E7-specific CD8+ T-cell immunity and durable antitumor effects in a preclinical model

Abstract Calreticulin (CRT) is an endoplasmic reticulum chaperone that facilitates antigen processing and presentation, making it an attractive fusion partner for enhancing tumor-specific T-cell responses in DNA vaccine development. However, the relative efficacy of CRT compared with other antigen-presentation–enhancing strategies has not been fully evaluated. We constructed a DNA vaccine encoding the immunodominant human papillomavirus (HPV)-16 E7 minigene epitope (aa 49–57) fused to the C-terminus of CRT (pcDNA3-CRT-E7(49–57), hereafter CRT-E7(49–57)). This vaccine was compared with DNA vaccines encoding CRT linked to full-length E7 (CRT-E7(1–98)) and other antigen-presentation–enhancing constructs, including ubiquitin linked to E7 minigene (Ub-E7(49–57)) and MHC class I trafficking domain linked to E7 minigene (MITD-E7 (49–57)). We evaluated E7-specific cytotoxic T-cell responses, tumor volume, and survival in both prophylactic and therapeutic TC-1 tumor models. Intramuscular electroporation of C57BL/6 mice with CRT-E7(49–57) elicited robust E7-specific CD8⁺ T-cell responses comparable to those induced by CRT-E7(1–98) and MITD-E7(49–57), but higher than those elicited by Ub-E7 (49–57). CRT-E7(49–57) vaccination provided complete protection against TC-1 tumor challenge, with mice remaining tumor-free and surviving beyond 60 days. Vaccinated mice also exhibited strong immune memory, as tumor rechallenge triggered potent E7-specific CD8⁺ T-cell responses and restricted tumor growth. In therapeutic settings, two doses of CRT-E7(49–57) completely suppressed tumor progression, outperforming Ub-E7(49–57) and conferring superior survival compared with MITD-E7(49–57). The CRT-E7(49–57) DNA vaccine induces durable, high-magnitude E7-specific CD8⁺ T-cell responses and confers effective prophylactic and therapeutic antitumor immunity, underscoring its promise as a versatile platform for cancer immunotherapy.

BEACON: BERTopic-augmented context-aware co-attention recommender system