Search Results (2,368)

Due to the allergenicity of soy protein, this study aimed to develop a hypoallergenic, dysphagia-friendly matrix using pea protein isolate. We investigated the effects of three hydrocolloid thickeners—xanthan gum (XG), guar gum (G), and carrageenan (C)—at various concentrations on the matrices’ rheological properties, textural characteristics, and dysphagia diet classification. The unthickened pea protein base was unstable, exhibiting rapid phase separation and low viscosity, unsuitable for dysphagia diets. The addition of XG (0.4–0.6 g), G (0.5–1.0 g), and C (0.8–1.2 g) successfully produced food matrices meeting the slightly, mildly, and moderately thick levels of the Japanese Society of Dysphagia Rehabilitation (JSDR) framework. However, discrepancies were noted between instrumental viscosity and syringe flow test classifications. Rheological analysis revealed that XG samples were in elastic (G′ > G″) domain in the linear viscoelastic region (LVR) and exhibited shear-thinning behavior. In contrast, G and C samples were in viscous (G″ > G′) domain. Frequency sweeps characterize XG samples as weak gels, G samples as dilute polymer solutions, and C samples as gel-like structures. Texture profile analysis further showed that xanthan gum imparted the highest firmness and thickness, whereas guar gum provided the best flowability. Full article

This study reports the effect of pH (2, 7, 10) and heat treatment (80 °C for 30 min) on the oil–water (o/w) interfacial behavior of hemp seed protein isolate (HPI) aqueous dispersions. The physicochemical, interfacial adsorption, rheology, and emulsifying properties of protein dispersions were evaluated. HPI dispersions at pH 10 exhibited the highest water solubility (60%), the greatest net charge (−27 mV), and the lowest hydrophobicity (~5 a.u.), promoting o/w interfacial pressure (π) and interfacial viscoelasticity. Strong interfacial viscoelastic protein layers (E^* = 25 mN/m) were also observed under acidic conditions (pH 2), where proteins exhibited high solubility (40%), a high positive net charge (21 mV), and increased hydrophobicity (46 a.u.). HPI dispersions in their neutral state (pH 7) were not able to form stable o/w emulsions due to their poor physicochemical properties such as low solubility (18%), low surface charge (−18 mV), and hydrophobicity (~5 a.u.). Heat treatment significantly increased the charge and hydrophobicity of both neutral and alkaline proteins (~30 mV and ~10 a.u., respectively), increasing their particle size distribution and ultimately reducing their interfacial protein layer elasticity (E^* = 20 and 13 nM/m, respectively). While particles at acidic conditions showed high thermal resistance, heat treatment improved the emulsifying stability in alkaline conditions while further reducing it in the neutral state. Overall, HPI dispersions demonstrated the ability to form stable emulsions at both alkaline and acid pHs, with those formed at pH 2 exhibiting a lower droplet size and superior stability. Full article

Standard epidemiological models often treat human behavior as static, failing to capture the dynamic feedback loops that shape epidemic waves. To address this, we developed a compartmental model of COVID-19 that couples the disease dynamics with two co-evolving behavioral games governed by imitation dynamics: an altruistic self-isolation game for infected individuals and a self-interested vaccination game for susceptible individuals. Our simulations reveal a fundamental behavioral paradox: strong adherence to self-isolation, while effective at reducing peak infections, diminishes the perceived risk of disease, thereby undermining the incentive to vaccinate. This dynamic highlights a critical trade-off between managing acute crises through non-pharmaceutical interventions and achieving long-term population immunity. We conclude that vaccination has a powerful stabilizing effect that can prevent the recurrent waves often driven by behavioral responses to non-pharmaceutical interventions. Public health policy must therefore navigate the tension between encouraging short-term mitigation behaviors and communicating the long-term benefits of vaccination to ensure lasting population resilience. Full article

Anxiety, depression, and social impairment exhibit high clinical comorbidity, yet their underlying shared neural circuitry remains poorly defined. Using a mouse model of chronic social isolation combined with circuit tracing and chemogenetic tools, we identified a key role for the basolateral amygdala (BLA) in relaying prefrontal cortex (PFC) signals to the bed nucleus of the stria terminalis (BNST) to drive behavioral changes. Further circuit dissection identified two distinct BNST microcircuits segregated by their input sources: one receives indirect PFC input relayed through the BLA (PFC → BLA → BNST), while the other is innervated by direct PFC projections (PFC → BNST). Chemogenetic inhibition of BLA neurons in the indirect pathway ameliorated anxiety-like behavior, depression-like behavior, and social deficits. Within the BNST, however, inhibition of neurons in PFC → BLA → BNST pathway selectively alleviated affective phenotypes without altering social behavior. In contrast, inhibition of neurons in PFC → BNST pathway specifically restored social recognition while leaving emotional behaviors intact. Thus, the BLA integrates PFC-derived signals to broadly modulate behavior, while downstream BNST microcircuits dissociate these influences. The indirect, BLA-relayed pathway within the BNST specifically drives affective symptoms, whereas the direct PFC → BNST pathway selectively governs social recognition. This dissociable circuit model offers a new framework for understanding clinical comorbidity and may inform targeted interventions for distinct symptom dimensions. Full article

Background: The belief that “sugar feeds cancer” is widespread and has strongly influenced public perceptions, patient behavior, and dietary recommendations, despite uncertainty regarding its scientific validity. This belief largely stems from misinterpretation of the Warburg effect, which describes altered glucose metabolism in cancer cells rather than dietary sugar dependence. The objective of this review was to critically evaluate whether dietary sugar intake directly contributes to cancer development or progression by examining the totality of epidemiological, experimental, and mechanistic evidence. Methods: We conducted a narrative review of human epidemiological studies, experimental animal and cell-based models, and mechanistic investigations published between 1980 and July 2025. Evidence was synthesized across cancer types, sugar sources, and biological pathways, with careful consideration of study design, exposure relevance, and key confounders, including obesity, insulin resistance, and overall dietary patterns. Results: Across cancer types, epidemiological evidence showed predominantly null or inconsistent associations between sugar intake and cancer risk or outcomes, with positive findings largely confined to metabolically susceptible subgroups and often attenuated after adjustment for adiposity and energy intake. Experimental studies suggested potential tumor-promoting effects under non-physiological conditions, while mechanistic data indicated that sugar influences cancer risk indirectly through insulin signaling, inflammation, and metabolic dysfunction rather than direct tumor fueling. Conclusions: Current evidence does not support the hypothesis that dietary sugar directly “feeds” cancer in humans. Overemphasis on sugar avoidance risks nutritional and psychological harm, particularly among cancer patients. Evidence-based guidance should prioritize overall dietary quality, metabolic health, and patient well-being rather than isolated sugar restriction. Full article

We use 29 years of altimeter-derived sea level anomalies and geostrophic velocities (1993–2021) from the Copernicus Marine Service to identify the Mexican Coastal Current (MCC) and to examine how it interacts with the coastline. Variance-ellipse and empirical orthogonal function analyses isolate a narrow alongshore jet with a mean width of about 95 km and average speeds near 0.3 m ${\mathrm{s}}^{-1}$ that reverses direction semiannually: poleward in June and July and equatorward in the rest of the year. When the MCC impinges on broad concavities in the coast, the boundary layer separates, forming recirculation cells that intensify and detach as coherent eddies. These near-shore eddies have similar radii (from ∼30 km) and relative vorticity of $\pm 0.5\times {10}^{-5}$${\mathrm{s}}^{-1}$ at the beginning of their generation, and they propagate offshore once the current weakens. A simple numerical model reproduces the observed behavior and suggests that eddy formation is controlled by flow separation rather than generic instability. The semiannual change in direction of the MCC indicate a link with the larger-scale North Equatorial Countercurrent and Costa Rica Coastal Current systems of the eastern tropical Pacific. Full article

In the context of global climate change and carbon-neutrality goals, carbon taxes and carbon tariffs have become key policy tools for regulating corporate emissions. However, most existing studies examine these policies in isolation and overlook firms’ behavioral responses under their joint implementation, especially with product heterogeneity. This study analyzes production and emission-reduction decisions of two-country manufacturers under carbon taxation and further investigates corporate behavior and social welfare outcomes when both carbon taxes and carbon tariffs are imposed. The results show that carbon taxes enhance emission-reduction efforts, though with diminishing marginal effects. Moderate carbon tariffs further motivate exporting firms to reduce emissions, while overly high tariffs may induce market exit, particularly for high-quality manufacturers. Consumer preferences also interact with policy effects: stronger preferences for high-quality products encourage firms to expand domestic markets and increase green investments, whereas weaker preferences shift focus toward exports. Social welfare responds asymmetrically, moderate tariffs improve environmental performance, while excessive tariffs lead to trade distortions and welfare losses. Overall, this study highlights nonlinear and heterogeneous firm responses under combined carbon policies, offering insights for policy design and corporate strategy. Full article

Data exfiltration poses a major cybersecurity challenge because it involves the unauthorized transfer of sensitive information. Intrusion Detection Systems (IDSs) are vital security controls in identifying such attacks; however, their effectiveness in cloud computing environments remains limited, particularly against covert channels such as Internet Control Message Protocol (ICMP) and Domain Name System (DNS) tunneling. This study compares two widely used IDSs, Snort and Suricata, in a controlled cloud computing environment. The assessment focuses on their ability to detect data exfiltration techniques implemented via ICMP and DNS tunneling, using DNSCat2 and Iodine. We evaluate detection performance using standard classification metrics, including Recall, Precision, Accuracy, and F1-Score. Our experiments were conducted on Amazon Web Services (AWS) Elastic Compute Cloud (EC2) instances, where IDS instances monitored simulated exfiltration traffic generated by DNSCat2, Iodine, and Metasploit. Network traffic was mirrored via AWS Virtual Private Cloud (VPC) Traffic Mirroring, with the ELK Stack integrated for centralized logging and visual analysis. The findings indicate that Suricata outperformed Snort in detecting DNS-based exfiltration, underscoring the advantages of multi-threaded architectures for managing high-volume cloud traffic. For DNS tunneling, Suricata achieved 100% detection (recall) for both DNSCat2 and Iodine, whereas Snort achieved 85.7% and 66.7%, respectively. Neither IDS detected ICMP tunneling using Metasploit, with both recording 0% recall. It is worth noting that both IDSs failed to detect ICMP tunneling under default configurations, highlighting the limitations of signature-based detection in isolation. These results emphasize the need to combine signature-based and behavior-based analytics, supported by centralized logging frameworks, to strengthen cloud-based intrusion detection and enhance forensic visibility. Full article

Background: Oxytocin (OT) is a nonapeptide hormone produced in the hypothalamus, released into the brain and peripheral circulation, and plays a key role in social behavior. Recent studies indicate that complement component C4a is an OT-binding protein, which modulates plasma OT concentrations in mice. However, the role of C4a is unclear as to whether it contributes to consolation behavior. Methods: Social behavior, especially allogrooming, which is a form of empathy that depends on detecting the emotional states of others, was measured in wild-type or C4a/Slp knockout (Slp^−/−) male mice. Results: Observer mice of both genotypes exhibited comforting (allogrooming) behavior toward a cage-mate demonstrator during reunion after brief isolation of the demonstrator mice. When demonstrator mice experienced body restraint stress during isolation, the allogrooming behavior was significantly increased in both genotypes, with a markedly greater increase in Slp^−/− than in Slp^+/+ mice. Allogrooming behavior in observer Slp^−/− mice was significantly suppressed by an OT receptor antagonist. Furthermore, immunohistochemical analysis revealed that activation was significantly elevated in OT-positive hypothalamic neurons in observer Slp^−/− mice that interacted with stressed demonstrator mice. OT release from the isolated hypothalamus, stimulated via CD38 and TRPM2 channel activation, was greater in Slp^−/− mice than in Slp^+/+ mice. Conclusions: Our results highlight that the data are consistent with a potential role for C4a in modulating neural circuits, possibly via its peripheral action on OT bioavailability. Direct evidence for C4a’s action within the brain remains a hypothesis for future investigation, for example, via site-specific manipulations. Full article

Tetranuclear rhodium carbonyl clusters are vital catalytic precursors; yet derivatives featuring bidentate phosphines are less common, due to the propensity for cluster fragmentation during synthesis. This study reports the successful isolation of five new heteroleptic species by reacting Rh₄(CO)₁₂ with various bidentate diphosphines under homogeneous conditions and at room temperature, namely the mono-substituted Rh₄(CO)₁₀(dppe) (1) and Rh₄(CO)₁₀(dppb) (3), the rare bis-substituted derivative Rh₄(CO)₈(dppe)₂ (2), and the two unique dimeric assemblies {Rh₄(CO)₁₀(dpp-hexane)}₂ (4) and {Rh₄(CO)₁₀(trans-dppe)}₂ (5). The tetrahedral Rh₄ core of the cluster precursor was preserved in all cases. The new compounds were characterized via infrared (IR) spectroscopy and single-crystal X-ray diffraction (SC-XRD). Furthermore, variable-temperature (VT) ³¹P{¹H} NMR spectroscopy elucidated the dynamic behavior of the phosphorus atoms. This work reports a robust methodology for accessing stable, low-nuclearity rhodium phosphine clusters with tunable properties. Full article

Traffic flow anomalies represent significant deviations from normal traffic behavior and disrupt the smooth operation of transportation systems. These may appear as unusually high or low traffic volumes compared to historical trends. Unexpectedly high volume can lead to congestion exceeding usual capacity, while unusually low volume might indicate incidents like road closures, or malfunctioning traffic signals. Identifying and understanding both types of anomalies is crucial for effective traffic management. This paper presents a clustering based approach for enhanced characterization of anamolies in traffic flows. Anomalies in traffic patterns are determined using three anomaly detection techniques: Elliptic Envelope, Isolation Forest, and Local Outlier Factor. These anomalies were newly detected in this work on the Montréal dataset after preprocessing, rather than directly reused from earlier studies. These methods were applied to a dataset that had been pre-processed using windowing techniques with different configuration settings to enhance the detection process. Then, to leverage the detected anomalies, we utilized clustering algorithms, specifically k-means and hierarchical clustering, to segment these anomalies. Each clustering algorithm was used to determine the optimal number of clusters. Subsequently, we characterized these clusters through detailed visualization and mapped them according to their unique characteristics. This approach not only identifies traffic anomalies effectively but also provides a comprehensive understanding of their spatial and temporal distributions, which is crucial for traffic management and urban planning. Full article

Phishing websites continue to evolve in sophistication, making them increasingly difficult to distinguish from legitimate platforms and challenging the effectiveness of current detection systems. In this study, we investigate the role of subtle deceptive behavioral cues such as mouse-over effects, pop-up triggers, right-click restrictions, and hidden iframes in enhancing phishing detection beyond traditional structural and domain-based indicators. We propose a hierarchical hybrid detection framework that integrates dimensionality reduction through Principal Component Analysis (PCA), phishing campaign profiling using K Means clustering, and a stacked ensemble classifier for final prediction. Using a public phishing dataset, we evaluate multiple feature configurations to quantify the added value of behavioral indicators. The results demonstrate that behavioral indicators, while weak predictors in isolation, significantly improve performance when combined with conventional features, achieving a macro F1 score of 97 percent. Explainable AI analysis using SHAP confirms the contribution of specific behavioral characteristics to model decisions and reveals interpretable patterns in attacker manipulation strategies. This study shows that behavioral interactions leave measurable forensic signatures and provides evidence that combining structural, domain, and behavioral features offers a more comprehensive and reliable approach to phishing intrusion detection. Full article

Background/Objectives: This study aimed to determine the antimicrobial susceptibility patterns of multidrug resistant (MDR) and extensively resistant (XDR) Salmonella enterica serovar Typhi (S. Typhi) strains among children, along with the associated behavioral and environmental risk factors across different population groups in multiple districts of Punjab, Pakistan. Methods: A cross-sectional study was conducted across 20 districts in Punjab, Pakistan. Structured questionnaires were used to assess sociodemographic and behavioral determinants. Blood cultures from febrile children were obtained for the isolation and identification of S. Typhi, followed by antimicrobial susceptibility testing and screening for the resistance genes. Results: A total of 900 blood samples were collected and 41.5% were positive for S. Typhi. The proportion of culture-positive cases were higher among children aged 6–12 years (34.8%). Sociodemographic and behavioral analysis revealed that children from low-income households (PKR < 20,000 showed significantly higher infection rate (67.1%, p < 0.001). Antimicrobial susceptibility testing revealed high resistance rates against several antibiotics: Ciprofloxacin (88.8%), Trimethoprim/sulfamethoxazole (83.7%), Ampicillin (73.8%) and Chloramphenicol (72.7%). However, all isolates remained susceptible to carbapenems and azithromycin. The prevalence of MDR and XDR S. Typhi in urban areas was 28.1% and 60.8%, respectively, while rural areas showed 22.6% MDR and 20.6% XDR. In contrast, nomadic populations exhibited a higher rate of MDR (49.3%) but a lower XDR prevalence of 18.6% with significant geographic variations in resistance patterns. Molecular analysis revealed a high prevalence of resistance genes, including sul1 (83.7%), sul2 (79.7%), followed by dfrA7 (81.3%), catA1 (64.9%) and bla_TEM (60.5%), bla_CTX-M-1 (12.5%), bla_CTX-M-15 (25.9%) and qnrS (88.8%), respectively. Conclusions: The study underscores a persistent typhoid burden and widespread antimicrobial resistance among children in Punjab. Targeted vaccination, antibiotic stewardship, public health education are urgently needed, especially among the nomadic population, where healthcare access and hygiene awareness are limited. Full article

In whey valorization, membrane separation stands out as a highly effective technique for purifying and isolating the various components of whey. The efficiency of whey ultrafiltration and diafiltration (UF/DF) largely depends on the balance between membrane selectivity, hydrodynamic conditions, and solute interactions at the membrane interface. In this study, sweet whey was fractioned using 10, 30 and 50 kDa polyether sulfone (PES) membranes under identical transmembrane pressure (TMP = 2.5 bar) with ultrafiltration and a subsequent 4-step constant volume diafiltration stages. The resulting compositional and dielectric changes were evaluated to identify optimal separation conditions and assess the applicability of dielectric parameter measurement as a rapid, non-destructive monitoring technique. Results showed that, regardless of the applied molecular weight cut-off (MWCO), using three DF cycles can wash out almost all the removable lactose from the retentates, and the dielectric assessment of both permeate and retentate fractions showed a strong, linear relationship between the change in dielectric behavior and the composition of each fraction. Analysis of the dielectric spectra confirmed that the ratio of the dielectric constant to the loss factor (ε′/ε″) exhibited a strong linear correlation (R² > 0.98, r > 0.99) with lactose concentration in the permeate fractions of all three MWCO membranes, as well as a similarly strong correlation (R² > 0.975, r > 0.98) with the total chemical oxygen demand (TCOD) measured in the retentate fractions. Full article

Background: Humulus lupulus (Hops) possesses a diverse array of bioactive compounds with reported antioxidant, anti-inflammatory, antibacterial, and neuroprotective properties. However, most studies have focused on isolated components, whose purification is costly and yields limited quantities. Objective: In this study, we aimed to evaluate whether a complete Hops extract could exert antioxidant and neuroprotective effects. Methods: First, the ability of Hops extract’s free radical scavenging capacity against superoxide, hydroxyl radical, and peroxynitrite was discovered using combinatorial chemical assays. Moreover, the used Hops extract prevented both DNA and protein degradation induced by hydroxyl radicals. Next, rats were orally administered with three different doses of Hops extract (10, 15, and 20 mg/kg/day) for 7 consecutive days. Results: Ex vivo analyses of brain tissues revealed that Hops pre-treatment attenuated FeSO₄-induced lipid peroxidation, increased the GSH/GSSG ratio and downregulated both glutathione peroxidase and reductase activities. Additionally, the expression of the nuclear factor erythroid 2-related factor (Nrf2) gene was significantly elevated in the striatum of Hops-treated animals. To further explore neuroprotection, we evaluated the effect of Hops (15 mg/kg/day) in an in vivo model of excitotoxicity induced by quinolinic acid (QUIN). Pre-treatment with the Hops extract reduced QUIN-induced circling behavior, increased the translocation of NRF2 to the nucleus and decreased apoptosis in the striatum. Conclusion: These findings suggest that the whole Hops extract enhances redox resilience in the brain and confers protection against oxidative and excitotoxic insults. Full article