Search Results (1,024)

Background: In forensic ballistics, identifying ammunition types on physical evidence is critical, particularly when metallic residues are minimal. This study comparatively analyzes the elemental signatures deposited by two common projectiles—Full Metal Jacket (FMJ) (Cu/Zn jacket) and Lead Round Nose (LRN) (exposed Pb core)—on complex targets, including pig bone/tissue and mango wood. Methods: Using a semi-automatic handgun at an intermediate range of 5.0 m, residues were examined through high-resolution benchtop Micro-XRF (M4 Tornado) for micro-spatial analysis and Portable XRF (Elio) for rapid field characterization. Additionally, fresh pork leg samples were subjected to a 3-month environmental degradation period to assess trace persistence. Results: Observations indicated that LRN projectiles exhibit markedly elevated Lead (Pb) concentrations along the wound track in bone, hence confirming Pb as a reliable indicator for unjacketed ammunition; specifically, the median Pb concentrations at bullet wiping were 10.39 wt% for M4 and 7.34 wt% for Elio. Conversely, FMJ traces remain strictly confined to the surface bullet wipe area, with median concentrations of Pb, Cu, and Zn being 2.21 wt%, 0.24 wt%, and 0.59 wt% via M4, respectively. Statistical analysis showed a strong correlation for high-concentration elements on tissue, but significantly greater variance on wooden surfaces where FMJ traces exhibited a very weak negative correlation (r = −0.2774) due to minimal and irregular metal transfer. Taphonomic evaluation revealed that the Pb signature from LRN is exceptionally stable (r ≈ 0.9999) even after decomposition, while FMJ signatures are highly sensitive to environmental exposure. Conclusions: This research underscores the necessity of high-sensitivity Micro-XRF (M4) for definitive ammunition verification, providing a refined analytical framework for shooting incident reconstruction even involving degraded remains or complex environmental scenes. Full article

Trace elements are widely involved in fundamental physiological processes, including enzymatic reactions, neurotransmitter metabolism, and redox homeostasis, and their balanced regulation plays an important role in maintaining normal brain development and neurological function. Depression is a complex psychiatric disorder characterized primarily by mood disturbances, with its onset and progression arising from long-term interactions among genetic susceptibility, neurobiological alterations, and environmental factors. A substantial body of epidemiological and clinical evidence indicates that dysregulation of trace elements—such as zinc, selenium, iron, and magnesium—is closely associated with the risk of depression and the severity of depressive symptoms. Mechanistic studies further demonstrate that trace elements influence depression-related pathophysiology through multi-target and multi-pathway mechanisms, including modulation of monoaminergic neurotransmission, neuroinflammation, oxidative stress, mitochondrial energy metabolism, and hypothalamic–pituitary–adrenal axis function. Network pharmacology analyses have additionally identified systemic hub targets, such as albumin (ALB), insulin (INS), and TP53, as well as key pathways including calcium signaling, neuroactive ligand–receptor interactions, and the HIF-1 signaling pathway. These findings suggest that trace elements may regulate depression-related pathological processes through coordinated network-level effects. Collectively, these integrative insights provide a theoretical basis for the application of trace elements in depression risk assessment, the development of precision intervention strategies, and future mechanistic investigations. Full article

Network operators increasingly rely on abstracted telemetry (e.g., flow records and time-aggregated statistics) to achieve scalable monitoring of high-speed networks, but this abstraction fundamentally constrains the forensic and security inferences that can be supported from network data. We present a design-time audit framework that evaluates which threat hypotheses become non-supportable as network evidence is transformed from packet-level traces to flow records and time-aggregated statistics. Our methodology examines three evidence layers (L0: packet headers, L1: IP Flow Information Export (IPFIX) flow records, L2: time-aggregated flows), computes a catalog of 13 network-forensic artifacts (e.g., destination fan-out, inter-arrival time burstiness, SYN-dominant connection patterns) at each layer, and maps artifact availability to tactic support using literature-grounded associations with MITRE Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK). Applied to backbone traffic from the MAWI Day-In-The-Life (DITL) archive, the audit reveals selectiveinference loss: Execution becomes non-supportable at L1 (due to loss of packet-level timing artifacts), while Lateral Movement and Persistence become non-supportable at L2 (due to loss of entity-linked structural artifacts). Inference coverage decreases from 9 to 7 out of 9 evaluated ATT&CK tactics, while coverage of defensive countermeasures (MITRE D3FEND) increases at L1 (7 → 8 technique categories) then decreases at L2 (8 → 7), reflecting a shift from behavioral monitoring to flow-based controls. The framework provides network architects with a practical tool for configuring telemetry systems (e.g., IPFIX exporters, P4 pipelines) to reason about and provision the minimum forensic coverage. Full article

Cancer remains a leading cause of morbidity and mortality worldwide, and effective strategies for cancer prevention are urgently needed to complement therapeutic advances. While dietary factors are known to influence cancer risk, the molecular mechanisms that mediate inter-individual responses to nutritional exposures remain poorly defined. Emerging evidence identifies long non-coding RNAs (lncRNAs) as pivotal regulators of gene expression, chromatin organization, metabolic homeostasis, immune signaling, and cellular stress responses, the core processes that drive cancer initiation and progression and are highly sensitive to nutritional status. In parallel, advances in precision nutrition have highlighted how variability in genetics, metabolism, microbiome composition, and epigenetic landscapes shape dietary influences on cancer susceptibility. This review integrates these rapidly evolving fields by positioning lncRNAs as molecular conduits that translate dietary exposures into transcriptional and epigenetic programs governing cancer development, progression, and therapeutic vulnerability. We provide mechanistic evidence demonstrating how dietary bioactive compounds and micronutrients, including polyphenols [such as curcumin, resveratrol, epigallocatechin gallate (EGCG)], flavonoids, alkaloids such as berberine, omega-3 (ω-3) fatty acids, folate, vitamin D, probiotic metabolites (such as butyrate and propionate), and trace elements (such as selenium and zinc), modulate oncogenic and tumor-suppressive lncRNAs. These nutrient–lncRNA interactions influence cancer-relevant pathways controlling proliferation, epithelial–mesenchymal transition (EMT), inflammation, oxidative stress, and metabolic rewiring. We further discuss emerging lncRNA signatures that reflect nutritional and metabolic states, their potential utility as biomarkers for individualized dietary interventions, and their integration into liquid biopsy platforms. Leveraging multi-omics datasets and systems biology, we outline AI-driven frameworks to map nutrient–lncRNA regulatory networks and identify targetable nodes for cancer chemoprevention. Finally, we address translational challenges, including compound bioavailability, inter-individual variability, and limited clinical validation, and propose future directions for incorporating lncRNA profiling into precision nutrition-guided cancer prevention trials. Together, these insights position lncRNAs at the nexus of diet and cancer biology and establish a foundation for mechanistically informed precision nutrition strategies in cancer chemoprevention. Full article

Recent discoveries of fluorite–barite deposits in the Donghai–Linshu area in northern Jiangsu Province, China, underscore the region’s mineral potential, yet detailed geological investigations remain limited. In this study, we examined monzonite and quartz monzonite from drill cores in the Jiashan mining area using petrography, U–Pb zircon dating, zircon trace element geochemistry, whole-rock geochemistry, and zircon Lu–Hf isotopes. Laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS) zircon U–Pb analyses were conducted to constrain the crystallization ages of the monzonite (127.06 ± 0.54 Ma and 126.83 ± 0.75 Ma) and quartz monzonite (127.2 ± 0.5 Ma and 128.59 ± 0.62 Ma) to the Early Cretaceous, marking a significant magmatic event. Many of the zircons contain inherited Neoproterozoic cores (718–760 Ma and 800–860 Ma), indicating the assimilation of deep crustal materials of this age. The monzonite is metaluminous, with moderate SiO₂ (61.61–62.41 wt.%), high alkalis (Na₂O + K₂O = 7.48–7.92 wt.%), and A/CNK = 0.72–0.91. The quartz monzonite has higher SiO₂ (66.26–68.18 wt.%) and alkalis (8.32–9.33 wt.%). Both rock types exhibit similar trace and rare earth element patterns: enrichment in large-ion lithophile and light rare earth elements, depletions in Nb, Ta, and Ti, no significant Zr-Hf depletion, and weak negative Eu anomalies (δEu ≈ 0.84–1.00). Their low Zr + Nb + Ce + Y contents, Ga/Al ratios, and TFeO/MgO ratios indicate that they have an I-type granite affinity. The Early Cretaceous zircons have highly negative ε_Hf(t) values (−33.7 to −23.5) and ancient two-stage model ages (2622–3247 Ma), which are consistent with derivation from Archean crust. The inherited Neoproterozoic zircons have younger Paleo–Mesoproterozoic T_DM2 ages. The evidence suggests that both intrusions were mainly generated by partial melting of ancient Archean basement, with minor mantle input. The magma generation was likely triggered by crustal anatexis induced by the underplating of mantle-derived magmas in an extensional tectonic regime, coeval with Early Cretaceous magmatism in the Sulu orogen. Full article

Modern healthcare systems increasingly depend on wearable Internet of Medical Things (IoMT) devices for the continuous monitoring of patients’ physiological parameters. It remains challenging to differentiate between genuine physiological anomalies, sensor faults, and malicious cyber interference. In this work, we propose a hybrid fusion framework designed to attribute the most plausible source of an anomaly, thereby supporting more reliable clinical decisions. The proposed framework is developed and evaluated using two complementary datasets: CICIoMT2024 for modelling security threats and a large-scale intensive care cohort from MIMIC-IV for analysing key vital signs and bedside interventions. The core of the system combines a supervised XGBoost classifier for attack detection with an unsupervised LSTM autoencoder for identifying physiological and technical deviations. To improve clinical realism and avoid artefacts introduced by quantised or placeholder measurements, the physiological module incorporates quality-aware preprocessing and missingness indicators. The fusion decision policy is calibrated under prudent, safety-oriented constraints to limit false escalation. Rather than relying on fixed fusion weights, we train a lightweight fusion classifier that combines complementary evidence from the security and clinical modules, and we select class-specific probability thresholds on a dedicated calibration split. The security module achieves high cross-validated performance, while the clinical model captures abnormal physiological patterns at scale, including deviations consistent with both acute deterioration and data-quality faults. Explainability is provided through SHAP analysis for the security module and reconstruction-error attribution for physiological anomalies. The integrated fusion framework achieves a final accuracy of 99.76% under prudent calibration and a Matthews Correlation Coefficient (MCC) of 0.995, with an average end-to-end inference latency of 84.69 ms (p95 upper bound of 107.30 ms), supporting near real-time execution in edge-oriented settings. While performance is strong, clinical severity labels are operationalised through rule-based proxies, and cross-domain fusion relies on harmonised alignment assumptions. These aspects should be further evaluated using realistic fault traces and prospective IoMT data. Despite these limitations, the proposed framework offers a practical and explainable approach for IoMT-based patient monitoring. Full article

Diet plays a central role in shaping the composition and metabolic activity of the oral microbiota, thereby influencing both oral and systemic health. Disturbances in this delicate host–microbe balance, triggered by dietary factors, smoking, poor oral hygiene, or antibiotic use, can lead to microbial dysbiosis and increase the risk of oral diseases such as periodontitis, as well as chronic systemic disorders including diabetes, cardiovascular disease, Alzheimer’s disease, and certain cancers. Among dietary contaminants, exposure to toxic heavy metals such as cadmium (Cd), lead (Pb), mercury (Hg), nickel (Ni), and arsenic (As) represents an underrecognized modifier of the oral microbial ecosystem. Even at low concentrations, these elements can disrupt microbial diversity, promote inflammation, and impair metabolic homeostasis. Saliva has recently emerged as a promising, non-invasive biofluid for monitoring nutritional status and early metabolic alterations induced by diet and environmental exposures. Salivary biomarkers, including metabolites, trace elements, and microbial signatures, offer potential for assessing the combined effects of diet, microbiota, and toxicant exposure. This review synthesizes current evidence on how diet influences the oral microbiota and modulates susceptibility to heavy metal toxicity. It also examines the potential of salivary biomarkers as integrative indicators of nutritional status and metabolic health, highlights methodological challenges limiting their validation, and outlines future research directions for developing saliva-based tools in personalized nutrition and precision health. Full article

Background/Objectives: Lithium (Li), silicon (Si), and boron (B) are proposed nutritional trace elements with potential roles in metabolic, neurobiological, endocrine, inflammatory, and bone-related processes. This review provides a critical synthesis of data on Li–Si–B, emphasizing (i) physiological and mechanistic pathways, (ii) human clinical relevance, (iii) shared biological domains, and (iv) safety considerations. Methods: A narrative review was conducted across PubMed, Scopus, and Web of Science from inception to January 2025. Predefined search strings targeted dietary, environmental, and supplemental exposures of lithium, silicon, or boron in relation to metabolism, endocrine function, neurobiology, inflammation, bone health, and the gut microbiome. Inclusion criteria required peer-reviewed studies in English. Data extraction followed a structured template, and evidence was stratified into human, animal, cellular, and ecological tiers. Methodological limitations were critically appraised. Results: Li, Si, and B influence overlapping molecular pathways including oxidative stress modulation, mitochondrial stability, inflammatory signaling, endocrine regulation, and epithelial/gut barrier function. Human evidence remains limited: Li is supported primarily by small trials; Si by bone-related observational studies and biomarker-oriented interventions; and B by metabolic, inflammatory, and cognitive studies of modest sample size. Convergence across elements appears in redox control, barrier function, and neuroimmune interactions, but mechanistic synergism remains hypothetical. Conclusions: Although Li–Si–B display compelling mechanistic potential, current human data are insufficient to justify dietary recommendations or supplementation. Considerable research gaps—including exposure assessment, dose–response characterization, toxicity thresholds, and controlled human trials—must be addressed before translation into public health policy. Full article

The Sındırgı earthquake sequence, with moment magnitudes of 6.1 on 10 August and 27 October 2025, respectively, occurred within the Simav Fault Zone in western Türkiye, rupturing nearby but structurally distinct fault segments. In this study, we combine Sentinel-1 InSAR time-series measurements with seismological data, geomorphic observations, and post-event field surveys to examine how deformation evolved between and after these events. InSAR results indicate coseismic line-of-sight displacements of 6–7 cm, followed by post-seismic deformation that persisted for months at 8–10 mm/yr. This behavior signifies that deformation continued well beyond the initial rupture. The estimated displacement does not align with a single fault plane. Instead, it corresponds to a network of early-mapped and previously unrecognized fault segments. Seismicity patterns and stress tensor inversions show that activity migrated spatially after 10 August and that the faulting mechanism altered before the second earthquake. When synthesized, observations indicate stress transfer within a modular, segmented fault system, thought to have been influenced by regional structural complexity. Field investigations after the October earthquake reported new surface cracks and fault traces, providing evidence of shallow deformation. The collected results indicate that post-seismic stress redistribution played a leading role in modulating the 2025 Sındırgı earthquake sequence. Full article

This study aimed to evaluate the impact of sterilization of low-adhesive films with ethylene oxide (EO) or accelerated electrons (radiation sterilization) on their performance in the context of their use to protect forensic traces. It was hypothesized that the implementation of the sterilization process made it possible to obtain functional tools for securing traces. The analysis showed that changes in surface density, density, tensile strength, and adhesion strength do not significantly affect the functional performance of the tapes. Additionally, no alterations in chemical resistance were observed following either sterilization method. The results confirm that both sterilization techniques are suitable for obtaining sterile tapes for forensic applications. Full article

Background/Objectives: This systematic review examines how artificial intelligence (AI) is transforming fingerprint and latent print identification in criminal investigations, tracing the evolution from traditional dactyloscopy to Automated Fingerprint Identification Systems (AFISs) and AI-enhanced biometric pipelines. Methods: Following PRISMA 2020 guidelines, we conducted a literature search in the Scopus, Web of Science, PubMed/MEDLINE, and legal databases for the period 2000–2025, using multi-step Boolean search strings targeting AI-based fingerprint identification; 68,195 records were identified, of which 61 peer-reviewed studies met predefined inclusion criteria and were included in the qualitative synthesis (no meta-analysis). Results: Across the included studies, AI-enhanced AFIS solutions frequently demonstrated improvements in speed and scalability and, in several controlled benchmarks, improved matching performance on low-quality or partial fingerprints, although the results varied depending on datasets, evaluation protocols, and operational contexts. They also showed a potential to reduce certain forms of examiner-related contextual bias, while remaining susceptible to dataset- and model-induced biases. Conclusions: The evidence indicates that hybrid human–AI workflows—where expert examiners retain decision making authority but use AI for candidate filtering, image enhancement, and data structuring—currently offer the most reliable model, and emerging developments such as multimodal biometric fusion, edge computing, and quantum machine learning may contribute to making AI-based fingerprint identification an increasingly important component of law enforcement practice, provided that robust regulation, continuous validation, and transparent governance are ensured. Full article

Construction on soft, highly compressible soils increasingly requires reliable ground improvement solutions. Among these, Rigid Inclusions (RIs) have emerged as one of the most efficient soil-reinforcement techniques. This paper synthesizes evidence from over 180 studies to provide a comprehensive state-of-the-art review of RI technology encompassing its governing mechanisms, design methodologies, and field performance. While the static behavior of RI systems has now been extensively studied and is supported by international design guidelines, the response under cyclic and seismic loading, particularly in liquefiable soils, remains less documented and subject to significant uncertainty. This review critically analyzes the degradation of key load-transfer mechanisms including soil arching, membrane tension, and interface shear transfer under repeated loading conditions. It further emphasizes the distinct role of RIs in liquefiable soils, where mitigation relies primarily on reinforcement and confinement rather than on drainage-driven mechanisms typical of granular columns. The evolution of design practice is traced from analytical formulations validated under static conditions toward advanced numerical and physical modeling frameworks suitable for dynamic loading. The lack of validated seismic design guidelines is high-lighted, and critical knowledge gaps are identified, underscoring the need for advanced numerical simulations and large-scale physical testing to support the future development of performance-based seismic design (PBSD) approaches for RI-improved ground. Full article

This study investigates the hydrography and geochemical signature in Ilha Grande Bay (RJ, Brazil), focusing on the seasonal intrusion of South Atlantic Central Water (SACW) and its interaction with lead sources. CTD (Conductivity, Temperature, and Depth) data revealed the presence of SACW during the summer campaigns (Mangaratiba/2011 and Frade/2012), characterized by temperatures below 20 °C and salinity between 34.6 and 36. The intrusion is driven by northeasterly winds that favor coastal upwelling, establishing a classic thermohaline stratification. The winter campaigns did not detect SACW, confirming its seasonal nature. Isotopic analysis of Pb in sediments identified six Pb²⁰⁶/Pb²⁰⁷ intervals, indicating multiple sources, including natural contributions, industrial waste, and urban effluents. The Pb²⁰⁶/Pb²⁰⁷ ranges were defined based on cluster analysis and frequency histograms, which are common methods in isotopic provenance studies. An overlap between the most radiogenic isotopic signatures and the presence of SACW suggests that this water mass acts as a vector for transporting trace elements from the deep oceanic region to the coast. This study provides the first evidence that the South Atlantic Central Water (SACW) acts as a seasonal vector, importing a distinct radiogenic Pb isotopic signature onto the continental shelf of Ilha Grande Bay. By synoptically coupling physical water-mass analysis (CTD) with Pb isotopic tracers, we introduce a novel approach that successfully discriminates oceanic from anthropogenic Pb sources, offering a new framework for understanding contaminant transport in coastal areas influenced by boundary currents. It is concluded that the coastal dynamics in Ilha Grande Bay are governed by the seasonal interaction of coastal, continental, and oceanic waters, and that the integration of physical and geochemical data is crucial for understanding mixing processes and contaminant transport in this complex environment. Full article

The metal-binding periplasmic protein CusF has been proposed as a bifunctional tag that enhances the solubility of recombinant proteins and enables purification using Cu affinity chromatography. However, evidence for its performance remains limited to a few model proteins. Here, we evaluated CusF as a solubility tag for two heterologous proteins: a putative poly(A)-polymerase from Enterococcus faecalis (Efa PAP) and the red fluorescent protein mCherry. The proteins were fused to CusF, expressed in E. coli BL21 (DE3) pLysS and Rosetta 2 (DE3) strains, and assessed for solubility and IMAC binding. Native Efa PAP was completely insoluble under all tested conditions, and fusion to CusF did not improve its solubility. Similarly, CusF–mCherry accumulated predominantly in the insoluble fraction, with only trace amounts detectable in soluble lysates. Soluble CusF–mCherry did not bind Cu²⁺-charged IMAC resin, while moderate binding to Ni²⁺-charged resin was attributable to the vector-encoded His tag rather than CusF. These results indicate that CusF does not universally enhance protein solubility and may not consistently bind Cu-based IMAC resin. Our findings expand empirical knowledge of solubility tag performance and emphasize the necessity of testing multiple tags to identify optimal strategies for recombinant protein production. Full article

This study investigates 49 gold solidi issued between the 4th and 5th century AD to determine their chemical composition. The coins were first catalogued by recording mass, diameter, and thickness. All specimens underwent non-destructive µ-EDXRF analysis to identify main elements, followed by semi-quantitative fineness evaluation. To validate these results, six coins were randomly micro-sampled: material was dissolved in aqua regia and analysed by ICP-AES for gold quantification and ICP-MS for high precision trace element determination. The non-destructive analyses showed consistently high gold percentages, confirming authenticity and the extensive use of this noble metal during the studied period. Two distinct groups were identified based on the XRF Pt/Pd ratio, suggesting the use of gold from different sources. Comparison of μ-EDXRF and ICP-AES gold contents shows no statistically significant differences; however, this apparent agreement should be interpreted cautiously, as it mainly reflects the limited resolving power of ICP-AES at very high gold concentrations rather than definitive evidence for the absence of surface-related effects. Trace elements analysis detected low concentrations of Cu, Sn, and Pb suggesting the use of alluvial gold for minting. The presence and correlation of terrigenous elements (Al, Ca, Ti, Cr, Mn, Fe, Ni, Zn, Sr) indicate soil as the burial site. Full article