Search Results (8,144)

Defect modes in phononic crystals (PnCs) provide strongly localized resonances that are essential for frequency-dependent wave filtering and highly sensitive sensing. Their functionality increases greatly when their spectral characteristics can be externally tuned without altering the structural configuration. However, existing feedback control strategies rely on laminated piezoelectric defects, which have uniform electromechanical loading that causes voltage cancellation for even-symmetric defect modes. Consequently, only odd-symmetric defect bands can be manipulated effectively, which limits multi-band tunability. To overcome this constraint, we propose a segmented piezoelectric sensor–actuator design that enables symmetry-dependent feedback at the defect site. We develop a transfer-matrix analytical framework to incorporate complex-valued feedback gains directly into dispersion and transmission calculations. Analytical predictions demonstrate that real-valued feedback yields opposite stiffness modifications for odd- and even-symmetric modes. This enables the simultaneous tuning of both defect bands and induces an exceptional-point-like coalescence. In contrast, imaginary feedback preserves stiffness but modulates effective damping, generating a parity-dependent amplification-suppression response. The analytical results closely match those of fully coupled finite-element simulations, reducing computation time by more than two orders of magnitude. These findings demonstrate that segmentation-enabled feedback provides an efficient and scalable approach to tunable, multi-band, non-Hermitian wave control in piezoelectric PnCs. Full article

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had major social and economic consequences worldwide. Whole genome sequencing (WGS) is essential for genomic monitoring, enabling tracking of viral evolution, detection of emerging variants, and identification of introductions and transmission chains to inform timely public health responses. Here, we compile and harmonize SARS-CoV-2 genomic data generated by multiple laboratories across Kazakhstan together with publicly available sequences to provide a national overview of genomic dynamics across successive epidemic waves from 2020 to 2022. We analyzed 4462 genomes deposited in GISAID (including 340 generated in this study), of which 3299 passed Nextclade quality filters, and summarized lineage turnover across major phases (pre-VOC, Alpha, Delta, Omicron BA.1/BA.2, Omicron BA.4/BA.5, and a later recombinant-dominant period). Sequencing intensity varied markedly over time (0.60‰ of confirmed cases during Delta vs. 11.57‰ during the Omicron BA.5 wave), suggesting that lineage diversity and persistence may be underestimated. Pre-VOC circulation included ≥12 Pango lineages with evidence of multiple introductions and sustained local transmission, including a Kazakhstan-restricted B.4.1 lineage that emerged in Nur-Sultan/Astana and disappeared after April 2020. The Tengizchevroil oilfield outbreak comprised B.1.1 viruses with phylogenetic support for ≥three independent introductions. Alpha and Omicron waves were characterized by repeated introductions and heterogeneous origins, whereas Delta was dominated by AY.122 with an additional distinct AY.122 cluster; a notable BF.7 local transmission event was observed during BA.5. We also highlight locally enriched non-lineage-defining mutations. Overall, recurrent importations and variable local amplification shaped SARS-CoV-2 dynamics in Kazakhstan, while interpretation is constrained by strongly time-skewed sequencing. Full article

In recent years, harmful algal blooms have led to frequent occurrences of shellfish toxin contamination, posing a significant threat to the safety of aquatic products and public health. As a potent neurotoxin, domoic acid (DA) can accumulate in shellfish, highlighting the urgent need for rapid and highly sensitive detection methods. In this study, we developed a fluorescent aptasensor based on a dual-signal amplification system by combining G-quadruplex (G4) dimers with multi-walled carbon nanotubes (CNTs). The sensor is designed with a hairpin-structured aptamer as the recognition probe, where short multi-walled CNTs serve as both a fluorescence quencher and platform, and G4 dimers are incorporated into the sensing interface to enhance signal output. In the absence of the target, the hairpin-structured aptamer remains closed, keeping the fluorescence signal “off”. Upon binding to DA, the aptamer undergoes a specific conformational change that exposes the G4-dimer sequence. The exposed sequence then binds to thioflavin T (ThT), which in turn generates a greatly enhanced fluorescence signal, leading to a substantial fluorescence enhancement and completing the second stage of the cascade amplification. Under optimal conditions, the constructed sensor achieves rapid detection of DA within 5 min, with a low detection limit of 1.1 ng/mL. This work presents a valuable tool for the rapid and sensitive detection of DA in shellfish, with promising applications in marine environmental monitoring and food safety regulation. Full article

Lavender has been cultivated in Bulgaria for over a century. The high essential oil content and quality of Bulgarian lavender varieties have established the country as a leading global producer. Studies into the crop’s genetic diversity are essential for selecting varieties best suited to specific environmental conditions, maximizing resilience and yield. Therefore, identifying appropriate genetic markers to monitor lavender diversity is a key prerequisite for developing effective crop selection strategies, particularly in response to the challenges posed by global climate change. In this study, we evaluate the versatility of markers for assessing genetic diversity of lavender genotypes. A total of 96, 97 and 96 bands were recorded using the 13 Start Codon Targeted Polymorphism (SCoT), 13 Inter-Simple Sequence Repeat (ISSR) and 14 Cis-Element Aligned Polymorphism (CEAP) primers, respectively. All amplification programs used were successful in the studied genotypes. Additionally, four informative primers of each marker system were applied for assessment of the within-field genetic variability in two lavender plantations from Bulgaria. This is the first report on the combined use and comparison of CEAP, SCoT and ISSR primers in lavender genotypes in Bulgaria. Full article

Metabolic dysfunction has emerged as a central driver of cardiovascular, renal, hepatic, and endocrine disorders, challenging traditional organ-specific disease models. Increasing evidence indicates that conditions such as obesity, type 2 diabetes, chronic kidney disease, heart failure, and metabolic dysfunction–associated steatotic liver disease frequently develop in parallel, reflecting shared upstream metabolic abnormalities rather than isolated pathologies. This narrative review synthesizes recent clinical, epidemiologic, biomarker, and therapeutic evidence to examine metabolic dysfunction as a unifying framework for multisystem disease, with particular focus on the cardiovascular–renal–hepatic–metabolic (CRHM) model. A targeted literature search of major biomedical databases was conducted to identify relevant studies published between 2020 and 2025, encompassing observational cohorts, randomized trials, and integrative reviews addressing cross-organ metabolic interactions. The reviewed evidence highlights consistent clinical overlap across organ systems, stage-dependent risk amplification and the utility of shared metabolic and inflammatory biomarkers in capturing multisystem vulnerability. In parallel, contemporary metabolic therapies demonstrate coordinated benefits across cardiovascular, renal, and hepatic domains, supporting the concept of common modifiable disease drivers. The reviewed evidence supports a shift from organ-based toward metabolic-centric frameworks for risk stratification and prevention. Viewing metabolic dysfunction as the organizing principle of cardiometabolic disease may improve recognition of multisystem risk, facilitate earlier intervention, and provide a more coherent foundation for precision and preventive medicine, in an era of growing cardiometabolic multimorbidity. Full article

In this study, the effects of electric-field intensity on N transformation during aerobic composting of biochar/pig manure were investigated. Four experimental groups were established under different applied voltages: 0 V (Group CK); 2 V (Group L); 4 V (Group M); and 5 V (Group H). The physicochemical properties of compost, as well as the nitrogen content and its existing forms in the compost, were systematically analyzed. The underlying mechanisms were further explored from the microscopic perspective by analyzing the pore structure of biochar and the microbial diversity in compost. The results showed that the total nitrogen content in compost increased by 5.66–20.87% with the application of the electric field. Cumulative NH₃ emissions decreased by 37.43%, 31.35%, and 40.95% in groups L, M, and H, respectively, while the NO₂ content decreased by 40.73%, 87.93%, and 94.44%, respectively, reducing the N losses during composting. The electric field significantly promoted the migration of nutrients from the compost to the surface of cotton stalk biochar. It also enhanced the microporous structure and adsorption capacity of cotton stalk biochar, thereby facilitating interfacial deposition and N immobilization. The amplification and sequencing of 16S rRNA gene further revealed that Ruminofilibacter, norank_f_MWH-CFBk5, and HN-HF0106 were the key bacterial genera affecting the gas emissions during aerobic composting. Among them, Ruminofilibacter and HN-HF0106 promoted the emission of N₂O, while norank_f_MWH-CFBk5 and Planktosalinus reduced NH₃ emission. This finding indicates that the electric field regulated N transformation and promoted N retention in compost by inhibiting the reproduction of denitrifying bacteria and increasing the abundance of nitrifying and nitrogen-fixing bacteria. This study confirms that electric field and biochar synergistically affect the nitrogen immobilization and waste resource utilization by optimizing the metabolic pathways of microorganisms and the structural characteristics of biochar. Full article

This paper presents a multichannel electronics measurement system that uses microwave sensors to perform real-time microplastics assessment in aqueous environments. The system is capable of simultaneously reading up to four microwave sensors, enabling the use of multiple sensors that target microplastic particles with different sizes and properties. The multichannel capability allows the measurement of multiple MW sensors integrated with different microfluidic channel designs while targeting different MPs’ dimension ranges, although experimental validation in this work was limited to a single sensor. Each readout channel is implemented combining radio-technology-integrated circuits with a microprocessor that has advanced analog peripherals used for signal conditioning and acquisition. An ADF4351 wideband frequency synthesizer is used for excitation signal generation while an ADL5902 power detector converts the sensor output to a DC voltage. Baseline removal and amplification of the power detector output is realized with a MSP430FR2355 microprocessor which is also responsible for its acquisition at 40 kHz and digital decimation. Characterization results show the system’s capability to generate excitation signals between 700 MHz and 3.5 GHz with power levels around 0 dBm. Sensor output can be detected with a power between −50 dBm and −5 dBm and a 230 Hz bandwidth. A compact form factor of 15 cm × 10 cm × 3 cm was realized together with a low power consumption of 6.6 W. Validation was realized with a previously developed microwave sensor, demonstrating the detection of polyethylene spheres with 400 μm diameters animated in 10 mL/min flux within the microfluidics device. Full article

The “Neuroimaging and Pathology Biomarkers in Parkinson’s Disease” course held on 12–13 September 2025 in Milan, Italy, convened an international faculty to review state-of-the-art biomarkers spanning neurotransmitter dysfunction, protein pathology and clinical translation. Here, we synthesize the four themed sessions and highlights convergent messages for diagnosis, stratification and trial design. The first session focused on neuroimaging markers of neurotransmitter dysfunction, highlighting how positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI) provided complementary insights into dopaminergic, noradrenergic, cholinergic and serotonergic dysfunction. The second session addressed in vivo imaging of protein pathology, presenting recent advances in PET ligands targeting α-synuclein, progress in four-repeat tau imaging for progressive supranuclear palsy and corticobasal syndromes, and the prognostic relevance of amyloid imaging in the context of mixed pathologies. Imaging of neuroinflammation captures inflammatory processes in vivo and helps study pathophysiological effects. The third session bridged pathology and disease mechanisms, covering the biology of α-synuclein and emerging therapeutic strategies, the clinical potential of seed amplification assays and skin biopsy, the impact of co-pathologies on disease expression, and the “brain-first” versus “body-first” model of pathological spread. Finally, the fourth session addressed disease progression and clinical translation, focusing on imaging predictors of phenoconversion from prodromal to clinically overt stages of synucleinopathies, concepts of neural reserve and compensation, imaging correlates of cognitive impairment, and MRI approaches for atypical parkinsonism. Biomarker-informed pharmacological, infusion-based, and surgical strategies, including network-guided and adaptive deep brain stimulation, were discussed as examples of how multimodal biomarkers may inform personalized management. Across all sessions, the need for harmonization, longitudinal validation, and pathology-confirmed outcome measures was consistently emphasized as essential for advancing biomarker qualification in multicentre research and clinical practice. Full article

Background/Objectives: In 2023, we reported that the tamarins (genus Saguinus) Saguinus imperator and Saguinus midas have had an extensive independent expansion of Platy-1 SINEs compared to previously characterized platyrrhine genomes among traditional cebids. This study investigates the amplification dynamics of Platy-1 insertions across thirteen diverse genomes representing each Platyrrhini family, including two from Pitheciidae and three from Atelidae. Methods: By comparing the distribution of Platy-1 subfamily content, total interspersed repeat content and the proximity of Platy-1 insertions to, or within, other repeats across evolutionary taxa, this study begins to identify genomic landscape features that are unique to family Callithrichidae that correlate with LINE (L1). Results: Platy-1 radiation in non-callithrichid taxa derives primarily from older subfamilies 1-4, 1-4a (as reported here for genus Alouatta) and 1-5, whereas callithrichids proliferate higher numbers of Platy-1 copies via independent bursts from much younger sources. Linage-specific Platy-1 activity was notable in two of the new genomes studied, Bolivian titi and mantled howler monkey, both with a relatively low copy number. Variable presence/absence patterns across evolutionary taxa support the traditional platyrrhine branching order Pitheciidae–Atelidae–Cebidae. Only one Platy-1-4a insertion polymorphism placed Aotidae between Atelidae and Cebidae, as opposed to between Cebidae and Callithrichidae. Conclusions: This study shows that callithrichids, and Saguinus tamarins in particular, are unique among platyrrhines with regard to their extensive rate of Platy-1 mobilization, a dynamic that appears to be correlated with LINE (L1) genomic content. Alouatta has two young lineage-specific Platy-1 subfamilies. With strong evidence of incomplete lineage sorting (ILS) and rapid radiation, the accurate placement of Aotus remains elusive. Full article

Understanding particle transport in rough-walled fractures is essential for predicting flow behavior, clogging, and permeability evolution in natural and engineered subsurface systems. This study develops a fully coupled CFD–DEM framework to investigate how self-affine fractal roughness, represented by the Joint Roughness Coefficient (JRC), governs fluid–particle interactions across multiple scales. Nine fracture geometries with controlled roughness were generated using a fractal-based surface model, enabling systematic isolation of roughness effects. The results show that increasing JRC introduces a hierarchy of geometric perturbations that reorganize the flow field, amplify shear and velocity-gradient fluctuations, and enhance particle–wall interactions. Particle migration exhibits a nonlinear response to roughness due to the competing influences of disturbance amplification and the formation of preferential high-velocity pathways. Furthermore, roughness-controlled scaling relations are identified for mean particle velocity, residence time, and energy dissipation, revealing JRC as a fundamental parameter linking geometric complexity to transport efficiency. Based on these findings, a unified mechanistic framework is established that conceptualizes fractal roughness as a multiscale geometric forcing mechanism governing hydrodynamic heterogeneity, particle dynamics, and dissipative processes. This framework provides new physical insight into transport behavior in rough fractures and offers a scientific basis for improved prediction of clogging, proppant placement, and transmissivity evolution in subsurface engineering applications. Full article

As an emerging threat to global food security, wheat blast necessitates the development of a rapid and field-deployable detection system to facilitate early diagnosis, enable effective management, and prevent its further spread to new regions. In this study, we aimed to validate and improve a Recombinase Polymerase Amplification coupled with PCRD lateral flow detection (RPA-PCRD strip assay) kit for the rapid and specific identification of Magnaporthe oryzae pathotype Triticum (MoT) in field samples. The assay demonstrated exceptional sensitivity, detecting as low as 10 pg/µL of target DNA, and exhibited no cross-reactivity with M. oryzae Oryzae (MoO) isolates and other major fungal phytopathogens under the genera of Fusarium, Bipolaris, Colletotrichum, and Botrydiplodia. The method successfully detected MoT in wheat leaves as early as 4 days post-infection (DPI), and in infected spikes, seeds, and alternate hosts. Furthermore, by combining a simplified polyethylene glycol-NaOH method for extracting DNA from plant samples, the entire RPA-PCRD strip assay enabled the detection of MoT within 30 min with no specialized equipment and high technical skills at ambient temperature (37–39 °C). When applied to field samples, it successfully detected MoT in naturally infected diseased wheat plants from seven different fields in a wheat blast hotspot district, Meherpur, Bangladesh. Training 52 diverse stakeholders validated the kit’s field readiness, with 88% of trainees endorsing its user-friendly design. This method offers a practical, low-cost, and portable point-of-care diagnostic tool suitable for on-site genomic surveillance, integrated management, seed health testing, and quarantine screening of wheat blast in resource-limited settings. Furthermore, the RPA-PCRD platform serves as an early warning modular diagnostic template that can be readily adapted to detect a wide array of phytopathogens by integrating target-specific genomic primers. Full article

Multipartite Gaussian Einstein–Podolsky–Rosen (EPR) steering is a key resource for quantum networks, but in practice it is strongly degraded by channel loss and excess noise. This motivates the need to distill multipartite Gaussian EPR steering across all relevant mode partitions. Here we propose and analyze a measurement-based noiseless linear amplification (NLA) protocol that distills Gaussian EPR steering in a four-mode square cluster state transmitted through lossy and noisy channels. Starting from a CV cluster shared by a transmitted node A and three local nodes (B, C, and D), we reconstruct the covariance matrix of the Gaussian cluster state and evaluate Gaussian steering monotones for all $(1+1)$, $(1+2)$, and $(1+3)$ bipartitions before and after applying measurement-based NLA. We show that appropriate conditioning on the noisy mode or on selected relay nodes systematically restores and enhances directional steering, extends both one-way and two-way steerable regions, and preserves the monogamy constraints characteristic of Gaussian graph states. Taken together, these results show that measurement-based NLA provides a practical route to distributing robust multipartite steering in CV cluster architectures, thereby strengthening the foundations for continuous-variable quantum information processing. Full article

Thrips are cosmopolitan agricultural pests and important vectors of plant viruses, and the increasing coexistence of multiple morphologically similar species has intensified the demand for species-specific molecular identification. However, traditional morphological identification and PCR assays using universal primers are often inadequate for mixed-species samples and field-adaptable application. In this study, we developed a species-specific molecular identification framework targeting a polymorphism-rich region of the mitochondrial cytochrome c oxidase subunit I (COI) gene, which is more time-efficient than sequencing-based COI DNA barcoding, for four economically important thrips species in southern China, including the globally invasive Frankliniella occidentalis. By aligning COI sequences, polymorphism-rich regions were identified and used to design four species-specific primer pairs, each containing a diagnostic 3′-terminal nucleotide. These primers were combined with a PBS-based DNA extraction workflow optimized for single-insect samples that minimizes dependence on column-based purification. The assay achieved a practical detection limit of 1 ng per reaction, demonstrated species-specific amplification, and maintained reproducible amplification at DNA inputs of ≥1 ng per reaction. Notably, PCR inhibition caused by crude extracts was effectively alleviated by fivefold dilution. Although the chemical identities of the inhibitors remain unknown, interspecific variation in inhibition strength was observed, with T. hawaiiensis exhibiting the strongest suppression, possibly due to differences in lysate composition. This integrated framework balances target specificity, operational simplicity, and dilution-mitigated inhibition, providing a field-adaptable tool for thrips species identification and invasive species monitoring. Moreover, it provides a species-specific molecular foundation for downstream integration with visual nucleic acid detection platforms, such as the CRISPR/Cas12a system, thereby facilitating the future development of portable molecular identification workflows for small agricultural pests. Full article

Conventional quantum mechanics treats the electron as a point-like particle endowed with intrinsic properties—mass, charge, and spin—that are inserted as axioms rather than derived from first principles. Here, we propose a thermodynamic reformulation of the electron grounded in entropy field dynamics, based on S-Theory. In this framework, the electron is composed of three distinct entropic components: S_core (a collapsed entropy core from configurational mass), S_EM (a structured electromagnetic entropy field from charge), and S_thermal (a diffuse entropy component from ambient interactions). We show that spin emerges as a rotating S_EM shell around S_core, and that electron collapse—as in quantum measurement—can be modeled as a Recursive Amplification of Sfield (RAS) process driven by entropic feedback. Through mathematical formulation and high-resolution simulations, we demonstrate how the S-field components evolve under entropic excitation, culminating in a collapse threshold defined by local entropy density matching. This model not only explains the emergence of quantum properties but also offers a thermodynamic mechanism for electron–photon interaction, wavefunction collapse, and spin generation, revealing the inner structure and dynamics of one of nature’s most fundamental particles. Full article

Background: Sarcomas are rare, aggressive malignancies with limited therapeutic options in advanced stages. This is the first real-world study in the MENA region evaluating the clinical utility of Next-Generation Sequencing (NGS) in guiding sarcoma treatment and improving outcomes. Methods: We retrospectively reviewed sarcoma patients who underwent NGS at a major referral center (2021–2024), comparing clinical and molecular outcomes between those who received NGS-based treatment adjustments (NBTA) and those who did not. Results: Seventy-eight patients were included (60% male; median age 44 years). Soft tissue sarcomas accounted for 70.5% of cases (n = 55), while bone sarcomas represented 29.5% (n = 23). Prior to NGS, 64.1% of patients had received a median of one line of systemic therapy. NGS was performed late in the disease course in 73% of cases. At least one mutation was detected in 87% (median 3 mutations). Targetable alterations were identified in 33% at the time of testing, rising to 42% with updated genomic knowledge and therapeutic advances. Overall, 20.5% received NBTA. Among non-NBTA patients, 67% had no actionable targets, 17% had no detectable mutations, and 16% were ineligible due to cost, limited access, or clinical deterioration. Tumor Mutational Burden was low in 79%, intermediate in 19%, and high in 2%, and all tumors were microsatellite stable. Patients receiving NBTA had a longer median Progression-Free Survival (9 vs. 2 months; p = 0.023). Median Overall Survival was longer in the NBTA group (74 vs. 48 months), though not statistically significant (p = 0.207). Genomic alterations were subtype-specific: EWSR1 rearrangements (Ewing and Desmoplastic small round cell tumors), CDK4 and MDM2 amplifications (Liposarcoma and Osteosarcoma), TP53 and RB1 mutations (Leiomyosarcoma), CDKN2A/B deletions (Undifferentiated Pleomorphic Sarcoma and Chondrosarcoma), and SS18 rearrangements (Synovial Sarcoma). Conclusions: Genomics-guided therapy in sarcoma is feasible and impactful. Expanding timely access to molecular profiling is essential for advancing precision oncology in the MENA region. Full article