Search Results (257)

Major depressive disorder (MDD) is one of the most prevalent psychiatric conditions and is characterized by alterations in cortical excitability, network connectivity, and neuroplasticity. Despite significant progress in neuroimaging and neurophysiology, the identification of objective and reliable biomarkers remains a major challenge, limiting diagnostic accuracy and treatment optimization. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) has emerged as a powerful methodology to probe causal brain dynamics with high temporal resolution. This review aims to summarize recent advances in the application of TMS-EEG to MDD, highlighting the transition from traditional TMS-evoked potential (TEP) analyses to more advanced, multidimensional approaches. We reviewed original research articles published between 2020 and 2025 that investigated neurophysiological markers and approaches to MDD using TMS-EEG. Traditional TEP measures provide markers of local cortical responses but are limited in capturing distributed network dysfunction. Emerging approaches expand the scope of TMS-EEG, allowing for the characterization of oscillatory activity, connectivity patterns, and large-scale network dynamics. Recent contributions also demonstrate the potential of computational and multivariate techniques to enhance biomarker sensitivity and predictive value. Taken together, recent evidence highlights TMS-EEG as a uniquely positioned methodology to investigate the neurophysiological substrates of MDD. By linking conventional TEP-based indices with innovative analytic strategies, TMS-EEG enables a multidimensional assessment of cortical function and dysfunction that transcends traditional descriptive markers. This integrative perspective not only refines mechanistic models of MDD but also opens new avenues for biomarker discovery, patient stratification, and treatment monitoring. Ultimately, the convergence of advanced TMS-EEG approaches with clinical applications holds promise for translating neurophysiological insights into precision psychiatry interventions aimed at improving outcomes in MDD. Full article

Motivated by the recent CMS observation of a near-threshold enhancement in top quark pair production, we investigate a novel class of hadronic systems containing a single top quark: the topped mesons ($t\overline{q}$, with $\overline{q}=\overline{u},\overline{d},\overline{s}$). In contrast to the extensively studied toponium ($t\overline{t}$) system—analyzed primarily within perturbative QCD—topped mesons offer a complementary nonperturbative probe of QCD dynamics in the heavy quark limit. These states are expected to exhibit longer lifetimes and narrower decay widths than toponium, as only a single top quark undergoes weak decay. We employ QCD sum rules within the framework of heavy quark effective theory to study the structure and mass spectrum of ground-state topped mesons. Our analysis predicts masses near 173.1 GeV, approximately 0.5–0.6 GeV above the top quark pole mass. Compared with singly topped baryons ($tqq$, with $q=u,d,s$), topped mesons have a simpler quark composition and more favorable decay channels (a topped meson is anticipated to decay weakly into a $\mathrm{{\rm Y}}$ meson and a charmed meson), enhancing their potential for both theoretical analysis and experimental discovery. Full article

Alpha-synuclein (αsyn) misfolding and aggregation underlie several neurodegenerative disorders, including Parkinson’s disease. Early oligomeric intermediates are particularly toxic yet remain challenging to detect and characterize within cellular systems. Here, we employed the luminescent conjugated oligothiophene h-FTAA to investigate early aggregation events of human wildtype (huWT) and A53T-mutated αsyn (huA53T) both in vitro and in HEK293 cells stably expressing native human-αsyn. Comparative fibrillation assays revealed that h-FTAA detected αsyn aggregation with higher sensitivity and earlier onset than Thioflavin T, with the A53T variant displaying accelerated fibrillation. HEK293 cells stably expressing huWT- or huA53T-αsyn were exposed to respective pre-formed fibrils (PFFs), assessed via immunocytochemistry, h-FTAA staining, spectral emission profiling, and fluorescence lifetime imaging microscopy (FLIM). Notably, huA53T PFFs promoted earlier aggregation patterns and yielded narrower fluorescence lifetime distributions compared with huWT PFFs. Spectral imaging showed h-FTAA emission maxima (~550–580 nm) red-shifted and broadened in cells along with variable lifetimes (0.68–0.87 ns), indicating heterogeneous aggregate conformations influenced by cellular milieu. These findings demonstrate that h-FTAA is useful for distinguishing early αsyn conformers in living systems and, together with stable αsyn-expressing HEK293 cells, offers a platform for probing early αsyn morphotypes. Taken together, this opens for further discovery of biomarkers and drugs that can interfere with αsyn aggregation. Full article

Background/Objectives: Prenatal exposure to famine can lead to lasting health effects through changes in DNA methylation. This study aims to evaluate the impact of prenatal exposure to the Chinses Great Famine (1959–1961) on human epigenome and the subsequent influence on blood lipids. Methods: We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and prenatal exposure to the Chinese Great Famine as well as blood lipids among eight participants exposed to famine and eight sex-matched participants (born ≤ 3 years after the famine). Genome-wide DNA methylation sites were profiled using the Illumina EPIC BeadChip, which covers 850K methylation positions. Results: After EWAS analyses, seven probes in genes C8orf31, ELAVL1, U6, GBA2, SHOX2, SLC1A4, and NPHP4 reached p < 1 × 10⁻⁵. Of these, famine exposure was associated with decreased methylation levels of a GBA2 exonic probe cg08258661 (p = 4.9 × 10⁻⁶). After false discovery rate (FDR) correction, pathway enrichment analyses for genes harboring nominally significant (p < 0.05) probes identified 44 significant pathways (q < 0.05), and 5 pathways were related to lipid metabolism. After FDR correction in each pathway, probes cg02622866 (5’UTR of ATF2, p = 1.09 × 10⁻³), cg07316730 (body of GRB2, p = 1.32 × 10⁻³), and cg01105385 (body of PIK3R1, p = 1.94 × 10⁻³) in the PI2K-Akt signaling pathway were associated with blood LDL-C (q ≤ 0.04); probes cg09180702 (3’UTR of PIGQ, p = 9.21 × 10⁻⁵, and q = 0.04) and cg01421548 (body of HS3ST4, p = 5.23 × 10⁻⁵, and q = 0.01) in the metabolism pathway were associated with blood LDL-C and HDL-C, respectively; In addition, probe cg08460387 (5’UTR of MAN1C1, p = 1.09 × 10⁻⁴, and q = 0.02) in the vesicle-mediated transport pathway was associated with log-transformed blood triglycerides. Conclusions: Through an epigenetic study of the Chinese Great Famine, we identified six novel genes involved in lipid metabolism. Full article

Detection of cancer biomarkers at the earliest stages of disease progression is commonly assumed to extend the overall quality of life for cancer patients as the result of earlier clinical management of the disease. Therefore, there is an urgent need for the development of standardized, sensitive, robust, and commonly available screening and diagnostic tools for detecting the earliest signals of neoplastic pathology progression. Recently, a new paradigm of cancer control, known as multi-cancer detection (MCD), evolved, which measures the composition of cancer-related molecular analytes in the patient’s fluids using minimally invasive techniques. In this respect, the “Holy Grail” of cancer researchers and bioengineers for decades has been composing a repertoire or molecular sensing probes that would allow for the diagnosis, prognosis, and monitoring of cancer diseases via their interaction with cell-secreted and cell-associated cancer antigens and biomarkers. Therefore, the current trend in screening and detection of cancer-related pathologies is the development of portable biosensors for mobile laboratories and individual use. Phage display, since its conception by George Smith 40 years ago, has emerged as a premier tool for molecular evolution in molecular biology with widespread applications including identification and screening of cancer biomarkers, such as Circulating Cellular Communication Network Factor 1 (CCN1), an extracellular matrix-associated signaling protein responsible for a variety of cellular functions and has been shown to be overexpressed as part of the response to various pathologies including cancer. We hypothesize that CCN1 protein can be used as a soluble marker for the early detection of breast cancer in a multi-cancer detection (MCD) platform. However, validated probes have not been identified to date. Here, we screened the multi-billion clone landscape phage display library for phages interacting specifically with immobilized CCN1 protein. Through our study, we discovered a panel of 26 different phage-fused peptides interacting selectively with CCN1 protein that can serve for development of a novel phage-based diagnostic platform to monitor changes in CCN1 serum concentration by liquid biopsy. Full article

Opportunistic networks, as an emerging ad hoc networking technology, the sparse distribution of nodes poses significant challenges to data transmission. Additionally, unlike static nodes in traditional ad hoc networks that can replenish energy on demand, the inherent mobility of nodes further complicates energy management. Thus, selecting an energy-efficient neighbor discovery algorithm is critical. Passive listening conserves energy by continuously monitoring channel activity, but it fails to detect inactive neighboring nodes. Conversely, active probing discovers neighbors by broadcasting probe packets, which increases energy consumption and may lead to network congestion due to excessive probe traffic. As the primary communication nodes in the maritime environment, vessels exhibit high mobility, and networks in oceanic regions often operate as opportunistic networks. To address the challenge of limited energy in maritime opportunistic networks, this paper proposes a hybrid neighbor discovery method that combines both passive and active discovery mechanisms. The method optimizes passive listening duration and employs Q-learning for adaptive power control. Furthermore, a more suitable wireless communication model has been adopted. Simulation results demonstrate its effectiveness in enhancing neighbor discovery performance. Notably, the proposed scheme improves network throughput while achieving up to 29% energy savings at most during neighbor discovery. Full article

While immunophilins are well-recognized therapeutic targets, several members of this family of peptidyl-proline isomerases (PPIases) have yet to be subjected to ligand discovery efforts. In this study, we demonstrate a cost-effective means to identify ligands to the insufficiently investigated two-domain PPIase human Cyclophilin40 (Cyp40). Central to this effort was the use of beads, wherein a confocal nanoscanning (CONA) approach was used to rapidly probe candidates. Here, we describe how one can adapt the physical nature of microsized beads as a means to strategically reduce cost and ultimately make the discovery of small molecule hit and lead compounds more accessible to everyone irrespective of financial status (democratization). Full article

Asset discovery in critical infrastructures, and in particular within industrial control systems, constitutes a fundamental cybersecurity function. Ensuring accurate and comprehensive asset visibility while maintaining operational continuity represents an ongoing challenge. Existing methodologies rely on deterministic tools that apply fixed fingerprinting strategies and lack the capacity for contextual reasoning. Such approaches often fail to adapt to the heterogeneous architectures and dynamic configurations characteristic of modern critical infrastructures. This work introduces an architecture based on a Mixture of Experts model designed to overcome these limitations. The proposed framework combines multiple specialized modules to perform automated asset discovery, integrating passive and active software probes with physical sensors. This design enables the system to adapt to different operational scenarios and to classify discovered assets according to functional and security-relevant attributes. A proof-of-concept implementation is also presented, along with experimental results that demonstrate the feasibility of the proposed approach. The outcomes indicate that our LLM-based approach can support the development of non-intrusive asset management solutions, strengthening the cybersecurity posture of critical infrastructure systems. Full article

A myriad of biological effects can be stimulated by ultrasound (US) for the treatment of cancer. The objective of our research was to investigate the effect of ultrasound alone and in combination with chemotherapeutic drugs such as doxorubicin (DOX) and temozolomide (TMZ) on human glioblastoma (GBM) and the human epidermoid carcinoma cancer 2D and 3D cell cultures. The results indicated that the US 96-probe device could induce tumour sphere cytotoxicity in a dosage- and time-dependent manner, with multiple treatments augmenting this cytotoxic effect. With enhanced cytotoxicity, US decreased tumour sphere growth metabolic activity, disrupted spheroid integrity, and heightened the occurrence of DNA double strand breaks, resulting in damage to tumour spheres and an inability to rebuild tumour spheres after multiple US treatments. The combination of US and TMZ/DOX enhanced the efficiency of treatment for GBM and epidermoid carcinoma by enhancing induced cytotoxicity in 3D tumour spheres compared to 2D monolayer cells and also by increasing the incubation time, which is the most crucial way to differentiate between the effectiveness of drug treatment with and without US. In conclusion, our data demonstrate that US enhances drug diffusion, uptake, and cytotoxicity using 3D spheroid models when compared with 2D cultures. They also demonstrate the significance of 3D cell culture models in drug delivery and discovery research. Full article

Targeted protein degradation (TPD) has emerged as a revolutionary strategy for modulating protein function, offering a promising alternative to traditional small-molecule inhibitors. The distinctive mechanism of action in TPD has previously allowed researchers to target undruggable proteins, broadening the scope of “druggable” properties and expanding the scope of therapeutic possibilities. As the field of TPD advances, several alternative strategies to proteolysis-targeting chimeras (PROTACs) have emerged, which do not rely on the E3 ubiquitin ligase recruitment mechanism, expending the scope of TPD. Recently, several new technologies have emerged for TPD of extracellular and membrane proteins. While encouraging progress has been made in this field, the application of these technologies remains in its early stages. In this review, we explore the therapeutic potential of current key emerging lysosome-mediated TPD approaches by summarizing key discoveries and address the challenges associated with degrading extracellular and membrane protein targets. We also outline the chemical structure, activity, and pharmaceutical properties of each degrader, as well as the development of chemical probes for perturbing autophagy pathways. Full article

SPR biosensors operate on the principle of evanescent wave propagation at metal–dielectric interfaces in total internal reflection conditions, with consequent photonic energy attenuation. This plasmonic excitation occurs in specific conditions of incident light wavelength, angle, and the dielectric refractive index. This principle has been the basis for SPR-based biosensor setups wherein mass/concentration-induced changes in the refractive indices of dielectric media reflect as plasmonic resonance condition changes quantitatively reported as arbitrary response units. SPR biosensors operating on this conceptual framework have been designed to study biomolecular interactions with real-time readout and in label-free setups, providing key kinetic characterization that has been valuable in various applications. SPR biosensors often feature antibodies as target affinity probes. Notably, the operational challenges encountered with antibodies have led to the development of aptamers—oligonucleotide biomolecules rationally designed to adopt tertiary structures, enabling high affinity and specific binding to a wide range of targets. Aptamers have been extensively adopted in SPR biosensor setups with promising clinical and industrial prospects. In this paper, we explore the growing literature on SPR setups featuring aptamers, specifically providing expert commentary on the current state and future implications of these SPR aptasensors for drug discovery as well as disease diagnosis and monitoring. Full article

Biodiversity monitoring requires the discovery of multi-target tracking. The main requirement is not to reduce the localization error but the continuity of the tracks: a high ratio between the duration of the track and the lifetime of the target. To this end, we present an algorithm for detecting and tracking mobile underwater targets that utilizes reflections from active acoustic emission of broadband signals received by a rigid hydrophone array. The method overcomes the problem of a high false alarm rate by applying a tracking approach to the sequence of received reflections. A 2D time–distance matrix is created for the reflections received from each transmitted probe signal by performing delay and sum beamforming and pulse compression. The result is filtered by a 2D constant false alarm rate (CFAR) detector to identify reflection patterns that correspond to potential targets. Closely spaced signals for multiple probe transmissions are combined into blobs to avoid multiple detections of a single target. The position and velocity are estimated using the debiased converted measurement Kalman filter. The results are analyzed for simulated scenarios and for experiments in the Adriatic Sea, where six Global Positioning System (GPS)-tagged gilt-head seabream fish were released and tracked by a dedicated autonomous float system. Compared to four recent benchmark methods, the results show favorable tracking continuity and accuracy that is robust to the choice of detection threshold. Full article

Electrical transport in 2D materials exhibits unique behaviors due to reduced dimensionality, broken symmetries, and quantum confinement. It serves as both a sensitive probe for the emergence of coherent electronic phases and a tool to actively manipulate many-body correlated states. Exploring their interplay and interdependence is crucial but remains underexplored. This review integratively cross-examines the atomic and electronic structures and transport properties of van der Waals-layered crystals ZrTe₃, 2H-TaS₂, and Cr₂Si₂Te₆, providing a comprehensive understanding and uncovering new discoveries and insights. A common observation from these crystals is that modifying the atomic and electronic interface structures of 2D van der Waals interfaces using heteroatoms significantly influences the emergence and stability of coherent phases, as well as phase-sensitive transport responses. In ZrTe₃, substitution and intercalation with Se, Hf, Cu, or Ni at the 2D vdW interface alter phonon–electron coupling, valence states, and the quasi-1D interface Fermi band, affecting the onset of CDW and SC, manifested as resistance upturns and zero-resistance states. We conclude here that these phenomena originate from dopant-induced variations in the lattice spacing of the quasi-1D Te chains of the 2D vdW interface, and propose an unconventional superconducting mechanism driven by valence fluctuations at the van Hove singularity, arising from quasi-1D lattice vibrations. Short-range in-plane electronic heterostructures at the vdW interface of Cr₂Si₂Te₆ result in a narrowed band gap. The sharp increase in in-plane resistance is found to be linked to the emergence and development of out-of-plane ferromagnetism. The insertion of 2D magnetic layers such as Mn, Fe, and Co into the vdW gap of 2H-TaS₂ induces anisotropic magnetism and associated transport responses to magnetic transitions. Overall, 2D vdW interface modification offers control over collective electronic behavior, transport properties, and their interplays, advancing fundamental science and nanoelectronic devices. Full article

Cryptic sites, which are transient binding sites that emerge through protein conformational changes upon ligand binding, are valuable targets for drug discovery, particularly for allosteric modulators. However, identifying these sites remains challenging because they are often discovered serendipitously when both ligand-binding (holo) and ligand-free (apo) states are experimentally determined. Here, we introduce CrypTothML, a novel framework that integrates mixed-solvent molecular dynamics (MSMD) simulations and machine learning to predict cryptic sites accurately. CrypTothML first identifies hotspots through MSMD simulations using six chemically diverse probes (benzene, dimethyl-ether, phenol, methyl-imidazole, acetonitrile, and ethylene glycol). A machine learning model then ranks these hotspots based on their likelihood of being cryptic sites, incorporating both hotspot-derived and protein-specific features. Evaluation on a curated dataset demonstrated that CrypTothML outperforms recent machine learning-based methods, achieving an AUC-ROC of 0.88 and successfully identifying cryptic sites missed by other methods. Additionally, CrypTothML ranked cryptic sites as the top prediction more frequently than existing methods. This approach provides a powerful strategy for accelerating drug discovery and designing allosteric drugs. Full article

Spaceborne radar is a powerful tool for probing planetary subsurface structures. Earlier radar studies of the Moon have primarily examined large-scale horizontal structures. However, recent discoveries of vertical holes suggesting the existence of lava tubes and theoretically predicted subsurface gas voids formed by volatiles in magma have highlighted the importance of small-scale subsurface structures. We developed a method using SELENE Lunar Radar Sounder (LRS) data to detect small-scale subsurface echoes (hundreds of meters). Surface scattering simulations incorporating incoherent scattering from sub-resolution roughness were performed using a high-resolution digital elevation model generated by a generative adversarial network. Detection thresholds for subsurface echo candidates (SECs) were determined from the histograms of difference intensities between LRS and simulation B-scans. Results show that some SECs exist in the extension area of the analyzed graben. SECs were also detected continuously across multiple LRS ground tracks in areas unrelated to grabens. Using the radar equation analysis, the echo intensities of SECs could be explained for subsurface structures with 50–600 m widths and dielectric constants of 1–4. This suggests the existence of either subsurface voids or materials with a high porosity of more than 35%. Among the SECs detected continuously across multiple LRS ground tracks, those that are more or less aligned in the downward elevation direction are likely indicative of lava tubes. On the other hand, the SECs distributed along the extension of the graben are aligned parallel to the contour lines. These SECs likely suggest gas voids at the tip of the intrusive magma that formed the graben. Full article