Search Results (384)

This paper details the implementation of an integrated engineering framework for the real-time assessment of pose and size in fusiform fish, utilizing laser-camera technology. The design, comprising a camera and laser emitter, leverages laser triangulation for accurately measuring distances between key points, providing a reliable baseline for data comparison. Enhanced with the yolov7 model backbone, it includes detection and segmentation features, enabling precise image instance segmentation of fish and laser lines. The system’s dual-network structure, which combines fully connected regression and DSNT-MobileFaceNet networks, efficiently identifies six crucial landmarks on fish—an essential step for detailed pose analysis. This method facilitates the accurate determination of two-dimensional fish posture by analyzing the relative positions of these landmarks. A notable capability of this system is its ability to infer depth information from laser lines on the fish’s body, aiding in the accurate measurement of dimensions such as body length and depth. Empirical results demonstrate the system’s effectiveness, with high mean Average Precision (mAP) values for both object detection (0.9560 for fish, 0.8550 for laser lines) and segmentation (0.9740 for fish, 0.8420 for laser lines). The DSNT-MobileFaceNet network, in particular, shows excellent fitting accuracy with an $R^2$ value of 0.9170. The deep learning model achieves an average error rate of 7.75% in detecting fish data, markedly improving upon the baseline error rate of 14.70%. Overall, this study confirms the proposed system’s capability in accurately assessing fish pose and size. As a rigorous proof of concept validated in a controlled laboratory environment, this work establishes a foundational framework for non-invasive morphological monitoring, suggesting its future applicability in marine biology and aquaculture. Full article

Background/Objectives: Advanced renal cell carcinoma (aRCC) remains incurable, with no established optimal sequence of targeted therapies due to interpatient heterogeneity and acquired resistance. We developed a luciferase-enabled patient-derived orthotopic xenograft (PDOX) avatar platform to evaluate sequential targeted therapies in individualized aRCC models that recapitulate tumor architecture, proliferation, angiogenesis, metastasis, and PD-L1 expression. Methods: Tumor specimens from two renal cell carcinoma (RCC) patients were expanded subcutaneously in NOD/SCID mice, transduced with luciferase/red fluorescent protein (Luc/RFP), and orthotopically implanted into mouse kidneys (KiCa-Pt58: sarcomatoid RCC, pT3aN1M1, Fuhrman grade 4; KiCa-Pt118: clear cell RCC with sarcomatoid component, pT3aNxM0, Fuhrman grade 4, respectively). Tumor growth and metastasis were monitored weekly by bioluminescence imaging (BLI). Mice were randomized into vehicle control or four sequential treatment groups (Everolimus→Sunitinib [E→S], Sunitinib→Everolimus [S→E], Pazopanib→Sunitinib [P→S], Pazopanib→Everolimus [P→E]). Drugs were administered orally three times weekly until resistance (>200% BLI increase), with one switch. At necropsy, tumor burden, ex vivo BLI metastasis, weights, H&E histology, and immunohistochemistry (Ki67, CD44, CD31, PD-L1) were assessed. Results: Two independent experiments were performed. In dosing optimization, PDOX tumors recapitulated parental histology and proliferative indices, mirroring patient trajectories. KiCa-Pt58 (metastatic sarcomatoid RCC; deceased 1-month post-nephrectomy) showed aggressive features: rapid engraftment at low doses, early growth (week 2), and lung metastases in 78% of mice (sacrifice day 34), reflecting a fulminant course. KiCa-Pt118 (non-metastatic; patient recurrence-free >8 years post nephrectomy) exhibited indolent behavior: delayed engraftment requiring higher doses plus lymph node stromal (HK) support, slower growth (week 4), no metastases, and later sacrifice (day 78), consistent with remission. In sequential therapy evaluation, for KiCa-Pt58, P→E yielded greatest reductions in tumor weight (p < 0.01), lung metastases (p < 0.01), Ki67+ proliferation, CD31+ angiogenesis, and PD-L1 expression versus control; E→S and S→E were also effective. For KiCa-Pt118, S→E and P→E reduced tumor burden (p < 0.01) and Ki67⁺ proliferation; S→E lowered CD31 and PD-L1. Conclusions: This RCC PDOX platform faithfully preserves patient-specific biology—including metastatic propensity, engraftment efficiency, growth kinetics, and stromal dependency—while enabling real-time evaluation of sequential targeted therapies. Given the limited number of models tested, these findings provide proof-of-concept for individualized treatment exploration in advanced RCC and support future investigation of rational combinations with immune checkpoint blockade in humanized or immunocompetent systems. Full article

Understanding cell migration is essential not only for fundamental biology but also for the development of targeted disease therapies. Traditional in vitro cell migration assays typically rely on optical microscopy to capture cell movements and subsequent image-based tracking to quantify cell migration characteristics, which often involve substantial experimental workload and analytical complexity. Therefore, there is a need for an automated and streamlined approach to monitor and analyze cell movements. In this work, a microfabricated impedance sensor integrating electrode pairs and selectively protein-coated channels was developed for real-time monitoring of single-cell migration. The optimized electrode dimensions with 10 μm width and 10 μm gap enabled sensitive detection of impedance magnitude increase induced by individual cells. The impedance magnitude changes were correlated with the cell coverage area on electrodes, allowing continuous tracking of single-mouse osteoblast MC3T3 cell movement across the electrode pair. Distinct impedance responses of signal duration and magnitude were observed under different surface coatings, revealing the influence of microenvironmental chemistry on cell motility and adhesion. Furthermore, comparative impedance profiling of MC3T3 and nasopharyngeal epithelial NP460 cells demonstrated that MC3T3 cells produced larger changes in impedance real part and phase due to larger spreading area and larger number of focal adhesions, whereas NP460 cells showed shorter impedance signal change durations, consistent with faster cell migration. These electrical signatures collectively captured intrinsic differences in cell morphology, adhesion, and motility. The developed impedance sensor provides a label-free approach for single-cell migration characterization and can be potentially applied to cell identification. Full article

Pancreatic cancer (PC) remains one of the most aggressive and lethal malignancies worldwide, largely due to late diagnosis, aggressive biology, limited therapeutic options and responsiveness. Conventional diagnostic and monitoring strategies, including imaging and serum biomarkers such as CA 19-9, provide limited sensitivity for early detection and suboptimal accuracy for the dynamic assessment of treatment response and disease evolution. These limitations highlight the urgent need for innovative, minimally invasive approaches capable of improving patient stratification and guiding personalized management. In this context, liquid biopsy has emerged as a promising, minimally invasive approach able to capture tumor-derived molecular information through the analysis of circulating cell-free nucleic acids, including circulating cell-free DNA (cfDNA) and circulating cell-free RNA (cfRNA). Released into the bloodstream by tumor cells, these analytes offer a real-time and comprehensive snapshot of tumor biology, capturing genetic, epigenetic, and transcriptional alterations through a simple blood draw. Liquid biopsy-based analyses hold significant potential for early detection, prognostic assessment, therapeutic decision-making, monitoring of minimal residual disease, and identification of resistance mechanisms. This review discusses the current state of research on circulating cell-free nucleic acids in PC, highlighting their biological basis, methodological approaches, clinical potential, and the challenges limiting their widespread implementation. By underscoring their translational relevance, we aim to outline how integrated liquid biopsy strategies, alongside the need for standardization and cross-study harmonization, may contribute to a more precise and dynamic approach to PC management. Full article

Women living with HIV face an increased burden of spontaneous preterm birth (sPTB); however, the underlying immunological mechanisms of sPTB and its association with HIV infection are poorly understood. Although the limited earlier literature implicates sphingosine-1-phosphate (S1P), a lysosphingolipid signaling molecule, in reproductive biology, the association of S1P signaling with HIV and sPTB has not been investigated. We examined whether two S1P signaling components, S1P receptors and sphingosine kinases, are expressed in the female reproductive tract and whether levels are associated with HIV status or spontaneous preterm birth. We quantified the mRNA expression of sphingosine-1-phosphate receptors 1 and 3 (S1PR1/S1PR3) and sphingosine kinases 1 and 2 (SPHK1/SPHK2) in 167 banked vaginal swab specimens collected between 14 and 26 weeks of gestation in a longitudinal pregnancy cohort in Lusaka, Zambia. We evaluated the expression of S1PR1, S1PR3, SPHK1, and SPHK2 by real-time quantitative reverse transcription PCR (RT-qPCR) in four groups (n = 41–42 each): women without HIV (WWoH) with term birth (≥37 weeks of gestation; TB), WWoH with spontaneous preterm birth (<37 weeks of gestation, sPTB), women with HIV (WWH) with TB, and WWH with sPTB. We found that S1P receptors and sphingosine kinases are expressed in the female reproductive tract. SPHK1 and SPHK2 mRNA expression were generally comparable among women independent of HIV status or birth outcome, though SPHK2 trended toward higher expression in women with HIV and women with sPTB. In contrast, S1PR1 mRNA trended toward higher expression in WWH vs. WWoH overall, as well as in WWH vs. WWoH among women with sPTB. Similarly, S1PR3 mRNA expression was greater in women with HIV than in women without HIV, and WWH, both with TB and sPTB, had higher S1PR3 mRNA expression than WWoH with TB. Perturbations in S1PR1 and S1PR3 mRNA expression may be associated with inflammation related to HIV infection and spontaneous preterm birth, suggesting that further studies of S1P signaling in pregnancy, especially among women with HIV, are warranted. Full article

This paper proposes a high-precision theoretical and computational neurorehabilitation framework for Mild Cognitive Impairment (MCI), connecting computational neuroscience and clinical practice through qEEG-guided neurofeedback training (NFT). By employing sLORETA to identify putative pathological nodes within the Default Mode Network (DMN)—specifically the Precuneus and the Posterior Cingulate—the model utilizes spectral decomposition to isolate the aperiodic 1/f component, reducing background noise bias and allowing the calculation of a pure individual alpha frequency (IAF) to inform recalibration of Weber’s Cognitive Threshold. The core architecture uses Bayesian algorithms and stochastic modeling to drive a Dynamic Weight Change mechanism. To support Long-Term Potentiation (LTP) and Hebbian learning, reward thresholds are modulated in real time to target a 70% success rate, as a strategic rationale to anticipate neural fatigue while maintaining the Reward Prediction Error required for synaptic strengthening. As a prospective validation pathway, future studies may assess clinical value through changes in MoCA and RAVLT scores, as well as by examining normalization of cortical coherence in the Default Mode Network (DMN). By merging computational neuroscience with biological models of synaptic plasticity, this work outlines how individual biology can be mapped into an explicit mathematical model. The proposed framework may inform an individualized protocol that provides an objective model-based measure of cognitive recovery, suggesting a replicable and robust strategy for neurorehabilitation during the prodromal phase of dementia, and providing a new approach to neuroscience-based cognitive rehabilitation. This work is intended as a theoretical and computational framework; no complete empirical dataset is reported in the present manuscript. Full article

Extracellular traps (ETs) are immune-derived chromatin networks initially described as antimicrobial barriers but increasingly recognized as modulators of tissue homeostasis and autoimmunity. The oral mucosa, constantly exposed to inflammatory stimuli, is particularly sensitive to ET-mediated remodeling (extracellular traps-mediated remodeling). In this study, we investigated how platelet-rich plasma (PRP), platelet-poor plasma (PPP), and washed platelets (WPT), widely used in regenerative medicine, influence ETosis in monocytes and macrophages, and how these ETs modulate the responses of primary buccal keratinocytes (pBMKs). ETs were induced in monocytes/macrophages using PRP, PPP, and WPT. pBMKs were exposed to ET-rich supernatants, and proliferation was monitored in real time through a live cell imaging system. ETs derived from PRP, PPP, and WPT did not induce either a statistically significant proliferation or morphological changes in buccal keratinocytes. These findings suggest that both platelet-derived products (PRP, PPP, WPT) and ETs play a crucial role in modulating epithelial biology, thus suggesting their possible role in chronic autoimmune diseases characterized by persistent inflammation and epithelial remodeling. Full article

Mast cell tumors are the most common skin neoplasm in dogs and may be influenced by reproductive status. A gonadectomy modifies gonadotropin levels and may affect the expression of hormonal receptors and proliferative factors; however, the evidence for this remains limited. The objective of this study was to evaluate the expression of VEGF, IGF-1, PCNA, Ki-67, c-KIT, LHR, FSHR, and ERα in intact and neutralized female dogs with and without MCTs. Gene expression in the skin samples was quantified by a real-time PCR, and four groups were included: intact controls (n = 10), neutralized controls (n = 10), intact MCT (n = 9), and neutralized MCT (n = 10). Tumor presence was associated with increased expression of LH and FSH receptors and c-KIT, while angiogenic and proliferative factors (PCNA, Ki-67, IGF-1, VEGF, and ERα) showed lower expression. In dogs with MCTs, a gonadectomy was associated with higher c-KIT and VEGF expression but lower LHR mRNA levels. PCNA expression was lower in the neutralized MCT dogs compared to the neutralized controls, whereas no differences were observed in the intact dogs. Additionally, ERα expression was higher in the neutralized control dogs than in the intact controls, with no differences detected in the MCT dogs. These findings suggest that reproductive status is associated with differential regulation of molecular pathways involved in canine MCT biology. Full article

Nitrate (NO₃⁻) serves as a pivotal molecule with dual functions in nutrient supply and signaling during plant growth and development. Precise monitoring of its spatiotemporal dynamics in planta is therefore essential for dissecting the regulatory mechanisms underlying plant nitrogen metabolism. However, conventional nitrate detection methods suffer from inherent limitations, including destructive sampling, insufficient spatiotemporal resolution, and an inability to achieve real-time whole-plant monitoring. Here, we report a genetically encoded nitrate biosensor, designated NitNRCL1, constructed using a split firefly luciferase complementation system. Functional validation in both prokaryotic and eukaryotic systems demonstrates that NitNRCL1 responds to changes in nitrate availability and generates stable chemiluminescent signals in bacteria and diverse plant species. Importantly, NitNRCL1 enables non-invasive, real-time, and whole-plant monitoring of nitrate levels in living plants. Using NitNRCL1, we successfully imaged the spatiotemporal dynamics of nitrate signaling in Arabidopsis thaliana. Collectively, our findings establish NitNRCL1 as a robust and novel tool for investigating nitrate transport, signaling, and metabolic pathways in plants. This biosensor advances our mechanistic understanding of plant nitrate biology and provides a technical foundation for breeding nitrogen-use-efficient crops and developing precision fertilization strategies. Full article

Liquid biopsy has emerged as a transformative tool in oncology, enabling minimally invasive and dynamic characterization of tumor biology. In prostate cancer, marked by high heterogeneity and frequent bone metastases, tissue biopsy is often challenging, highlighting the clinical value of circulating biomarkers. Circulating tumor DNA (ctDNA) is the most clinically advanced analyte, supporting detection of actionable alterations such as BRCA1/2 and ATM mutations, guiding targeted therapies, and enabling real-time monitoring of treatment response and resistance. Circulating tumor cells (CTCs) and extracellular vesicles (EVs) provide complementary insights into tumor biology and disease progression. However, challenges remain, including limited sensitivity in low tumor burden and biological confounders such as clonal hematopoiesis (CH), which can lead to false-positive findings. Emerging approaches, including fragmentomics and methylation profiling, offer improved tumor specificity and may help overcome these limitations. Together, these advances support the integration of liquid biopsy into clinical practice for personalized management and longitudinal monitoring in prostate cancer. Full article

The biomechanics of frog jumping has been a subject of significant interest in both biology and engineering, driven by the high efficiency of their movement. This study presents the dynamic simulation of a frog’s complete jump cycle, from take-off to landing and re-stabilization, to advance the development of bio-inspired jumping robots for irregular terrains. As a primary contribution, and unlike previous studies that focus exclusively on the propulsion phase, this work addresses all stages, using direct servomotor actuation without mechanical energy storage. Biological joint kinematics were mathematically characterized using Cubic Smoothing Splines. By empirically tuning the smoothing parameter ($p$), the trajectories achieved the continuous differentiability required for electromechanical actuation. These curves were implemented into a 3D multibody simulation (Altair Inspire), where a PID-based tracking framework managed the mechanically nonlinear multibody dynamics governing the jump (arising from contact forces, impacts, and time-varying inertial effects) to ensure stabilization during the complex landing phase. Validating the model against previous studies, the simulation successfully achieved a maximum horizontal jump distance of 24.12 cm (4.02 body lengths) and a peak velocity of 1.45 m/s. The kinematic fidelity of the model was mathematically validated, yielding a maximum Normalized Root Mean Square Error (NRMSE) of 4.121% relative to biological reference trajectories. Furthermore, the robustness of the landing and re-stabilization phases was demonstrated through a continuous double jump covering a total distance of 45.83 cm. Finally, a dynamic scaling analysis was performed to evaluate the feasibility of implementing real motors. Ultimately, this study establishes a mathematically robust framework for replicating frog-inspired jumping dynamics, contributing a transferable methodology for the design and control of articulated bio-inspired robotic systems. Full article

Extrahepatic cholangiocarcinoma (eCCA) is a highly aggressive malignancy arising from the biliary epithelium, with surgical resection representing the only potentially curative treatment. The predominant periductal infiltrating growth pattern, characterized by subepithelial tumor spread and desmoplastic stromal reaction, severely limits the diagnostic sensitivity of conventional endoscopic sampling techniques, which primarily assess the luminal mucosal surface. This review provides a histomorphology-oriented diagnostic framework for indeterminate extrahepatic biliary strictures, integrating advanced endoscopic technologies with emerging optical diagnostic approaches. ERCP combined with cholangioscopy demonstrates superior sensitivity for perihilar strictures, while EUS-guided tissue acquisition shows higher diagnostic yield in distal cholangiocarcinoma, also providing locoregional staging. Advanced EUS technologies—including elastography, contrast harmonic EUS, and Detective Flow Imaging—further improve characterization of indeterminate strictures by evaluating tissue stiffness, microvascular architecture, and periductal infiltration. Ex vivo fluorescence confocal laser microscopy (FCM) enables real-time microscopic evaluation of biopsy specimens, reducing diagnostic turnaround time and minimizing inadequate sampling. A location-adapted diagnostic algorithm integrating cross-sectional imaging, ERCP, cholangioscopy, and EUS is proposed. An integrated, biology-informed endoscopic approach tailored to tumor location and ductal wall involvement may significantly improve early eCCA detection and guide patient selection for curative treatment. Full article

While the quantum emergence of spacetime is becoming a major research topic in physics, the quantum emergence of intelligence has not been widely researched in quantum information science (QIS). Following causal-logical quantum gravity theory, bipolar entropy vs. entropy and negative entropy (or negentropy) are reviewed and distinguished for quantum emergence/submergence of quantum agent (QA) and quantum intelligence (QI) in algebraic terms. This work refers to QA as an entangled bipolar string/superstring in bipolar dynamic equilibrium (BDE) and QI being centered on logically definable causality in regularity, mind-light-matter unity, and brain-universe similarity. ER = EPR is extended to ER ≥≥ EPR for the mathematical scalability of bipolar strings and their collective entanglement. The extension leads to a number of conjectures, testable predictions, and theorems. The term “equilibraton” is proposed as a type of EPR or bipolar generic string to serve as an entropic stitch to collectively hold the universe together as a quantum entanglement in BDE with ubiquitous, regulated local emergence and submergence of QA&QI. Equilibraton leads to the concept of bipolar entropy square—a complete entropic solution to the background issue in quantum gravity. With complete background independence, energy/information conservational bipolar entropy, energy/information invariance, bipolar entropy non-additivity, and equilibrium-based plateau concavity are introduced. The nature of the one-dimensional arrow of time is conjectured. As a unification of order and disorder for equilibrium-based regulation, bipolar entropy bridges QA&QI to agentic AI, where quantum-bio-economics can be viewed as a topological intervention of a natural dynamic equilibrium in a social or natural world. Use cases are reviewed to illustrate the practical and theoretical aspects of bipolar entropy in business management, quantum-bio-economics, quantum cryptography, physics, and biology. Eddington–Einstein’s comments on entropy are revisited. It is expected that bipolar entropy will bring quantum emergence/submergence to agentic AI&QI for entangled machine thinking and imagination as a naturally scalable and testable foundation of real-world quantum gravity, quantum information science (QIS), quantum cognition and quantum biology (QCQB) to enhance Large Language AI Models (LLMs) and machine intelligence. Full article

The Mittag-Leffler function holds significant importance in fractional calculus due to its extensive applications in addressing challenges across science, engineering, biology, hydrology, and earth sciences. Notably, the closed-form solution of a time-fractional model naturally emerges as the Mittag-Leffler function (MLF), necessitating precise and efficient computations. Consequently, numerical approximations are essential for accurately calculating the Mittag-Leffler function. In this study, we develop a straightforward yet precise real pole rational approximation for the Mittag-Leffler function. We demonstrate first-order convergence and L-acceptability, which aid in mitigating unwanted oscillations. Additionally, we create an effective and precise first-order generalized exponential time differencing scheme to solve the time-fractional reaction–diffusion equations. We obtain and prove the convergence result using Grönwall-type inequality. Several numerical experiments are conducted to confirm the efficiency and accuracy of the proposed numerical scheme compared with exact solutions. The computational efficiency of the proposed method is compared with another existing first-order numerical technique. Furthermore, our proposed scheme is crucial for developing higher-order predictor–corrector schemes for solving time-fractional models. Full article

Bacterial biofilms are structured microbial communities enclosed within a self-produced extracellular polymeric substance matrix composed of polysaccharides, proteins, extracellular DNA, and lipids. This matrix promotes adhesion, structural stability, and the development of heterogeneous microenvironments that restrict antimicrobial penetration and shield bacteria from host immune responses. As a result, biofilms are major contributors to chronic, recurrent, device-related, and difficult-to-treat infections, posing a major challenge for clinical management and antimicrobial stewardship. This review summarizes current understandings of biofilm biology, its clinical relevance, including the stages of biofilm development, the composition and protective roles of the matrix, and the physiological heterogeneity that arises during maturation. It also examines key mechanisms underlying biofilm tolerance and resistance, such as limited antibiotic diffusion, and sequestration, enzymatic inactivation, efflux pump upregulation, persister cell formation, and horizontal gene transfer. In addition, it highlights important clinical settings in which biofilms are implicated, including cystic fibrosis, chronic wounds, osteomyelitis, implant- or device-associated infections, and breast implant illness, in which persistent implant-associated biofilms and the resulting chronic inflammatory milieu have been hypothesized to contribute to local and systemic manifestations in a subset of patients. The review further discusses conventional and emerging approaches for biofilm detection alongwith real-time monitoring. Biofilm-associated infections remain difficult to eradicate because persistence is driven by multiple interconnected protective mechanisms. Effective management therefore requires integrated strategies that combine accurate detection with multifaceted therapies, including antibiotics alongside matrix-disrupting enzymes, quorum-sensing inhibitors, bacteriophages, metabolic reactivators, and nanotechnology-based delivery systems. Advances in multi-omics and system-level modeling will be essential for developing next-generation strategies to prevent, monitor, and treat biofilm-associated disease. Full article