Search Results (440)

Background and Objectives: Orthobiologic injectables—principally platelet-rich plasma (PRP), bone marrow aspirate concentrate (BMAC), cell-based therapies and, increasingly, extracellular vesicles—are widely used for chronic musculoskeletal (MSK) pain, yet their evidence base is inconsistent and guideline endorsement is heterogeneous. One frequently proposed contributor to this inconsistency is the use of biologically dissimilar products as interchangeable, one-size-fits-all injections in poorly stratified populations. This narrative review examines current evidence through a conceptual “precision” framework organized around three axes—the biology of the product, the pathology of the target tissue, and the phenotype of the patient—and around image-guided delivery as the procedural context in which these axes are operationalized. It spans osteoarthritis, tendinopathy, plantar fasciopathy, discogenic and spinal pain, and impaired bone healing, with emphasis on PRP, BMAC, and platelet- and cell-derived extracellular vesicles. Materials and Methods: PubMed/MEDLINE, Embase, Cochrane CENTRAL and Web of Science were searched from inception to 15 January 2026 and updated on 31 August 2026; 4812 de-duplicated records were screened by two authors independently, and 435 full texts were assessed, from which 76 sources are cited (36 clinical studies and evidence syntheses, 11 guidelines, consensus statements or reporting standards, and 29 narrative, mechanistic, regulatory or methodological references). Evidence was prioritized as guidelines and formal consensus, then syntheses with a certainty assessment, then individual trials, with neutral and negative trials given equal weight. This is a narrative, not a systematic, review; SANRA was used as a critical-appraisal checklist, not as a reporting guideline. Results: Across indications, pooled efficacy signals are frequently positive but of low-to-moderate certainty, with substantial risk of bias, small-study effects, and inconsistent product reporting; adequately controlled trials in knee osteoarthritis, Achilles and lateral-elbow tendinopathy, and discogenic pain have returned neutral results. Candidate response modifiers—structural phenotype, inflammatory and metabolic status, pain-processing phenotype, intraprocedural signals, and machine-learning models—are at present largely prognostic associations rather than validated treatment-effect modifiers. Guideline positions diverge, reflecting differences in methodology and evidence thresholds as well as in the underlying evidence. Conclusions: We present the three-axis framework as a testable hypothesis and a structure for stratified prospective trials, not as a validated clinical algorithm. We classify its components by clinical readiness, distinguish prognostic from predictive biomarkers, temper regenerative language where only symptomatic benefit is demonstrated, and identify platelet- and cell-derived extracellular vesicles as an early-stage, predominantly preclinical direction whose translational promise remains to be established. Full article

The methodological innovation of this study is a phase-domain separation-and-recombination framework that maps harmonic voltage to prospective flux, maps controlled quasi-DC winding current to magnetic operating-point displacement, and then resolves their nonlinear interaction through a shared-yoke three-limb model. A reduced nonlinear model informed by the measured major loops of a 50 kVA, 10 kV/400 V, Yyn0 transformer is evaluated over breaker-command angle and residual-flux sweeps. The operating matrix contains a sinusoidal baseline, a 0.15 p.u. negative-sequence second harmonic, a 0.08 p.u. negative-sequence fifth harmonic, their simultaneous application, and single-phase or asymmetric DC-current commands. Peak current, cycle-envelope decay, current total harmonic distortion, negative-sequence ratio, and a fourth-order three-phase current norm distinguish instantaneous from sustained stress. At the 60° command angle, the baseline, harmonic, DC-biased, and combined peaks are 21.30, 32.19, 35.15, and 41.67 A, respectively. Harmonic phase and sequence shift the knee-crossing instant and the dominant limb, whereas differential DC injection compresses one-directional saturation margin. The interaction contrast is interpreted as a model-output non-additivity statistic rather than an independent physical coupling constant. The conclusions are limited to the modeled distorted-source and differential-bias conditions; absolute prediction requires transformer-specific transient validation. Full article

GNSS cycle-slip diagnostics require thresholds that transfer across receivers and observation conditions. We combine causal dual-frequency phase–Doppler innovations (PDI), current-epoch common-mode subtraction, trailing robust normalization, worst-source quantile calibration, and half-cycle-grid ambiguity-increment repair. Three IGS source stations and an expanded station-disjoint target cohort of five stations supplied four separated 15 min blocks per station at native 1 s and decimated 5 s sampling. Two targets were usable from the original list; three were added after the primary run but before their data were inspected. Threshold calibration is source-only, whereas score normalization uses the causal target-stream history. At 1 s and the 1% source budget, PDI produced a 1.114% unmodified-background alarm rate (UBAR), 98.68% detection, and 98.34% exact dual-frequency repair over 3184 seeded event epochs. A post hoc fixed-score audit reduced UBAR from pooled calibration’s 1.284% without changing event success. A stronger covariance-weighted GF/MW integer-search control repaired 96.86% on the half-cycle grid; PDI’s paired five-station repair-gain interval was 0.19–2.97 percentage points. On integer-only events the control slightly exceeded PDI, and at 5 s it repaired 81.97% versus PDI’s 54.99%. Thus, the large advantage over componentwise GF/MW rounding does not extend to all classical repair estimators. The sampling-rate comparisons use separately generated, identically specified injection ensembles rather than paired physical events. The contribution is source-only threshold calibration with causal target-stream normalization, not universal repair superiority. UBAR includes unlabeled natural events; moving-receiver transfer and downstream positioning benefit remain unvalidated. Full article

With the growing complexity of electromagnetic environments, electronic systems suffer from prominent strong electromagnetic interference in practical service. As a key component implementing power amplification and transmission in communication systems, interference and damage effects of a GaN HEMT power amplifier under High-altitude Electromagnetic Pulse (HEMP) directly affect the regular operation of systems. In this paper, a physical device model and an injection source model are built first; injection simulations of different HEMP pulses are adopted to analyze internal temperature and current density distributions, predicting vulnerable positions of the device under gate injection. A GaN HEMT power amplifier based on CGH40010F is then established to investigate the failure mechanism under HEMP injection and the damage effect of different pulse parameters. An injection experiment system is conducted according to HEMP pulse standard; results indicate that power amplifier failure stems from GaN HEMT device destruction. The damage evolution is tightly associated with injected energy accumulation, and the gate–source channel is the susceptible region for GaN HEMT under gate injection. These conclusions can provide important references for the protective design of GaN HEMT power amplifiers. Full article

Environmental regulations and stricter emission limits are driving the development of advanced fuel supply systems. Precise fuel metering under varying engine loads has become critical, with modern strategies using multiple injections of very short duration. However, injector behavior, particularly nonlinear flow characteristics, is not fully understood. This study presents an experimental analysis of the flow characteristics Q = f (t_inj) and opening dynamics of five low-pressure gas injectors with different valve system designs. The tests were conducted for injection times t_inj = 0–20 ms. For t_inj > 2.5 ms, the characteristics were very well described by a linear model (R² > 0.995), whereas for t_inj < 2.5 ms, there was a clear deviation from the linear relationship between flow rate and injection time. Analysis of the electrical signals, outlet pressure, and body vibrations made it possible to identify the mechanistic sources of the observed nonlinearity. It was demonstrated that the initial lack of flow results from an electromechanical delay associated with the rise in current and the electromagnetic force required to overcome the spring force, friction, and inertia of the valve element. The subsequent movement of the valve contributing factors a dynamic change in the flow cross-sectional area and, consequently, a nonlinear change in flow rate. Additionally, the change in the position of the valve element affects the inductance of the coil and the nature of the electromagnetic force. Near the maximum lift, the element bounces off the stop, causing a momentary change in its position and a local decrease in flow rate. Only after the valve element’s motion stabilizes does the flow transition to a nearly linear relationship. The response times of the injectors ranged from 0.60 to 1.30 ms, and the times to reach full opening ranged from 1.08 to 2.14 ms, corresponding, respectively, to the onset and the transition to the steady-state region of the characteristic curve. The results indicate that the nonlinearity of the short-time portion of the characteristic has a mechanistic, electromechanical nature and results from the coupling of electromagnetic phenomena, the motion of the valve element, and the varying flow cross-section. This means that accurately modeling it requires taking into account the actual dynamics of valve-opening, particularly in the case of strategies that use short and repeated injection pulses. These findings highlight a significant limitation in fuel dosing precision and emphasize the need to incorporate nonlinear injector models or dynamic corrections in ECU control algorithms—an essential step for further reducing exhaust emissions. Full article

In non-obstructive azoospermia (NOA), microdissection testicular sperm extraction can provide sperm for intracytoplasmic sperm injection, but retrieval fails in approximately half of procedures. Genomic, transcriptomic, noncoding RNA, proteomic, metabolomic, and microbiome studies have reported molecular associations and prediction estimates. This critical narrative review examines the requirements for an assay–model system to support preoperative retrieval counseling. A focused PubMed/MEDLINE search updated on 31 August 2026 and targeted reference checking identified representative human reports and methodological guidance. Selected reports mainly illustrate discovery, development, and same-source evaluation. Common limitations include small cohorts, local assay optimization, heterogeneous outcomes, incomplete calibration, and uncertain transportability. Established karyotyping and Y-chromosome testing must be distinguished from discovery-scale genomics, which currently supports etiologic and qualified genotype-specific counseling rather than a universal calibrated retrieval model. A routine-variable multicenter model reported an external-cohort area under the receiver-operating-characteristic curve (AUC) of 0.8301, although cohort provenance, calibration, and clinical utility require independent confirmation. An author-developed seven-gate framework integrates clinical-question definition, assay specification, model development, internal validation, external evaluation, incremental value, and prospective impact. Future omics studies should test incremental value beyond a prespecified routine-variable model in the same patients and assess calibration, threshold consequences, net benefit, assay failure, cost, and patient outcomes. Full article

Myofascial pain syndrome (MPS) of the cervicoscapular girdle—most typically involving the upper trapezius and the rhomboid muscles—is among the most frequent causes of chronic regional musculoskeletal pain, yet the mainstays of interventional treatment (dry needling, local anesthetic trigger point injection, corticosteroid, botulinum toxin) act principally on nociceptive transmission or on the contractile taut band rather than on the disordered tissue biology that sustains it. Two injectable biologics with fundamentally different design logic have been proposed to fill this gap. Platelet-rich plasma (PRP) is an autologous, polypharmacological concentrate that delivers a supraphysiological bolus of platelet α-granule growth factors and leukocyte-dependent immunomodulators. Polydeoxyribonucleotide (PDRN) is a standardized, allogeneic-source (salmonid sperm DNA) low-molecular-weight deoxyribonucleotide mixture that acts through a single defined molecular target, the adenosine A2A receptor, supplemented by nucleoside salvage. This narrative review contrasts the two agents across four axes: (i) molecular and cellular mechanism; (ii) the biological plausibility of each in the specific microenvironment of the myofascial trigger point (MTrP)—an acidic, hypoxic, sensitizer-rich focus; (iii) the current clinical evidence in MPS and, by extension, across tendinopathy, plantar fasciitis, knee osteoarthritis, and acute muscle injury; and (iv) practical translational considerations including standardization, regulatory status, cost, and trial design. We conclude that PRP has the broader and methodologically stronger clinical evidence base in tendon and joint indications but is undermined by preparation heterogeneity and by consistently negative results in acute muscle injury, whereas PDRN offers reproducibility, an anti-inflammatory and pro-angiogenic profile that maps plausibly, based on preclinical evidence, onto MTrP pathophysiology, though direct validation in human myofascial tissue is lacking, and an excellent safety record, but is supported almost entirely by small, short-horizon, and frequently non-randomized studies. Neither agent can currently be recommended as standard care for trapezius or rhomboid MPS. We propose a mechanistic rationale and a concrete trial framework, including muscle-specific ultrasound-guided delivery, pressure pain threshold and Neck Disability Index as co-primary endpoints, and mandatory injectate characterization, for the head-to-head studies that the field now requires. Full article

Low Earth orbit (LEO) mega-constellations demand scalable routing that survives time-varying topologies, constrained onboard resources, and dynamic traffic. Deterministic shortest-path routing guarantees optimal paths but adapts poorly to real-time loads; distributed deep reinforcement learning (DRL) can introduce loops and inconsistent end-to-end decisions. This paper fuses deterministic inter-domain planning with DRL-based intra-domain forwarding in a single hierarchical framework. An evolutionary greedy algorithm partitions the constellation into compact domains. Dijkstra’s algorithm then computes backbone paths on the domain-level graph. Inside each domain, a context-enhanced Per-Action Dueling Double Deep Q-Network encodes individual neighbors through a weight-shared encoder and summarizes the valid-neighbor set via masked mean pooling. This design lets the policy compare a candidate against the current alternative set without injecting input-order bias. Local one- and two-hop topological features drive decentralized inference. A greedy–beam–Dijkstra fallback ladder guarantees reachability whenever the subgraph stays connected. On a 1584-satellite Starlink Gen1-1 topology, all 21 domain sizes and six inter-domain strategies reach 100% of test pairs; the best average hop count sits at 1.16× the global Dijkstra benchmark. Under an identical 52-dimensional state and training pipeline on 1000 held-out source–destination pairs, Context Per-Action uses 75.8% fewer parameters than a flat multilayer perceptron (MLP), lifts greedy success from 74.6% to 83.5%, and lifts greedy-plus-beam success from 88.3% to 94.5% (means over three independent training seeds). Centralized load-aware routing under dynamic traffic cuts high-load packet loss from 34–73% to 0–9.5% in the adopted flow-level model and preserves 99.2% reachability despite 30% link failures. Zero-shot transfer from ideal Walker topologies to real two-line element (TLE) snapshots and purely local load adaptation remain open; multi-snapshot training or online adaptation is the necessary next step. Full article

Hybrid systems comprising grid-following voltage-source converters (GFL-VSCs) and grid-forming voltage-source converters (GFM-VSCs) are increasingly adopted for renewable-energy integration. However, the influence of installed-capacity allocation on their coupled transient synchronization stability remains insufficiently characterized. This paper develops a capacity-ratio-dependent nonlinear transient model under a fixed total installed capacity. A synchronous-machine-like analytical framework is established to elucidate how the capacity ratio modifies GFL current injection, GFM power support, and current-limiting behavior, as well as the electrical coupling between the two converters. The critical clearing time (CCT) is employed as a quantitative measure of transient stability, and the reduced-order model is validated against a detailed MATLAB/Simulink model under three-phase and two-phase-to-ground faults. In addition, the sensitivities to key system and control parameters are investigated. The results demonstrate that transient stability varies non-monotonically with the capacity ratio. A low GFL capacity limits its fault-current contribution and alters the coupling dynamics, whereas a low GFM capacity weakens voltage-forming support and reduces the available margin before current limitation becomes dominant. The proposed analysis provides a quantitative basis for capacity allocation and stability-oriented design of hybrid converter-based power systems. Full article

This study establishes a field-measurement-based wideband modeling and station-level simulation framework for conducted high-frequency (HF) disturbance studies in modular multilevel converter-based high-voltage direct-current (MMC-HVDC) stations. Full-scale engineering-site frequency-response measurements are used to identify kHz-to-MHz terminal models of the arm reactor and the valve-side winding of the converter transformer. The arm reactor is fitted in the admittance domain by vector fitting and synthesized as a passive parallel network containing the main inductive path and multiple damped resistor–inductor–capacitor (RLC) branches. The transformer valve-side winding is represented by a Foster I/II hybrid $\pi$-type terminal network reconstructed from two single-phase port-impedance measurements. The validated equipment models are integrated into a representative Power Systems Computer-Aided Design (PSCAD) station model. A 2 ms valve-side source sequence, constructed from nearest-level-control switching instants and a parameterized switching-transient template, is applied in paired injection and zero-injection simulations. For the representative event, the source peak is 605.6 V. Over the first 4 $\mathsf{\mu }$s, the arm-reactor terminal reaches 972.6 V, while the direct-current (DC)-side, valve-side alternating-current (AC), and point-of-common-coupling (PCC) responses reach 534.2, 438.4, and 151.9 V, respectively. The corresponding peak changes relative to the source are $+4.11$, $-1.09$, $-2.81$, and $-12.01$ dB. The DC-side response contains a dominant damped oscillation near 0.61 MHz, and the AC/PCC transfer varies markedly across 0.2–2.0 MHz. In a separate control-identical comparison over the first 2.5 $\mathsf{\mu }$s, the field-identified and lumped models give DC-side peaks of 171.9 and 1.23 V and PCC peaks of 121.4 and 3.93 V under the same excitation. The framework connects field-identified equipment terminal behavior with station-level time-domain propagation analysis and provides a modeling basis for broadband resonance screening and conducted electromagnetic-interference (EMI) assessment. Full article

The semiconductor industry faces converging pressures from energy-constrained edge electronics and energy-bottlenecked high-performance computing, motivating heterogeneous monolithic three-dimensional (M3D) integration as a system-level response. M3D imposes a strict back-end-of-line (BEOL) thermal budget on upper-tier devices, restricting the channel materials and contact processes available and degrading conventional thin-film transistor performance. The source-gated transistor (SGT), in which drain saturation is set by gate-modulated injection across an engineered source barrier rather than by drain-side channel pinch-off, provides a device-level response: low saturation voltage, high output impedance, large intrinsic gain, and tolerance to channel-length variation, all achieved with moderate-mobility and nonideal-contact channel materials. This review organizes reported SGTs by source-barrier architecture and channel-material platform, develops a spatial characterization framework that complements electrical measurements for unambiguous identification of source-controlled operation, and surveys applications across standalone edge electronics and BEOL-compatible upper tiers in M3D stacks. Integrating non-volatile memory mechanisms into the source barrier further extends SGTs into a compute-in-memory and neuromorphic upper-tier role in which the voltage-invariant saturation current itself functions as a programmable, read-bias-robust state variable. Together, these considerations position SGTs as a flexible architectural primitive for heterogeneous M3D platforms that address the energy demands of both edge and high-performance computing. Full article

Tool-level attacks on Large Language Model (LLM) agents—poisoned tool descriptions, prompt injection, and capability misrepresentation—are universally effective, yet no existing defense provides comprehensive protection. We propose Architectural Intent Collapse (AIC), a formal framework capturing the systematic loss of communicative intent when text from heterogeneous sources is flattened into a single context window. Grounded as a novel instantiation of the Confused Deputy Problem, AIC reveals that the missing boundary is not permission but intent: the architecture cannot distinguish descriptive statements from prescriptive commands. We formalize AIC via an architectural collapse operator, introduce Intent Separation Degree (ISD) as a measurable metric, and develop a mechanism-based taxonomy of five intent-disguise attack types, including two previously undescribed (Conditional Latency and Inference Inducement). Experiments across 25 framework–model combinations (employing GPT-4o, Claude-4-Sonnet, Gemini-2.5-Pro, DeepSeek-V3, and Qwen3-32B as LLM backends) confirm that ISD degrades with description verbosity, strongly predicts defense effectiveness ($r=-0.97$), and is uniformly low across all current frameworks. Three root-cause defense principles are derived; one retains substantial protection against adaptive attackers. This research is useful for agent framework designers, security practitioners, and researchers seeking a principled understanding of why tool-level attacks succeed and how architectural defenses can address their root cause. Full article

Tendinopathies represent a major clinical challenge. Vasculature, neuromuscular junctions, low cellularity, and slow extracellular matrix (ECM) turnover restrict endogenous repair and predispose injured tendons to fibrosis, mechanical weakness, and reinjury. Current therapeutic strategies including rehabilitation protocols, anti-inflammatory medications, platelet-rich plasma (PRP) injections, and surgical repair primarily address symptoms or structural deficits without correcting the underlying biological limitations of tendon healing. Cell-based therapies have emerged as a promising regenerative approach aimed at restoring tissue homeostasis through modulation of angiogenesis, collagen synthesis, immune responses, and tenogenic differentiation. Mesenchymal stem cells (MSCs), adipose-derived stem cells (ADSCs), tendon-derived stem cells (TDSCs), induced pluripotent stem cells (iPSCs), differentiated tenocytes, and extracellular vesicle (EV)-based products have demonstrated the ability to enhance vascularization, promote type I collagen remodeling, suppress excessive inflammation, and stimulate tenocyte lineage commitment. These effects are mediated through paracrine signaling, growth factor secretion, and activation of key pathways, including HIF-1α, TGF-β/SMAD, NF-κB, and PI3K/Akt signaling. Despite promising preclinical data, significant translational challenges remain, including limited cell survival at the injury site, variability in cell sources and dosing, immunogenicity, risk of misdifferentiation, and lack of standardization across clinical protocols. Emerging strategies such as genetic modification, hypoxic preconditioning, scaffold-based delivery systems, and extracellular vesicle engineering aim to enhance therapeutic efficacy and reproducibility. This review synthesizes current evidence on cell-based tendon repair, critically evaluates mechanistic insights, clinical trials, and translational barriers, and outlines future directions toward biologically informed regenerative therapies. Full article

Particulate contamination in oral dosage forms poses significant challenges to product integrity and patient trust, yet these formulations lack the well-defined regulatory limits established for injectables. This review comprehensively analyses existing literature, regulatory guidelines, and analytical techniques to identify primary contamination sources, assess regulatory gaps, and propose science-based mitigation strategies. Key contamination vectors include raw materials, manufacturing equipment, facilities, packaging, personnel activities, utilities, processing aids, cleaning residues, and process design deficiencies. While solid oral dosage forms can encapsulate particulates, liquid formulations present a heightened ingestion risk. To combat these vulnerabilities, advanced analytical techniques—such as Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy, and X-ray fluorescence—are evaluated alongside emerging artificial intelligence-driven detection and real-time monitoring systems. Because current regulations inadequately address particulate matter in oral dosage forms, this paper introduces a structured decision pathway model to enhance contamination management. Ultimately, regulatory harmonization is essential for patient safety, and future research must focus on refining detection methodologies, risk-based strategies and establishing scientifically justified particulate thresholds. Full article

The deployment of large language models (LLMs) in real-world applications introduces a compounding security problem: detecting adversarial inputs such as prompt injection and jailbreak-driven data leakage while simultaneously preventing the detection mechanism itself from becoming a source of data exposure. Existing approaches address either detection effectiveness or privacy preservation, but rarely both in a unified, deployable architecture. This paper proposes and evaluates a privacy-preserving hybrid middleware architecture that enforces a local trust boundary as its primary design constraint. The architecture combines deterministic rule-based screening, a fine-tuned small language model (SLM) operating entirely within the local processing environment, and a sensitivity-aware routing mechanism that invokes external LLM reasoning only for prompts all local components have assessed as non-sensitive. Evaluation on a 120-prompt benchmark spanning benign, jailbreak, and sensitive categories (including 20 hard negatives constructed to be lexically adjacent to genuine secrets) shows that the routed architecture attains 95.83% accuracy with complete recall, retaining 95% of sensitive prompts within the local boundary, at the cost of a 12.5% false-positive rate. Comparison against two published detectors reveals a systematic asymmetry: an injection-specific classifier reaches 82.5% recall on jailbreak prompts but 25% on sensitive ones, while a content-safety model inverts that profile, confirming empirically that the two risks are addressed separately by current tooling. The framework is model-agnostic, requires no retraining of the underlying LLM, and is compatible with black-box API deployments. The evaluation dataset and fine-tuned model are released publicly. Full article