Search Results (626)

Streak cameras, essential for ultrahigh temporal resolution diagnostics in laser-driven inertial confinement fusion, underpin the streak tube imaging LiDAR (STIL) system—a flash LiDAR technology offering high spatiotemporal resolution, precise ranging, enhanced sensitivity, and wide field of view. This study establishes a theoretical model of the STIL system, with numerical simulations predicting limits of temporal and spatial resolutions of ~6 ps and 22.8 lp/mm, respectively. Dynamic simulations of laser backscatter signals from targets at varying depths demonstrate an optimal distance reconstruction accuracy of 98%. An experimental STIL platform was developed, with the key parameters calibrated as follows: scanning speed (16.78 ps/pixel), temporal resolution (14.47 ps), and central cathode spatial resolution (20 lp/mm). The system achieved target imaging through streak camera detection of azimuth-resolved intensity profiles, generating raw streak images. Feature extraction and neural network-based three-dimensional (3D) reconstruction algorithms enabled target reconstruction from the time-of-flight data of short laser pulses, achieving a minimum distance reconstruction error of 3.57%. Experimental results validate the capability of the system to detect fast, low-intensity optical signals while acquiring target range information, ultimately achieving high-frame-rate, high-resolution 3D imaging. These advancements position STIL technology as a promising solution for applications that require micron-scale depth discrimination under dynamic conditions. Full article

Non-invasive, continuous monitoring of carotid artery hemodynamics may provide valuable insights on cerebral blood perfusion (CBP). Near-infrared spectroscopy (NIRS) is a non-invasive modality that may be a good candidate for real-time carotid artery monitoring. We designed a wearable NIRS system to monitor the left and right radial and carotid arteries in 20 healthy subjects. The changes in total hemoglobin concentration (HbT) and tissue oxygen saturation (StO₂) in all 80 arteries were continuously monitored in response to changes in oxygen supply. Wilcoxon non-parametric equivalence testing was used to compare changes in the radial (reference) and carotid arteries. The system-derived HbT and StO₂ trends matched the expected physiological responses over time in the radial and carotid arteries. The mean peak-to-peak amplitude [uM] of HbT during sustained deep breathing was practically equivalent between the left radial (0.9 ± 0.8) and left carotid (1.6 ± 1.1) arteries (p = 0.01). The mean peak-to-peak amplitude [%] of StO₂ was practically equivalent between the left radial (0.3 ± 0.2) and left carotid (0.3 ± 0.2) arteries (p < 0.001) and the right radial (0.4 ± 0.5) and right carotid (0.5 ± 0.4) arteries (p = 0.001). These findings indicate that NIRS may be a good option for monitoring the carotid arteries to track changes in CBP. Full article

Head and neck cancer (HNC) is the seventh most common cancer worldwide, with rising incidence particularly in oropharyngeal cancer subsites. Despite well-known risk factors, such as tobacco and alcohol consumption as well as human papillomavirus (HPV) infection, most HNCs are diagnosed at an advanced stage, resulting in poor prognosis. Early detection and screening are critical, especially in high-risk populations. Nevertheless, there is a lack of guidelines for a stratified HNC screening. A systematic literature review was conducted following PRISMA guidelines, using PubMed and ScienceDirect databases up to 30 June 2025. Search terms included “screening”, “early diagnosis”, and specific HNC subsites. A total of 199 records were screened, and 160 studies were included based on relevance and scientific rigor. The review concentrates on contemporary screening modalities, stratification of high-risk cohorts, emerging technologies, and cost-effectiveness evidence. Visual inspection and panendoscopy remain the standard tools for HNC screening, but have limited effectiveness and cost-efficiency. Opportunistic screening in high-risk individuals, especially in regions with high HNC prevalence, has shown benefits. Liquid biopsy techniques targeting HPV- and Epstein-Barr virus-related HNC demonstrate high sensitivity for early detection and recurrence monitoring. Novel imaging technologies like narrow-band imaging and Raman spectroscopy show promising diagnostic accuracy but require further validation. Most broad-based screening programs lack cost-effectiveness, while targeted strategies in high-risk groups appear more viable. Screening for HNC should be stratified by individual risk profiles and regional disease prevalence. Emerging technologies, particularly liquid and optical biopsy techniques, offer transformative potential. Future screening strategies must integrate technological advances into tailored, evidence-based protocols to improve early detection and patient outcomes in HNC. Full article

Background: Raman Spectroscopy is a non-invasive technique capable of characterising tissue constituents and detecting conditions such as cancer with high accuracy. Machine learning techniques can automate this task and discover relevant data patterns. However, the high-dimensional, multicollinear nature of Raman data makes their deployment and explainability challenging. A model’s transparency and ability to explain decision pathways have become crucial for medical integration. Consequently, an effective method of feature-reduction while minimising information loss is sought. Methods: Two new feature selection methods for Raman spectroscopy are introduced. These methods are based on explainable deep learning approaches, considering Convolutional Neural Networks and Transformers. Their features are extracted using GradCam and attention scores, respectively. The performance of the extracted features is compared to established feature selection approaches across four classifiers and three datasets. Results: We compared the proposed method against established feature selection approaches over three real-world datasets and different compression levels. Comparable accuracy levels were obtained using only 10% of features. Model-based approaches are the most accurate. Using Convolutional Neural Networks and Random Forest-assigned feature importance performs best when maintaining between 5–20% of features, while LinearSVC with L1 penalisation leads to higher accuracy when selecting only 1% of them. The proposed Convolutional Neural Networks-based GradCam approach has the highest average accuracy. Conclusions: No approach is found to perform best in all scenarios, suggesting that multiple alternatives should be assessed in each application. Full article

Organic photodetectors (OPDs) offer considerable promise for low-power, solution-processable biosensing and imaging applications; however, their performance remains limited by spectral mismatch and interfacial trap states. In this study, a highly sensitive polymer photodiode was developed via trace incorporation (0.8 wt%) of InP/ZnSe/ZnS quantum dots (QDs) into a PTB7-Th:PC₇₁BM bulk heterojunction (BHJ) matrix. This QD doping approach enhanced the external quantum efficiency (EQE) across the 540–660 nm range and suppressed the dark current density at −2 V by passivating interface trap states. Despite a slight decrease in optical absorption at the optimized composition, the internal quantum efficiency (IQE) increased significantly from ~80% to nearly 95% resulting in a net EQE improvement. This suggests that QD incorporation improved charge transport without compromising charge separation efficiency. As a result, the device achieved a specific detectivity (D*) of 1.8 × 10¹³ Jones, representing a 93% improvement over binary BHJs, along with an ultra-low dark current density of 7.76 × 10⁻¹⁰ A/cm². Excessive QD loading, however, led to optical losses and increased dark current, underscoring the need for precise compositional control. Furthermore, the enhanced detectivity led to a 4 dB improvement in the signal-to-noise ratio (SNR) of photoplethysmography (PPG) signals in the target wavelength range, enabling more reliable biophotonic sensing without increased power consumption. This work demonstrates that QD-based spectral and interfacial engineering offers an effective and scalable route for advancing the performance of OPDs, with broad applicability to low-power biosensors and high-resolution polymer–QD imaging systems. Full article

Polymerization shrinkage in resin-based composites can lead to gap formation at the tooth–restoration interface, potentially compromising the long-term success of restorations. Bulk-fill composites have been developed to reduce shrinkage stress, but their adaptation and bond strength—especially in deep cavities—remain areas of concern. This study investigated the adaptation and bond strength of a newly developed dual-cure bulk-fill composite in 4 mm deep preparations compared to light-cured and self-adhesive bulk-fill composites in six groups. Standard composite molds were used to observe and measure sealed floor area (SFA%) of the composite after the polymerization process under optical coherence tomography (OCT) imaging. Micro-tensile bond strength (MTBS) testing was conducted in extracted human teeth. OCT showed that the prototype dual-cure composites had the lowest gap formation during polymerization (SFA 91%), while the self-adhesive composite demonstrated the highest debonding from the cavity floor (SFA 26%, p < 0.001). For MTBS analysis, the lowest mean bond strength was recorded for the self-adhesive composite (~21 MPa) and the highest for a light-cured bulk-fill (~50 MPa, p < 0.05). Overall, the dual-cure bulk-fill composites exhibited less gap formation than the light-cured ones. The prototype dual-cure material with 90 s waiting before light-curing showed the best adaptation. However, these differences were not reflected in the bond strength values to the cavity floor dentin using the universal adhesive used in the current study, as the light-cured composite showed the highest bond strength values. The self-adhesive composite showed the poorest results in both experiments, indicating that the application of a bonding system is still necessary for better adaptation and bonding to the cavity floor dentin. Full article

The evidence for photobiomodulation in reducing postoperative pain after endodontic instrumentation is classified as low or very low certainty, indicating a need for further research. Longitudinal pain assessments over 24 h are crucial, and studies should explore these pain periods. Background/Objectives: This double-blind, randomized controlled clinical trial evaluated the effect of PBM on pain following single-visit endodontic treatment of maxillary molars at 4, 8, 12, and 24 h. Primary outcomes included pain at 24 h; secondary outcomes included pain at 4, 8, and 12 h, pain during palpation/percussion, OHIP-14 analysis, and frequencies of pain. Methods: Approved by the Research Ethics Committee (5.598.290) and registered in Clinical Trials (NCT06253767), the study recruited adults (21–70 years) requiring endodontic treatment in maxillary molars. Fifty-eight molars were randomly assigned to two groups: the PBM Group (n = 29), receiving conventional endodontic treatment with PBM (100 mW, 333 mW/cm², 9 J distributed at 3 points near root apices), and the control group (n = 29), receiving conventional treatment with PBM simulation. Pain was assessed using the Visual Analog Scale. Results: Statistical analyses used chi-square and Mann–Whitney tests, with explained variance (η²). Ten participants were excluded, leaving 48 patients for analysis. No significant differences were observed in postoperative pain at 24, 4, 8, or 12 h, or in palpation/percussion or OHIP-14 scores. Pain frequencies ranged from 12.5% to 25%. Conclusions: PBM does not influence post-treatment pain in maxillary molars under these conditions. These results emphasize the importance of relying on well-designed clinical trials to guide treatment decisions, and future research should focus on personalized dosimetry adapted to the anatomical characteristics of the treated dental region to enhance the accuracy and efficacy of therapeutic protocols. Full article

Background/Objectives: Doxorubicin (DOX), a widely used anthracycline chemotherapeutic agent, is recognized for its efficacy in treating various malignancies. However, its clinical application is critically limited due to dose-dependent cardiotoxicity, predominantly induced by oxidative stress and compromised antioxidant defenses. Photobiomodulation (PBM), a non-invasive intervention that utilizes low-intensity light, has emerged as a promising therapeutic modality in regenerative medicine, demonstrating benefits such as enhanced tissue repair, reduced inflammation, and protection against oxidative damage. This investigation sought to evaluate the cardioprotective effects of PBM preconditioning in human-induced pluripotent stem cell-derived ventricular cardiomyocytes (hiPSC-vCMs) subjected to DOX-induced toxicity. Methods: Human iPSC-vCMs were allocated into three experimental groups: control cells (untreated), DOX-treated cells (exposed to 2 μM DOX for 24 h), and PBM+DOX-treated cells (preconditioned with PBM, utilizing 660 nm ±10 nm LED light at an intensity of 10 mW/cm² for 500 s, delivering an energy dose of 5 J/cm², followed by DOX exposure). Cell viability assessments were conducted in conjunction with evaluations of oxidative stress markers, including antioxidant enzyme activities and malondialdehyde (MDA) levels. Furthermore, transcriptional profiling of 40 genes implicated in cardiac dysfunction was performed using TaqMan quantitative polymerase chain reaction (qPCR), complemented by analyses of protein expression for markers of cardiac stress, inflammation, and apoptosis. Results: Exposure to DOX markedly reduced the viability of hiPSC-vCMs. The cells exhibited significant alterations in the expression of 32 out of 40 genes (80%) after DOX exposure, reflecting the upregulation of markers associated with apoptosis, inflammation, and adverse cardiac remodeling. PBM preconditioning partially restored the cell viability, modulating the expression of 20 genes (50%), effectively counteracting a substantial proportion of the dysregulation induced by DOX. Notably, PBM enhanced the expression of genes responsible for antioxidant defense, augmented antioxidant enzyme activity, and reduced oxidative stress indicators such as MDA levels. Additional benefits included downregulating stress-related mRNA markers (HSP1A1 and TNC) and apoptotic markers (BAX and TP53). PBM also demonstrated gene reprogramming effects in ventricular cells, encompassing regulatory changes in NPPA, NPPB, and MYH6. PBM reduced the protein expression levels of IL-6, TNF, and apoptotic markers in alignment with their corresponding mRNA expression profiles. Notably, PBM preconditioning showed a diminished expression of BNP, emphasizing its positive impact on mitigating cardiac stress. Conclusions: This study demonstrates that PBM preconditioning is an effective strategy for reducing DOX-induced chemotherapy-related cardiotoxicity by enhancing cell viability and modulating signaling pathways associated with oxidative stress, as well as inflammatory and hypertrophic markers. Full article

Background/Objectives This systematic review and network meta-analysis aimed to determine the most effective therapeutic exercise modality for improving quality of life (QoL) in patients with advanced-stage cancer. Specifically, the study compared the effects of aerobic training, strength training, and combined aerobic and strength training on QoL outcomes. Methods A systematic literature search was conducted in PubMed, Embase, Cochrane Reviews, and the Cochrane Central Register of Controlled Trials up to 24 February 2023. The review adhered to PRISMA guidelines. Included studies were randomized controlled trials (RCTs) involving adult patients with advanced-stage cancers (e.g., pancreatic, colorectal, lung, breast, prostate, gastrointestinal, gynecological, hematological, head and neck, melanoma, or cancers with bone metastases). The primary outcome was post-intervention QoL, while the secondary outcome assessed was the dropout rate across exercise modalities. Results Aerobic training demonstrated the greatest improvement in QoL with a standardized mean difference (SMD) of 0.30 (95% CI: 0.00 to 0.61), followed by strength training (SMD = 0.13; 95% CI: −0.41 to 0.66) and combined training (SMD = 0.07; 95% CI: −0.11 to 0.24). However, none of the interventions showed statistically significant superiority. Dropout rates were comparable across all exercise modalities and control groups, suggesting strong adherence and feasibility of these interventions in advanced cancer populations. Conclusions While all exercise modalities were associated with improved QoL in patients with advanced-stage cancer, no single intervention emerged as significantly superior. Aerobic exercise may offer a slight advantage, although this effect was not statistically significant. These results highlight the importance of individualized exercise prescriptions based on patient preference, functional status, and treatment context. Further research is warranted to identify patient subgroups that may benefit most from specific exercise interventions and to explore QoL subdomains such as fatigue, emotional well-being, and physical functioning. Full article

A conventional microchannel plate framing camera is typically utilized for inertial confinement fusion diagnosis. However, as a vacuum electronic device, it has inherent limitations, such as a complex structure and the inability to achieve single-line-of-sight imaging. To address these challenges, a CMOS image sensor that can be seamlessly integrated with an electronic pulse broadening system can provide a viable alternative to the microchannel plate detector. This paper introduces the design of an 8 × 8 pixel-array ultrashort shutter-time single-framing CMOS image sensor, which leverages silicon epitaxial processing and a 0.18 μm standard CMOS process. The focus of this study is on the photodiode and the readout pixel-array circuit. The photodiode, designed using the silicon epitaxial process, achieves a quantum efficiency exceeding 30% in the visible light band at a bias voltage of 1.8 V, with a temporal resolution greater than 200 ps for visible light. The readout pixel-array circuit, which is based on the 0.18 μm standard CMOS process, incorporates 5T structure pixel units, voltage-controlled delayers, clock trees, and row-column decoding and scanning circuits. Simulations of the pixel circuit demonstrate an optimal temporal resolution of 60 ps. Under the shutter condition with the best temporal resolution, the maximum output swing of the pixel circuit is 448 mV, and the output noise is 77.47 μV, resulting in a dynamic range of 75.2 dB for the pixel circuit; the small-signal responsivity is 1.93 × 10⁻⁷ V/e⁻, and the full-well capacity is 2.3 Me⁻. The maximum power consumption of the 8 × 8 pixel-array and its control circuits is 0.35 mW. Considering both the photodiode and the pixel circuit, the proposed CMOS image sensor achieves a temporal resolution better than 209 ps. Full article

Background: Docetaxel (Doc) resistance in prostate cancer (CaP) patients is associated with the secretion of proinflammatory cytokines that induce an interaction between tumor cells and macrophages. Tumor cell-derived cytokines released in response to increased intracellular concentrations of Doc attract monocytes and macrophages to the tumor site and induce Doc resistance. Objectives: To generate Doc-resistant CaP cell line LNCaP-Doc/R and determine if we could modulate/reduce proinflammatory signals by administering Doc, encapsulated in a PLGA: Chitosan core-shell hierarchical nanoparticle (HNP-Doc) in the resistant and naive CaP Cells. Methods: LNCaP-Doc/R cells were generated by intermittent increasing concentration of Doc, proliferation, growth curve and cytotoxicity of Doc and HNP-Doc were evaluated followed by LNCaP and LNCaP-Doc/R (Doc resistant) CaP cells co-cultured with U937 monocytes with either free Doc or HNP-Doc encapsulated Doc, and various cytokine levels were measured in the conditioned media to assess the cytokine levels. Results: Our results show that LNCaP-Doc-R cells had slower growth in the lag phase, needed a 90-fold increase in Doc concentration to achieve 50% killing. Basal levels of cytokines secreted by LNCaP and LNCaP-Doc/R cells in response to free Doc and HNP-encapsulated Doc differed considerably, with free Doc-treated cells demonstrating, on average, 2–7-fold higher pro-inflammatory cytokine levels as compared to HNP-encapsulated Doc. The levels of pro-inflammatory cytokines, such as IFNγ, IL-1α, and RANTES, were increased ~2.38, ~2.75, and ~5.75-fold, respectively, in free Doc-treated CaP cells and were significantly lower when Doc was delivered via HNP. Further, LNCaP-Doc/R cells co-cultured with U937 had significantly lower markers of macrophage differentiation in response to HNP-encapsulated Doc treatment as opposed to free Doc treatment. Conclusions: Based on this analysis, we conclude that Doc treatment in vitro is associated with a proinflammatory response involving cytokines linked to macrophage recruitment and activation, with a lesser proinflammatory response with HNP-encapsulated Doc treatment. Full article

Coherent anti-Stokes Raman scattering (CARS) is a powerful nonlinear spectroscopic technique widely used in biological imaging, chemical analysis, and combustion and flame diagnostics. The adoption of pulse shapers in CARS has emerged as a useful approach, offering precise control of optical waveforms. By tailoring the phase, amplitude, and polarization of laser pulses, the pulse shaping approach enables selective excitation, spectral resolution improvement, and non-resonant background suppression in CARS. This paper presents a comprehensive review of applying pulse shaping techniques in CARS spectroscopy for biophotonics. There are two different pulse shaping strategies: passive pulse shaping and active pulse shaping. Two passive pulse shaping techniques, hybrid CARS and spectral focusing CARS, are reviewed. Active pulse shaping using a programmable pulse shaper such as spatial light modulator (SLM) is discussed for CARS spectroscopy. Combining active pulse shaping and passive shaping, optimizing CARS with acousto-optic programmable dispersive filters (AOPDFs) is discussed and illustrated with experimental examples conducted in the authors’ laboratory. These results underscore pulse shapers in advancing CARS technology, enabling improved sensitivity, specificity, and broader applications across diverse scientific fields. Full article

Given the high cost and limited availability of noble-metal-based catalysts in acidic media water electrolysis, developing cost-effective and high-performance non-noble metal catalysts is crucial for realizing large-scale hydrogen production. In this study, Fe-, Co-, and Ni-doped MoSe₂ nanomaterials were synthesized via chemical vapor deposition, and their electrocatalytic performance for the hydrogen evolution reaction (HER) was systematically evaluated. Characterization techniques including X-ray diffraction, X-ray photoelectron spectroscopy, transmission electron microscopy, scanning electron microscopy, and Raman spectroscopy were used to confirm the incorporation of doping elements and investigate their effects on the crystal structure and morphology of MoSe₂. Electrochemical tests, including linear sweep voltammetry and cyclic voltammetry, revealed that the doping of Fe, Co, and Ni significantly enhanced the HER catalytic activity of MoSe₂, with the Co-doped sample exhibiting the best performance, showing an overpotential of 0.293 V at 100 mA/cm⁻² and a Tafel slope of 47 mV/dec. Furthermore, density functional theory calculations were employed to analyze the adsorption energy of hydrogen atoms on the catalysts, providing deeper insights into the role of doping in tuning the catalytic activity of MoSe₂. This study offers new theoretical support and experimental evidence for the application of transition metal-doped MoSe₂ in electrocatalysis. Full article

KIF1A is a neuron-specific kinesin motor responsible for intracellular transport along axons. Pathogenic KIF1A mutations cause KIF1A-associated neurological disorders (KAND), a spectrum of severe neurodevelopmental and neurodegenerative conditions. While individual KIF1A mutations have been studied, how different substitutions at the same residue affect motor function and disease progression remains unclear. Here, we systematically examine the molecular and clinical consequences of mutations at three key motor domain residues—R216, R254, and R307—using single-molecule motility assays and genotype–phenotype associations. We find that different substitutions at the same residue produce distinct molecular phenotypes, and that homodimeric mutant motor properties correlate with developmental outcomes. In addition, we present the first analysis of heterodimeric KIF1A motors—mimicking the heterozygous context in patients—and demonstrate that while heterodimers retain substantial motility, their properties are less predictive of clinical severity than homodimers. These results highlight the finely tuned mechanochemical properties of KIF1A and suggest that dysfunctional homodimers may disproportionately drive the diverse clinical phenotypes observed in KAND. By establishing residue-specific genotype–phenotype relationships, this work provides fundamental insights into KAND pathogenesis and informs targeted therapeutic strategies. Full article

We explore quantum well laser diodes for applications in pulse oximetry based on two material systems, namely, classical AlGaAs and a rather exotic GaAsBi, with lasing at around 800 nm and 1100 nm, respectively. These spectral regions and material families were selected due to their closely matched effective penetration depths into soft tissue. An improved design of the band structure of device active areas was tested on both material systems, yielding enhancement of the two main parameters, namely, output power and threshold current. A maximum emission power of the AlGaAs laser diode was registered at 4.9 mW (I = 60 mA, λ = 801 nm). For the GaAsBi-based devices, the target emission of 1106 nm was measured in pulsed mode with a peak output power of 9.4 mW (I = 3 A). The most optimized structure was based on three GaAsBi quantum wells surrounded by parabolically graded AlGaAs barriers. This structure was capable of 130 mW peak power (I = 2 A, λ = 1025 nm) along with a more than tenfold decrease in threshold current to 250 mA compared to a classical rectangular quantum well active region. Full article