Combining bioluminescent sensors and isothermal amplification enables fast and simple nucleic acid diagnostics, holding great potential for point-of-care applications. We previously developed the LUNAS (luminescent nucleic acid sensor) platform, which integrates recombinase polymerase amplification (RPA) with a clustered regularly interspaced short palindromic repeats (CRISPR) dCas9-mediated bioluminescent readout. Here, we extend LUNAS into a multiplex platform through the development of green- and red-light emitting LUNAS variants. These color variants can be integrated with duplex RPA for amplification and orthogonal detection of two DNA targets in a single reaction, without compromising sensitivity or reaction speed. Using this approach, we developed a duplex assay for the sexually transmitted infections gonorrhea and chlamydia, with attomolar sensitivity and a robust ratiometric readout. Using a simple digital camera, multicolor LUNAS enabled detection of bacterial DNA from clinical samples with loads down to ∼100 copies/μL and within ∼30 min, demonstrating its diagnostic performance for low-resource applications.

Organised meteor observations in Poland began in 1925. For many years, amateur astronomers observed these phenomena using visual methods. They were mainly members of the Polish Amateur Astronomical Society. Since the beginning of the 21st century, observations using cameras and digital cameras have been introduced. Networks of fireball stations were also established, making it possible to determine the locations where meteorites fall.

Background: There is a widespread use of dental digital photography in the current practice of dentistry as a means of diagnosing and documenting, as well as communicating with the patient and conducting research. The developments and advancements in the technologies of camera, AI, and digital workflows have increased their usage in various specialities. Aim: This article is a review of the principles, equipment, protocols, ethical and future aspects of dental digital photography. Methods: A wide range of literature reviews has been done over the period of the last 25 years as given from 1997 to 2025, on the basis of PubMed, Scopus, and Google Scholar. Critical evaluation was done of the articles on the principles, equipment, clinical applications, and innovations of dental photography. Findings: Dental digital photography necessitates standard protocols: ideally, camera settings, lighting system and accessories to obtain reproducible and high-quality dental digital images. Its uses are applied in the field of prosthodontics, orthodontics, periodontics, forensic dentistry, and oral surgery. New technologies like smartphone imaging, artificial intelligence, 3D photogrammetry and augmented reality are contributing to precision and patient-centred care. The considerations of legal, ethical and consent are vital in clinical application. Conclusion: Digital photography in the dental practice is a built-in clinical process that is used to improve patient communication, as well as bolster medico-legal healthcare records. With ongoing advances in AI and advances in imaging technology, it is on the verge of changing dentistry through diagnosis, treatment planning and learning.

Background: Virdentopsy is a dental-focused extension of virtopsy that enables remote collection, transmission, and expert interpretation of post-mortem dental data when on-site forensic odontologists are unavailable. Objective: This narrative review summarizes the current concepts, workflow, advantages, limitations, and implementation barriers of virdentopsy in forensic odontology and disaster victim identification (DVI). Review Approach: Relevant literature on virtopsy, virdentopsy, teledentistry, forensic imaging, and digital dental identification published up to 2025 was narratively reviewed from major biomedical and forensic sources. Because this is a narrative review, no formal quality-scoring tool or quantitative meta-analysis was applied. Results: The available literature shows that remote dental evaluation can be supported by grouped digital inputs, including imaging (intraoral radiographs, panoramic imaging, CT/CBCT), photography (2D intraoral and extraoral images), scanning (photogrammetry, intraoral scanning, 3D surface capture), and communication tools (video review and live streaming). These methods can strengthen documentation, facilitate remote expert consultation, and support humanitarian identification work. However, the evidence remains heterogeneous and is limited by variable infrastructure, image quality, chain-of-custody requirements, and uneven legal readiness across jurisdictions. Conclusion: Virdentopsy is a promising but still evolving forensic workflow. It is best viewed as an adjunct to established dental autopsy practice rather than a universal replacement. Standardized capture protocols, secure data transfer, training, and validation studies are required before broad routine implementation.

ABSTRACT Aims To evaluate whether landmarks used to measure digital phalanx bone development using micro-CT could be used to measure bone development in digital photographs, and the association in pasture-based cows, between bone development, age and lameness history. Methods 160 distal phalanges (from the hind feet of 40 cows) were collected post-mortem, photographed, and measured at four sites (A–D) near the flexor tuberosity. Associations between age and lameness history, and the average sum of A–D for the two lateral and two medial claws within a cow (BD-Ave) and the highest sum of A–D for an individual claw (BD-Max) were modelled. Results Median age of enrolled cows was 8 (min 3, max 12) years and 34/40 had a history of lameness in the lactation before culling. Only minor modifications to the measurement landmarks were needed to account for the differences between micro-CT scans and digital photographs. Age was associated with BD-Max and BD-Ave: a 1-year increase in age increased geometric mean BD-Max by 1.12 (95% CI = 1.03–1.21) times and geometric mean BD-Ave by 1.09 (95% CI = 1.04–1.14) times. Prior lameness was compatible with an increase and decrease in geometric mean BD-Max and BD-Ave. Compared to cows with no history of lameness in the previous lactation, for previously lame cows, BD-Max was 1.61 (95% CI = 0.88–2.95) and BD-Ave, 1.25 (95% CI = 0.89–1.78) times greater, equivalent to a 5- and 3-year age effect, respectively. Most of the measurement differences between claws were in D (abaxial caudal bone development), as 136/160 claws recorded zero for A, B and C but all claws had values > 0 mm for D. In all claws where only D was > 0 mm, bone development was smooth. In these claws, an additional year in age increased D measurements by 1.09 (95% CI = 1.05–1.11) times – similar to the effect on BD-Max, while the effect on the sum of the remaining measurements was compatible with both a moderate increase or decrease. These observations indicate the principal effect of age was on measurement D. Conclusions Photography may provide an economical alternative to micro-CT for studying digital phalanx bone development in ex-vivo samples. Our data suggest lameness and age may affect bone development in pasture-based cows. However, these are preliminary data; further research is needed comparing CT and photography measurements, and to better understand the association between age, lameness and bone development in pasture-based dairy cows.

Diabetic foot ulcers, resulting from neuropathic and/or vascular complications in patients with diabetes mellitus, pose a major global health challenge. Early detection and consistent monitoring of wound progression are essential for timely intervention, effective treatment, and the prevention of severe complications such as amputation. In modern diabetic foot care, images captured using digital cameras and mobile phones are increasingly employed for remote wound assessment. In this context, automated segmentation of these wounds from such images plays a vital role by enabling objective and quantitative evaluation of wound areas-crucial for tracking the progression of healing over time. Recent years have witnessed growing interest in deep learning-based wound segmentation techniques, with a particular focus on models that are both computationally efficient and suitable for deployment on resource-constrained devices, including smartphones and point-of-care platforms. In this study, we propose a lightweight convolutional neural network (CNN) for diabetic foot wound segmentation that augments the U-Net architecture with ghost feature generation and Convolutional Block Attention Modules (CBAM) to improve computational efficiency and feature representation. The model was evaluated on a privately annotated dataset of 3450 diabetic foot wound images and compared against state-of-the-art architectures, including SegNet, U-Net, MobileNetV2, Mask R-CNN, and the domain-specific approach of Wang et al. We further investigated a fully automated two-step pipeline for wound segmentation incorporating a prior foot segmentation-based ROI detection. Using ROI detection, the proposed CNN achieved a precision of 85.13%, recall of 91.84%, Dice coefficient of 86.95%, and IoU of 77.23%. These results demonstrate competitive performance relative to high-capacity models while maintaining substantially reduced computational complexity, highlighting its suitability for real-time clinical deployment in low-resource environments.

In the Arctic region, a decline in ice and snow cover has been observed in recent years, resulting in adverse effects on the climate, hydrological events, biological processes, and human populations. Monitoring changes in ice and snow cover using satellite imagery or models is common, while novel research is beginning to use ground-based camera systems for in situ monitoring of cryosphere elements. This study focused on maximizing the usage of ground-based time-lapse imagery from trail cameras for ice and snow studies from 2016-2022 within the context of the changing Arctic climate by monitoring lake ice and snow at five lakes (Resolute Lake, Small Lake, North Lake, Plateau Lake, and Hunting Camp Lake) near Resolute and Nanuit Itillinga, Nunavut, in the Central Canadian High Arctic. A semi-automated technique using image classification tools was developed to quantify the progression of ice and snow extent in the camera view. The image classification yielded an overall classification accuracy of 86%, and a Kappa coefficient of 0.79 from nearly 13 000 images, indicating a strong and viable monitoring system despite some variance in performance from viewing conditions. Lake ice and snow phenology dates determined from classified imagery had averages generally within a few days of observations (mean bias error of 2-9 days). Average ice duration was 308 days (September 20 to July 25), and average snow duration was 298 days (September 14 to July 8). The camera-based data extraction technique is a viable tool, not only for tracking long-term changes in snow/ice conditions, but also for validating satellite or modelling work in other logistically challenging environments. Thus, this methodology to monitor Arctic ice and snow phenology can support better projections for future responses to climate change.

This systematic review critically examines the use of 2D and 3D digital imaging technologies of the face and teeth, with and without integration of artificial intelligence, for human identification in forensic and medicolegal contexts. Following PRISMA 2020 guidelines, Scopus, PubMed and Web of Science were systematically searched, identifying 26 studies published between 2011 and 2025 that met predefined eligibility criteria framed by a PECO-style question. Eighteen studies focused on facial imaging, six on dental imaging and two on integrated orofacial workflows, using digital photography, CCTV/video, 3D surface imaging, intraoral scanners, and three-dimensional superimposition methods, sometimes combined with classical algorithms and deep learning models. In controlled or semi-controlled settings, state-of-the-art facial algorithms often reported very high accuracy, with values up to 99.85%. By contrast, studies using real CCTV or other challenging forensic imagery showed more variable performance, with accuracies ranging from about 72.8% to 96.6%. Dental and orofacial studies reported 100% correct identifications for 3D superimposition of intraoral scans in small samples, and around 83% accuracy for automated AI-based dental identification. Crucially, fulfilling the promise of a true orofacial approach, this review proposes a structured research agenda focused on creating realistic multi-modal databases, standardizing protocols, and implementing probabilistic reporting (likelihood ratios) to guide future validation and legal admissibility.

To accurately assess the corrosion degree of bronze artefacts, this article quantitatively characterises the corrosion of bronze artefacts using the entropy-weighted grey correlation method, which is of great significance for formulating effective surface corrosion assessment strategies for artefacts. In this work, the corroded areas of the artefacts were observed using an Ultra-deep field microscope and photographed with a digital camera. A schematic diagram of the corrosion on the bronzes was drawn using Adobe Photoshop software for subsequent entropy correlation sorting as a comparative analysis. To obtain evaluation data, the surface corrosion products of 64 bronze artefacts from the Jingmen City Museum collection were tested using energy-dispersive spectrometer. Finally, a quantitative relationship between the elemental composition of corrosion products on the surface of bronzes and their level of corrosion was established using the entropy-weighted grey correlation method. The results show that the influence of each index is ranked in order of importance as the ratio of chlorine to metal elements, the ratio of oxygen-to-metal ratio, S, Pb, Sn, and Cu, among which the ratios of chlorine to metal elements, the ratios of oxygen-to-metal ratio, and the S element have a greater correlation with the degree of corrosion of bronzes. The study also integrates the entropy-weighted grey correlation analysis results with the macroscopic characteristics and microscopic morphological analysis of the samples, validating the effectiveness of the weighted grey correlation method in grading the degree of corrosion in bronzes. This approach offers a novel method for quantitatively measuring bronze corrosion.

Although the Tajima overcorrection technique is used in primary rhinoplasty procedures at our institution, we have observed a recurring asymmetry problem in patients who undergo such procedures at around the age of approximately 1. Notably, this asymmetry appears to be minor and remains stable over time. The current study is a longitudinal analysis of outcomes following primary overcorrected rhinoplasty and provides insights into the long-term trajectory of nasal morphology after treatment. This retrospective study examined a cohort of 146 patients with a nonsyndromic unilateral cleft lip who underwent cheiloplasty with primary Tajima overcorrected rhinoplasty at the Chang Gung Memorial Hospital Craniofacial Center between 2002 and 2003. A longitudinal analysis of nostril morphology was conducted using a series of digital photographs taken at five time points: 1 (T1), 5 (T2), 10 (T3), 15 (T4), and 18 (T5) years of age. Symmetry was assessed using anthropometric measurements, including nostril height, nostril base height, nostril width, nasal width and columella angle. Nostril asymmetry improved over time among both patients with a complete and incomplete unilateral cleft lip. Nostril height, nostril width, nasal width and columella angle significantly varied with time (P < 0.01), whereas nostril base height remained stable. Achieving adequate cleft-side nasal height during primary procedures is crucial. The current results can provide valuable guidance for surgeons regarding the optimal timing for secondary rhinoplasty, particularly in cases where primary outcomes are suboptimal.

Hard-to-heal (chronic) wounds in patients with diabetes represent a considerable, difficult-to-manage burden, and significantly increase the risk of amputations of lower extremities. These lesions are often accompanied by infections. Novel therapeutic approaches are urgently needed in the field of wound management. Cold atmospheric plasma (CAP) is a promising tool in the management of hard-to-heal wounds. Its beneficial use can be attributed to the reduction of bacterial load and direct stimulation of tissue regeneration. The effectiveness of different CAP devices for the treatment of hard-to-heal wounds is well documented by clinical case series and randomised controlled studies. The aim of this prospective, observational study was to investigate the bacterial load and composition in hard-to-heal wounds following CAP treatment, and the impact on long-term wound healing outcome. A total of 22 patients were included in the study. All wounds were exposed to the argon-driven CAP jet kINPen Med (neoplas med GmbH, Germany), in addition to standard phase-adapted wound care. A digital wound camera monitored wound area development over time, while swab tests monitored bacterial colonisation. The results showed that CAP application significantly reduced the bacterial burden almost immediately, although this reduction was not maintained. The analysis revealed a better healing tendency when wounds were colonised by Gram-positive bacteria as opposed to Gram-negative bacteria. Moreover, a higher susceptibility of Gram-negative bacteria to the CAP jet was detected. In conclusion, the bacterial composition of wounds might affect the healing outcome during CAP therapy.

Two-month outcomes of advanced pneumatic compression device (APCD) and usual care (UC) in Head and Neck Cancer survivors with previously untreated lymphedema were compared. Participants in this multisite, randomized clinical trial were randomized to APCD or UC. The primary endpoint was severity of lymphedema symptoms. Secondary endpoints were anatomical lymphedema changes, biopsychosocial outcomes, and barriers to care. Two hundred thirty-six participants were enrolled (119 APCD, 117 UC). Analysis was intention-to-treat. Lymphedema-associated symptom burden measured using the VHNSS and LSIDS was improved to a similar degree in both groups. APCD demonstrated a statistically significant improvement in external soft tissue swelling assessed by digital photography. No difference in CT imaging measures of lymphedema was noted. UC participants experienced barriers to care. APCD is an effective treatment for lymphedema in HNCS. The APCD addresses clinically significant barriers to therapist guided treatment. A hybrid approach may be complementary and optimize patient outcomes. NCT04797390.

Buffalo fly (Haematobia irritans exigua) is recognised for its impact on cattle health, welfare, and production. It is ranked the number one endemic pest for the Australian beef cattle industry by Meat and Livestock Australia. An accurate estimation of fly numbers is essential to evaluate treatment efficacy, phenotyping of susceptible animals for genetic improvement and determining threshold levels to guide integrated pest management strategies. Traditionally, fly numbers are estimated through visual scoring which is inherently challenging as it involves estimating moving flies on a restless host. This study used digital photography and an open-source, semi-automated software package DotDotGoose to count fly numbers on individual animal images. These were then compared to the visual fly scores on the same animals. A random selection of 98 images was used and fly numbers were counted on these images in duplicate by four assessors, one experienced field researcher and three novice assessors. The fly counts on individual images were analysed for consistency and agreement and a consistency and agreement of 99 % was achieved within the four assessors, classified as excellent. The analysis further showed that visual assessments and manual visual counts by experienced assessors consistently underestimated fly numbers compared to the digital image counts. Our results suggest that a digital counting platform offers a more reliable alternative to visual scoring for buffalo fly counts. It improves accuracy and consistency and enables remote image analysis, lowers time and labour costs, and provides the potential for automated real-time monitoring and reporting of fly numbers.

Anatomical photographs are essential in medical education and research as they document fine details of human anatomy. which may support visualization of dissection material. This study investigated the feasibility of an artificial intelligence (AI)-based image enhancement system for anatomical dissection photographs and explored whether subtle visual differences could be detected under magnification. A dataset of 50 anatomical photographs taken between 2001 and 2024 with four different digital cameras was processed using Upscayl (v2.11.5) with the preset "16× REAL-ESRGAN." Processing was performed on a Casper Excalibur G770 laptop, requiring approximately 3-5 min per image. Original and enhanced images were compared at magnifications of 1×, 5×, 10×, 15×, and 20× on a 55-in. Full HD display. Forty experts, including neuroanatomists and neurosurgeons, qualitatively assessed the images with respect to anatomical accuracy, noise reduction, edge definition, and training value. The visual differences between the original and enhanced images were generally subtle. However, subtle improvements in edge definition and noise reduction became more apparent in deep anatomical regions, such as ventricular cavities, particularly at higher magnification levels. High-resolution images showed limited observable differences, whereas lower-resolution images exhibited slightly more noticeable changes under magnification. The enhancement process did not introduce distortions of anatomical structures. A key limitation was the substantial increase in file size after enhancement. AI-based image enhancement appears feasible for anatomical dissection photographs and may provide modest visual benefits in selected settings, especially for older or lower-resolution images viewed at higher magnification. Further optimization is required to reduce file size and processing time before routine educational or publication use.

Towards sustainable management of Xylella fastidiosa vectors: An annotated image dataset for automated in-field detection of Aphrophoridae foam.

AI-powered detection of dental anatomy: a YOLO-based approach.

Alginate hydrogel film reinforced with Fe3O4@SiO2/Schiff-base/Cu(II) nanoparticles in promoting diabetic wound healing.

Background/Objectives: Accurate and reproducible wound measurement is essential for monitoring healing and guiding treatment decisions. Conventional ruler-based techniques are prone to geometric overestimation and operator variability. This study evaluated the accuracy and reproducibility of the MolecuLightDX wound imaging device for measuring wound surface area and depth compared with ruler-based measurements and ground truth digital photography methods. Methods: This investigation comprised two companion studies: a prospective, paired, multicenter clinical study comparing MolecuLightDX measurement with the ruler method against an image-based ground truth, and a bench and clinical validation of the AutoDepth feature against a calibrated three-dimensional optical scanner. The area of study included 17 benchtop wound models and enrolled 27 patients (33 wounds; area range: 0.56-23.04 cm2) across two wound care centers, and the AutoDepth study included 17 benchtop wound models and 34 clinical wounds (depth range: 0.06-4.13 cm). Accuracy, intra- and inter-user variability, and agreement were assessed using the mean percentage error (MPE), coefficient of variation (CV), intraclass correlation coefficients (ICC), and Bland-Altman analysis. Results: The device demonstrated high accuracy and reproducibility for both wound surface area and depth measurements compared with ruler-based and ground truth digital photography methods. The MPE for surface area was <10%, representing a tenfold improvement over ruler estimation (77.9%). For wound area, intra- and inter-user CVs were <10%, and for depth, ICCs were ≈0.99. Conclusions: The MolecuLightDX device provides accurate and consistent wound area and depth measurements across diverse wound types, demonstrating superior accuracy and reproducibility compared with conventional ruler-based methods and supporting its integration into wound assessment workflows.

Monitoring seasonal grass cover dynamics in a multi-use savanna rangeland is important for sustaining the coexistence of livestock and wildlife. Moreover, population growth is driving increased livestock production, which further limits resources for both livestock and wildlife. To better understand the effect of grazing on grass cover dynamics, we developed a multi-scale remote sensing approach to study the monthly variation in grass cover in two types of conservation areas: a wildlife sanctuary and a communal livestock grazing and wildlife conservancy. The study was carried out in a semi-arid region in Kenya during an exceptionally dry year of 2022 when grazing resources were limited. The Excess Greenness color index was first used to develop a model predicting green fractional vegetation cover (fCover) of field photographs. This model was then applied to upscale fCover to the landscape level using very-high-resolution Pléiades satellite data. The resulting fCover maps were subsequently used to predict grass cover from medium-resolution Sentinel-2 multispectral satellite imagery using Random Forest machine learning. The final model showed high predictive power of grass cover in May (R 2 = 0.96, root mean square error (RMSE) = 4.95%), while predictions were less accurate yet promising for January (R 2 = 0.67, RMSE = 7.1%). The monthly grass cover maps demonstrate differences between the two conservation areas; the grazing area experienced low grass cover throughout the year, whereas grass cover in the wildlife sanctuary was more driven by rainfall. The results demonstrate the usability of digital cameras as the basis for vegetation cover models. Furthermore, this method can be used for adaptive land management to monitor within-season resources for both livestock and wildlife. • Fractional grass cover can be upscaled from field to regional levels • Training data from one month was used to predict monthly variations in grass cover • Areas with higher grazing pressure had lower grass cover throughout the year • The wildlife sanctuary experienced a more natural fluctuation in grass cover

During the current study, the causes, impacts, and mitigation efforts related to Glacial Lake Outburst Floods (GLOFs) in Bilhanz and Badswat, Ishkoman Valley, were thoroughly examined between July to September 2024. These events led to significant landscape alterations, transforming once fertile agricultural and forest lands into debris covered areas, as evidenced by satellite and digital camera imagery. A large lake formed in Badswat, destroying extensive agricultural and forest land, which forced the relocation of many residents. Most displaced individuals received housing support from the Aga Khan Agency for Habitat (AKAH), while the government provided limited assistance. The Saudi government also made notable contributions. Between 2018 and 2021, successive GLOF events damaged 186 hectares of agricultural land in both villages in addition to damages and losses to livestock and other life supporting systems. Climate change and deforestation were identified as the primary drivers of these disasters. A multivariate analysis revealed that gender, age, and education had significant impacts on awareness and perceptions of environmental degradation and climate change. Older respondents, particularly those aged 50-60, were the most influential in shaping future disaster preparedness and mitigation efforts. Although education had a smaller effect size, it still played a crucial role in raising environmental awareness. Mitigation strategies proposed include afforestation, carbon capture, renewable energy, and waste reduction. Many respondents emphasized the importance of community involvement and education in addressing environmental issues. However, opinions vary on the most effective methods for controlling soil pollution and improving overall environmental health.