Urban Pedestrian Routes' Accessibility Assessment Using Geographic Information System Processing and Deep Learning-Based Object Detection.

The need to establish safe, accessible, and inclusive pedestrian routes is considered one of the European Union's main priorities. We have developed a method of assessing pedestrian mobility in the surroundings of urban public buildings to evaluate the level of accessibility and inclusion, especially for people with reduced mobility. In the first stage of assessment, artificial intelligence algorithms were used to identify pedestrian crossings and the precise geographical location was determined by deep learning-based object detection with satellite or aerial orthoimagery. In the second stage, Geographic Information System techniques were used to create network models. This approach enabled the verification of the level of accessibility for wheelchair users in the selected study area and the identification of the most suitable route for wheelchair transit between two points of interest. The data obtained were verified using inertial sensors to corroborate the horizontal continuity of the routes. The study findings are of direct benefit to the users of these routes and are also valuable for the entities responsible for ensuring and maintaining the accessibility of pedestrian routes.

A dataset of text prompts, videos and video quality metrics from generative text-to-video AI models.

Evaluating the quality of videos which have been automatically generated from text-to-video (T2V) models is important if the models are to produce plausible outputs that convince a viewer of their authenticity. This paper presents a dataset of 201 text prompts used to automatically generate 1,005 videos using 5 very recent T2V models namely Tune-a-Video, VideoFusion, Text-To-Video Synthesis, Text2Video-Zero and Aphantasia. The prompts are divided into short, medium and longer lengths. We also include the results of some commonly used metrics used to automatically evaluate the quality of those generated videos. These include each video's naturalness, the text similarity between the original prompt and an automatically generated text caption for the video, and the inception score which measures how realistic is each generated video. Each of the 1,005 generated videos was manually rated by 24 different annotators for alignment between the videos and their original prompts, as well as for the perception and overall quality of the video. The data also includes the Mean Opinion Scores (MOS) for alignment between the generated videos and the original prompts. The dataset of T2V prompts, videos and assessments can be reused by those building or refining text-to-video generation models to compare the accuracy, quality and naturalness of their new models against existing ones.

Shift in virus composition in honeybees (Apis mellifera) following worldwide invasion by the parasitic mite and virus vector Varroa destructor.

Invasive vectors can induce dramatic changes in disease epidemiology. While viral emergence following geographical range expansion of a vector is well known, the influence a vector can have at the level of the host's pathobiome is less well understood. Taking advantage of the formerly heterogeneous spatial distribution of the ectoparasitic mite Varroa destructor that acts as potent virus vector among honeybees Apis mellifera, we investigated the impact of its recent global spread on the viral community of honeybees in a retrospective study of historical samples. We hypothesized that the vector has had an effect on the epidemiology of several bee viruses, potentially altering their transmissibility and/or virulence, and consequently their prevalence, abundance, or both. To test this, we quantified the prevalence and loads of 14 viruses from honeybee samples collected in mite-free and mite-infested populations in four independent geographical regions. The presence of the mite dramatically increased the prevalence and load of deformed wing virus, a cause of unsustainably high colony losses. In addition, several other viruses became more prevalent or were found at higher load in mite-infested areas, including viruses not known to be actively varroa-transmitted, but which may increase opportunistically in varroa-parasitized bees.

The Potential of Electrospinning to Enable the Realization of Energy-Autonomous Wearable Sensing Systems.

The market for wearable electronic devices is experiencing significant growth and increasing potential for the future. Researchers worldwide are actively working to improve these devices, particularly in developing wearable electronics with balanced functionality and wearability for commercialization. Electrospinning, a technology that creates nano/microfiber-based membranes with high surface area, porosity, and favorable mechanical properties for human in vitro and in vivo applications using a broad range of materials, is proving to be a promising approach. Wearable electronic devices can use mechanical, thermal, evaporative and solar energy harvesting technologies to generate power for future energy needs, providing more options than traditional sources. This review offers a comprehensive analysis of how electrospinning technology can be used in energy-autonomous wearable wireless sensing systems. It provides an overview of the electrospinning technology, fundamental mechanisms, and applications in energy scavenging, human physiological signal sensing, energy storage, and antenna for data transmission. The review discusses combining wearable electronic technology and textile engineering to create superior wearable devices and increase future collaboration opportunities. Additionally, the challenges related to conducting appropriate testing for market-ready products using these devices are also discussed.

Minutes-duration optical flares with supernova luminosities.

In recent years, certain luminous extragalactic optical transients have been observed to last only a few days1. Their short observed duration implies a different powering mechanism from the most common luminous extragalactic transients (supernovae), whose timescale is weeks2. Some short-duration transients, most notably AT2018cow (ref. 3), show blue optical colours and bright radio and X-ray emission4. Several AT2018cow-like transients have shown hints of a long-lived embedded energy source5, such as X-ray variability6,7, prolonged ultraviolet emission8, a tentative X-ray quasiperiodic oscillation9,10 and large energies coupled to fast (but subrelativistic) radio-emitting ejecta11,12. Here we report observations of minutes-duration optical flares in the aftermath of an AT2018cow-like transient, AT2022tsd (the 'Tasmanian Devil'). The flares occur over a period of months, are highly energetic and are probably nonthermal, implying that they arise from a near-relativistic outflow or jet. Our observations confirm that, in some AT2018cow-like transients, the embedded energy source is a compact object, either a magnetar or an accreting black hole.

Corrigendum: Applications and techniques for fast machine learning in science.

[This corrects the article DOI: 10.3389/fdata.2022.787421.].

Supershear Rayleigh wave imaging for quantitative assessment of biomechanical properties of brain using air-coupled optical coherence elastography.

Recently, supershear Rayleigh waves (SRWs) have been proposed to characterize the biomechanical properties of soft tissues. The SRWs propagate along the surface of the medium, unlike surface Rayleigh waves, SRWs propagate faster than bulk shear waves. However, their behavior and application in biological tissues is still elusive. In brain tissue elastography, shear waves combined with magnetic resonance elastography or ultrasound elastography are generally used to quantify the shear modulus, but high spatial resolution elasticity assessment in 10 µm scale is still improving. Here, we develop an air-coupled ultrasonic transducer for noncontact excitation of SRWs and Rayleigh waves in brain tissue, use optical coherent elastography (OCE) to detect, and reconstruct the SRW propagation process; in combing with a derived theoretical model of SRWs on a free boundary surface, we quantify the shear modulus of brain tissue with high spatial resolution. We first complete validation experiments using a homogeneous isotropic agar phantom, and the experimental results clearly show the SRW is 1.9649 times faster than the bulk shear waves. Furthermore, the propagation velocity of SRWs in both the frontal and parietal lobe regions of the brain is all 1.87 times faster than the bulk shear wave velocity. Finally, we evaluated the anisotropy in different brain regions, and the medulla oblongata region had the highest anisotropy index. Our study shows that the OCE system using the SRW model is a new potential approach for high-resolution assessment of the biomechanical properties of brain tissue.

Effects of Extraction Process Factors on the Composition and Antioxidant Activity of Blackthorn (Prunus spinosa L.) Fruit Extracts.

This study aimed at establishing the optimal conditions for the classic extraction of phenolic compounds from Prunus spinosa L. fruits. The effects of different parameters, i.e., ethanol concentration in the extraction solvent (mixture of ethanol and water), operation temperature, and extraction time, on process responses were evaluated. Total phenolic content (TPC), total anthocyanin content (TAC), antioxidant capacity (AC), and contents of protocatechuic acid (PA), caffeic acid (CA), vanillic acid (VA), rutin hydrate (RH), and quercetin (Q) of fruit extracts were selected as process responses. A synergistic effect of obtaining high values of TPC, TAC, AC, PA, and VA was achieved for the extraction in 50% ethanol at 60 °C for 30 min. At a higher level of process temperature, the extraction of protocatechuic acid and vanillic acid was enhanced, but the flavonoids, i.e., rutin hydrate and quercetin, were degraded. A lower temperature should be used to obtain a higher amount of flavonoids. TPC, TAC, AC, and phenolic acid contents (PA, CA, and VA) in the extract samples obtained at an ethanol concentration of 50-100%, a temperature of 30-60 °C, and an extraction time of 30 min were strongly directly correlated.

Noncontact longitudinal shear wave imaging for the evaluation of heterogeneous porcine brain biomechanical properties using optical coherence elastography.

High-resolution quantification of heterogeneous brain biomechanical properties has long been an important topic. Longitudinal shear waves (LSWs) can be used to assess the longitudinal Young's modulus, but contact excitation methods have been used in most previous studies. We propose an air-coupled ultrasound transducer-based optical coherence elastography (AcUT-OCE) technique for noncontact excitation and detection of LSWs in samples and assessment of the nonuniformity of the brain's biomechanical properties. The air-coupled ultrasonic transducer (AcUT) for noncontact excitation of LSWs in the sample has a center frequency of 250 kHz. Phase-resolved Doppler optical coherence tomography (OCT) was used to image and reconstruct the propagation behavior of LSWs and surface ultrasound waves at high resolution. An agar phantom model was used to verify the feasibility of the experimental protocol, and experiments with ex vivo porcine brain samples were used to assess the nonuniformity of the brain biomechanical properties. LSWs with velocities of 0.83 ± 0.11 m/s were successfully excited in the agar phantom model. The perivascular elastography results in the prefrontal cortex (PFC) of the ex vivo porcine brains showed that the Young's modulus was significantly higher in the longitudinal and transverse directions on the left side of the cerebral vessels than on the right side and that the Young's modulus of the PFC decreased with increasing depth. The AcUT-OCE technique, as a new scheme for LSW applications in in vivo elastography, can be used for noncontact excitation of LSWs in brain tissue and high-resolution detection of heterogeneous brain biomechanical properties.

The Pleasurable Urge to Move to Music Through the Lens of Learning Progress.

Interacting with music is a uniquely pleasurable activity that is ubiquitous across human cultures. Current theories suggest that a prominent driver of musical pleasure responses is the violation and confirmation of temporal predictions. For example, the pleasurable urge to move to music (PLUMM), which is associated with the broader concept of groove, is higher for moderately complex rhythms compared to simple and complex rhythms. This inverted U-shaped relation between PLUMM and rhythmic complexity is thought to result from a balance between predictability and uncertainty. That is, moderately complex rhythms lead to strongly weighted prediction errors which elicit an urge to move to reinforce the predictive model (i.e., the meter). However, the details of these processes and how they bring about positive affective responses are currently underspecified. We propose that the intrinsic motivation for learning progress drives PLUMM and informs the music humans choose to listen to, dance to, and create. Here, learning progress reflects the rate of prediction error minimization over time. Accordingly, reducible prediction errors signal the potential for learning progress, producing a pleasurable, curious state characterized by the mobilization of attentional and memory resources. We discuss this hypothesis in the context of current psychological and neuroscientific research on musical pleasure and PLUMM. We propose a theoretical neuroscientific model focusing on the roles of dopamine and norepinephrine within a feedback loop linking prediction-based learning, curiosity, and memory. This perspective provides testable predictions that will motivate future research to further illuminate the fundamental relation between predictions, movement, and reward.

Effects of changes in trunk inclination on ventilatory efficiency in ARDS patients: quasi-experimental study.

BACKGROUND: Trunk inclination from semirecumbent head-upright to supine-flat positioning reduces driving pressure and increases respiratory system compliance in patients with acute respiratory distress syndrome (ARDS). These effects are associated with an improved ventilatory ratio and reduction in the partial pressure of carbon dioxide (PaCO2). However, these physiological effects have not been completely studied, and their mechanisms have not yet been elucidated. Therefore, this study aimed to evaluate the effects of a change in trunk inclination from semirecumbent (45°) to supine-flat (10°) on physiological dead space and ventilation distribution in different lung regions. RESULTS: Twenty-two ARDS patients on pressure-controlled ventilation underwent three 60-min steps in which trunk inclination was changed from 45° (baseline) to 10° (intervention) and back to 45° (control) in the last step. Tunk inclination from a semirecumbent (45°) to a supine-flat (10°) position resulted in a higher tidal volume [371 (± 76) vs. 433 (± 84) mL (P < 0.001)] and respiratory system compliance [34 (± 10) to 41 (± 12) mL/cmH2O (P < 0.001)]. The CO2 exhaled per minute improved from 191 mL/min (± 34) to 227 mL/min (± 38) (P < 0.001). Accordingly, Bohr's dead space ratio decreased from 0.49 (± 0.07) to 0.41 (± 0.06) (p < 0.001), and PaCO2 decreased from 43 (± 5) to 36 (± 4) mmHg (p < 0.001). In addition, the impedance ratio, which divides the ventilation activity of the ventral region by the dorsal region ventilation activity in tidal images, dropped from 1.27 (0.83-1.78) to 0.86 (0.51-1.33) (p < 0.001). These results, calculated from functional EIT images, indicated further ventilation activity in the dorsal lung regions. These effects rapidly reversed once the patient was repositioned at 45°. CONCLUSIONS: A change in trunk inclination from a semirecumbent (45 degrees) to a supine-flat position (10 degrees) improved Bohr's dead space ratio and reduced PaCO2 in patients with ARDS. This effect is associated with an increase in tidal volume and respiratory system compliance, along with further favourable impedance ventilation distribution toward the dorsal lung regions. This study highlights the importance of considering trunk inclination as a modifiable determinant of physiological parameters. The angle of trunk inclination is essential information that must be reported in ARDS patients.

Analysis of Building Accessibility Using Inertial and Optical Sensors.

The inclusive use of urban spaces necessitates detailed knowledge of the accessibility of public buildings or places where educational, health or administrative services are provided. Despite the improvements already made in many cities regarding architectural work, further changes to public buildings and other spaces, such as old buildings or areas of historical importance, are still required. To study this problem, we developed a model based on photogrammetric techniques and the use of inertial and optical sensors. The model allowed us to perform a detailed analysis of urban routes in the surroundings of an administrative building, by means of mathematical analysis of pedestrian routes. It was applied to the specific case of people with reduced mobility and included analysis of the building accessibility as well as detection of suitable transit routes, deterioration of the road surfaces and the presence of architectural obstacles on the route.

Ultrasonic needle hydrophone calibration in air by a parabolic off-axis mirror focused beam using three-transducer reciprocity.

An acoustic field distribution investigation in air requires a small receiving sensor. Needle hydrophones seem to be an attractive solution, and it has previously been demonstrated that needle hydrophones designed for use in water can be used in air. The metrology problem is that an absolute sensitivity calibration is needed, because needle hydrophones are not characterized in air, especially for frequencies below 1 MHz, which is of interest for air-coupled ultrasound. Conventional, three-transducer/microphone reciprocity calibration requires measurements to be done in the far field. However, when transducer diameter is large and the frequency is high, the required measurement distance becomes very large: 3 m for a 20 mm source, transmitting at 1 MHz. Large propagation distance leads to high attenuation and nonlinear effects in air propagation, and distortion and losses accumulate. Small needle hydrophones have low sensitivity, so that high excitation amplitudes would be required, which can lead to transducer heating and increase nonlinearity effects. A derivative of the three-transducer reciprocity calibration method is proposed, where a large aperture transducer is focused onto a hydrophone, using hybrid of plane wave and spherical wave reciprocity. Use of a focused source minimizes the frequency-dependent diffraction effects, and the spherical wave approximation is valid at the focal distance, and low level excitation signals can be used. Focusing is accomplished using a parabolic off-axis mirror. Calibration is in transmission, which reduces the complexity of the electrical measurements. The corresponding equations have been derived for this setup. Calibration of the transducer and needle hydrophone absolute sensitivity is obtained.

Semi-Supervised Mixture Learning for Graph Neural Networks With Neighbor Dependence.

A graph neural network (GNN) is a powerful architecture for semi-supervised learning (SSL). However, the data-driven mode of GNNs raises some challenging problems. In particular, these models suffer from the limitations of incomplete attribute learning, insufficient structure capture, and the inability to distinguish between node attribute and graph structure, especially on label-scarce or attribute-missing data. In this article, we propose a novel framework, called graph coneighbor neural network (GCoNN), for node classification. It is composed of two modules: GCoNN Γ and GCoNN Γ° . GCoNN Γ is trained to establish the fundamental prototype for attribute learning on labeled data, while GCoNN [Formula: see text] learns neighbor dependence on transductive data through pseudolabels generated by GCoNN Γ . Next, GCoNN Γ is retrained to improve integration of node attribute and neighbor structure through feedback from GCoNN [Formula: see text] . GCoNN tends to convergence iteratively using such an approach. From a theoretical perspective, we analyze this iteration process from a generalized expectation-maximization (GEM) framework perspective which optimizes an evidence lower bound (ELBO) by amortized variational inference. Empirical evidence demonstrates that the state-of-the-art performance of the proposed approach outperforms other methods. We also apply GCoNN to brain functional networks, the results of which reveal response features across the brain which are physiologically plausible with respect to known language and visual functions.

Novel acoustic radiation force optical coherence elastography based on ultrasmall ultrasound transducer for biomechanics evaluation of in vivo cornea.

We developed a novel acoustic radiation force optical coherence elastography (ARF-OCE) based on an ultrasmall ultrasound transducer for quantitative biomechanics evaluations of in vivo cornea. A custom single-sided meta-ultrasonic transducer with an outer diameter of 1.8 mm, focal spot diameter of 1.6 mm, central frequency of 930 kHz, and focal length of 0.8 mm was applied to excite the sample. The sample arm of the ARF-OCE system employed a three-dimensional printed holder that allowed for ultrasound excitation and ARF-OCE detection. The phase-resolved algorithm was combined with a Lamb wave model to depth-resolved evaluate corneal biomechanics after keratoconus and cross-linking treatments (CXL). The results showed that, compare to the healthy cornea, the Lamb wave velocity was significantly reduced in the keratoconus, increased in the cornea after CXL, and increased with cross-linked irradiation energy in the cornea. These results indicated the good clinical translation potential of the proposed novel ARF-OCE.

Adaptive data collection for intraindividual studies affected by adherence.

Recently, the use of mobile technologies in ecological momentary assessments (EMAs) and interventions has made it easier to collect data suitable for intraindividual variability studies in the medical field. Nevertheless, especially when self-reports are used during the data collection process, there are difficulties in balancing data quality and the burden placed on the subject. In this paper, we address this problem for a specific EMA setting that aims to submit a demanding task to subjects at high/low values of a self-reported variable. We adopt a dynamic approach inspired by control chart methods and design optimization techniques to obtain an EMA triggering mechanism for data collection that considers both the individual variability of the self-reported variable and of the adherence. We test the algorithm in both a simulation setting and with real, large-scale data from a tinnitus longitudinal study. A Wilcoxon signed rank test shows that the algorithm tends to have both a higher F1 score and utility than a random schedule and a rule-based algorithm with static thresholds, which are the current state-of-the-art approaches. In conclusion, the algorithm is proven effective in balancing data quality and the burden placed on the participants, especially in studies where data collection is impacted by adherence.

Treatment of COVID-19 pneumonia with low-dose radiotherapy plus standard of care versus standard of care alone in frail patients : The SEOR-GICOR IPACOVID comparative cohort trial.

PURPOSE: To assess the efficacy of lung low-dose radiotherapy (LD-RT) in the treatment of patients with COVID-19 pneumonia. MATERIALS AND METHODS: Ambispective study with two cohorts to compare treatment with standard of care (SoC) plus a single dose of 0.5 Gy to the whole thorax (experimental prospective cohort) with SoC alone (control retrospective cohort) for patients with COVID-19 pneumonia not candidates for admission to the intensive care unit (ICU) for mechanical ventilation. RESULTS: Fifty patients treated with LD-RT were compared with 50 matched controls. Mean age was 85 years in both groups. An increase in arterial oxygen partial pressure (PaO2)/fraction of inspired oxygen (PAFI) in the experimental LD-RT-treated group compared to the control group could not be found at 48 h after LD-RT, which was the primary endpoint of the study. However, PAFI values significantly improved after 1 month (473 vs. 302 mm Hg; p < 0.0001). Pulse oxymetric saturation/fraction of inspired oxygen (SAFI) values were also significantly higher in LD-RT-treated patients than in control patients at 1 week (405 vs. 334 mm Hg; p = 0.0157) and 1 month after LD-RT (462 vs. 326 mm Hg; p < 0.0001). All other timepoint measurements of the respiratory parameters were similar across groups. Patients in the experimental group were discharged from the hospital significantly earlier (23 vs. 31 days; p = 0.047). Fifteen and 26 patients died due to COVID-19 pneumonia in the experimental and control cohorts, respectively (30% vs. 48%; p = 0.1). LD-RT was associated with a decreased odds ratio (OR) for 1­month COVID-19 mortality (OR = 0.302 [0.106-0.859]; p = 0.025) when adjusted for potentially confounding factors. Overall survival was significantly prolonged in the LD-RT group compared to the control group (log-rank p = 0.027). No adverse events related to radiation treatment were observed. CONCLUSION: Treatment of frail patients with COVID-19 pneumonia with SoC plus single-dose LD-RT of 0.5 Gy improved respiratory parameters, reduced the period of hospitalization, decreased the rate of 1­month mortality, and prolonged actuarial overall survival compared to SoC alone.

Seguridad y eficacia de la bioprótesis de válvula cardiaca INC en humanos / Safety and efficacy of the INC bioprosthetic heart valve in humans

Resumen Introducción: Las bioprótesis de válvulas cardiacas son el estándar de oro para el reemplazo quirúrgico de la válvula aórtica en pacientes seleccionados. Objetivo: Evaluar la seguridad y eficacia de la válvula cardiaca bioprotésica del Instituto Nacional de Cardiología (INC) en humanos. Métodos: Estudio unicéntrico que incluyó 341 pacientes que se sometieron a reemplazo valvular quirúrgico único de válvula aórtica con válvula INC. Resultados: Se realizaron 318 implantes de novo (93 %) y 23 como segunda cirugía (7 %); las puntuaciones STS fueron de 1.4 y 1.8 % y el seguimiento de 42 y 46 meses, respectivamente. No existieron diferencias en las complicaciones ni en la tasa de implantación de marcapasos. Ambos grupos mantuvieron una FEVI normal. Se observó mejoría global en la clase funcional con empeoramiento solo en dos pacientes del grupo de novo. La disfunción de la prótesis INC que ameritó reintervención quirúrgica se observó en ocho pacientes (4.65 %) del grupo de novo versus un paciente (7.69 %) con segunda cirugía. Conclusiones: La válvula cardiaca INC es eficaz y segura, se asocia a baja tasa de complicaciones y mejoría de la clase funcional durante el seguimiento a largo plazo. Se necesitan estudios prospectivos comparativos de esta válvula.

Abstract Introduction: Heart valve bioprostheses are the gold standard for aortic valve surgical replacement in selected patients. Objective: To evaluate the safety and efficacy of the of the National Institute of Cardiology (INC) bioprosthetic heart alve of the National Institute of Cardiology (INC) bioprosthetic heart valve in humans. Methods: Single-center study that ncluded 341 patients who underwent single surgical aortic valve replacement with INC heart valve. Results: 318 implants were performed de novo (93%) and 23 as redo surgery (7%); STS scores were 1.4 and 1.8%, and follow-up was for 42 and 46 months, respectively. There were no differences in clinical complications or pacemaker implantation rate. Both groups maintained a normal LVEF. Overall improvement in functional class was observed, with worsening only in two patients of the de novo group. INC prosthesis dysfunction requiring surgical reintervention was observed in eight patients (4.65%) of the de novo group vs. one patient in the redo group. Conclusions: The INC heart valve is efficacious and safe, and is associated with a The INC heart valve is efficacious and safe, and is associated with a low rate of complications and functional class improvement during long-term follow-up. Prospective, comparative studies of this valve are required.

Assessment of Keratitis Severity Using Quantitative Image Analysis in an In Vivo Murine Model of Staphylococcus aureus Bacterial Keratitis.

Purpose: Bacterial keratitis (BK) severity in murine models has traditionally been measured by subjective clinical grading or quantification of ocular bacterial burden. This investigation explores an objective and repeatable quantification of slit lamp photography (SLP) images to measure BK severity. Methods: BALB/c strain mice underwent three parallel scratches of the right cornea with subsequent inoculation of 107Staphylococcus aureus cells. SLP imaging and clinical severity grading were performed at 48 hours post-infection. Stromal infiltrate (SI) area on SLP images were quantified. Bacterial burden was determined after enucleation and homogenization. Spearman rank correlations (rs) were used to estimate associations between SI area, clinical severity grades, and bacterial burden. Results: BALB/c strain mice (n = 14) were evaluated with an average SI area of 0.92 mm2 (standard deviation, SD = 0.65) and average bacterial burden of 3.16 × 105 colony forming units per milliliter (CFU/mL) (SD = 8.3 × 105). Clinical severity grade positively correlated with SI area (rs = 0.59, p = 0.0276) and bacterial burden (rs = 0.66, p = 0.0106). There was a trend towards positive association between SI area and bacterial burden (rs = 0.51, p = 0.0543). Conclusions: SLP annotation of SI area is correlated with clinical severity and may provide an objective, quantitative, and repeatable assessment of BK disease severity. Translational Relevance: SLP annotation of SI area is a novel quantitative method to evaluate bacterial keratitis severity longitudinally in mouse models which may be a powerful tool to better understand BK pathogenesis and response to treatments.