Series Of Images Research Articles

Trend Analysis of Total Suspended Solids in Inland Waters Using the BFAST Algorithm on MOD09GA Products in Porto Primavera Reservoir – Brazil

Satellite remote sensing, particularly using the MODIS orbital platform, is crucial for large-scale lake monitoring, allowing the observation of optically active components with suitable spatial and temporal resolution for lakes with surfaces greater than 40 hectares. In this context, the objective of this article was to propose a methodology that improves the retrieval and monitoring of data related to Total Suspended Solids (TSS) in large lakes. The methodology employed involved defining a baseline to map the spatiotemporal dynamics of TSS using MODIS band 1, which generates information in the infrared spectrum and is centered at 645 nm. The method was tested in the Porto Primavera Reservoir (PPR), Brazil. To validate the model, two fieldwork campaigns were conducted in the PPR, where radiometric and water quality data were collected. An empirical model was fitted between reflectance and the TSS data set (r = 0.93, R2 = 0.85, p < 0.01, n = 25). This empirical model was applied to a time series of MODIS images from May 2000 to April 2020. Using the spatial distribution maps, a time series was created from an average pixel of the sampling stations, and then this time series was analyzed to separate the trend and seasonality. The results showed that the average TSS values observed in the time series were 5.79 mg/L. The seasonality of the time series revealed that the highest concentration is recorded in the austral summer (December-February), the rainiest season. The trend component indicates that variations in TSS concentration coincide with exceptional events of increased precipitation and with a homogenization interval of the waters following the reservoir's construction.

Blue skies: Does the visual composition of sky guide subjective judgments of naturalness in the environment?

Expanding on previous findings, that highlighted the significance of sky in environmental perception, our analysis investigated whether the visual composition of the sky shapes perceptions of environmental naturalness. The study employed a novel, free-selection task in which participants viewed a series of environmental images with varying levels of natural and urban elements, as well as different sky visibility conditions, and were asked to identify “nature” within these images. The task procedure also involved subjective ratings of each scene. Using previously gathered data, we reassessed 105 participants' selection of the sky as “nature” across 96 photos of diverse outdoor scenes to understand which visuospatial features influence these perceptions. Utilizing the Boruta feature selection algorithm, we identified key characteristics—fractal dimensions, brightness, and entropy in brightness, hue, and saturation—that significantly predicted the selection of sky as “nature”, irrespective of the environment type (urban or natural). Results indicated that lower fractal dimensions are preferred for sky selected as “nature”, inversely affecting the naturalness judgment of scenes with the additional effect of brightness. These findings enhance our understanding of how visuospatial features influence environmental perception, offering implications for future research directions and theoretical advancements in understanding environmental perception.

2.5D deep learning based on multi-parameter MRI to differentiate primary lung cancer pathological subtypes in patients with brain metastases

BackgroundBrain metastases (BMs) represents a severe neurological complication stemming from cancers originating from various sources. It is a highly challenging clinical task to accurately distinguish the pathological subtypes of brain metastatic tumors from lung cancer (LC).The utility of 2.5-dimensional (2.5D) deep learning (DL) in distinguishing pathological subtypes of LC with BMs is yet to be determined. MethodsA total of 250 patients were included in this retrospective study, divided in a 7:3 ratio into training set (N=175) and testing set (N=75). We devised a method to assemble a series of two-dimensional (2D) images by extracting adjacent slices from a central slice in both superior-inferior and anterior-posterior directions to form a 2.5D dataset. Multi-Instance learning (MIL) is a weakly supervised learning method that organizes training instances into “bags” and provides labels for entire bags, with the purpose of learning a classifier based on the labeled positive and negative bags to predict the corresponding class for an unknown bag. Therefore, we employed MIL to construct a comprehensive 2.5D feature set. Then we used the single-slice as input for constructing the 2D model. DL features were extracted from these slices using the pre-trained ResNet101. All feature sets were inputted into the support vector machine (SVM) for evaluation. The diagnostic performance of the classification models were evaluated using five-fold cross-validation, with accuracy and area under the curve (AUC) metrics calculated for analysis. ResultsThe optimal performance was obtained using the 2.5D DL model, which achieved the micro-AUC of 0.868 (95% confidence interval [CI], 0.817–0.919) and accuracy of 0.836 in the test cohort. The 2D model achieved the micro-AUC of 0.836 (95 % CI, 0.778–0.894) and accuracy of 0.827 in the test cohort. ConclusionsThe proposed 2.5D DL model is feasible and effective in identifying pathological subtypes of BMs from lung cancer.

Magnetic Resonance Elastography for Staging Liver Fibrosis in the Oncopig.

This pilot study investigated the feasibility of using magnetic resonance elastography (MRE) for the non-invasive detection and quantification of liver fibrosis in the Oncopig cancer model. Seven 8-week-old Oncopigs underwent alcoholic liver fibrosis induction and serial MRE imaging and liver biopsy at 1, 2, and 3 months post procedure. MRE was utilized to quantify liver stiffness, and liver fibrosis was histologically graded using the METAVIR system. The primary outcome measure was the capability to detect and quantify liver fibrosis using MRE with radiologic-pathologic correlation. Liver fibrosis induction, MRE imaging, and liver biopsy were successfully performed. MRE liver fibrosis was evident in 57% (4/7), 50% (3/6), and 40% (2/5) animal subjects 1, 2, and 3 months after fibrosis induction, with mean liver stiffness of 2.94, 3.25, and 2.91 kPa, respectively. Histological liver fibrosis was noted in 71% (5/7), 100% (5/5), and 100% (5/5) of animal subjects with available tissue samples. There was no significant statistical correlation between the MRE-measured liver stiffness and the METAVIR fibrosis scores. In conclusion, quantifiable liver fibrosis may be induced in the Oncopig. MRE has potential utility in non-invasively detecting liver stiffness in this large-animal preclinical model, though tissue biopsy was more sensitive in demonstrating disease.

Gender bias in generative artificial intelligence text-to-image depiction of medical students

Introduction: In Australia, 54.3% of medical students are women yet they remain under-represented in stereotypical perspectives of medicine. While potentially transformative, generative artificial intelligence (genAI) has the potential for errors, misrepresentations and bias. GenAI text-to-image production could reinforce gender biases making it important to evaluate DALL-E 3 (the text-to-image genAI supported through ChatGPT) representations of Australian medical students. Method: In March 2024, DALL-E 3 was utilised via GPT-4 to generate a series of individual and group images of medical students, specifically Australian undergraduate medical students to eliminate potential confounders. Multiple iterations of images were generated using a variety of prompts. Collectively, 47 images were produced for evaluation of which 33 were individual characters and the remaining 14 images were comprised of multiple (5 to 67) characters. All images were independently analysed by three reviewers for apparent gender and skin tone. Consequently, 33 feature individuals were evaluated and a further 417 characters in groups were evaluated ( N = 448). Discrepancies in responses were resolved by consensus. Results: Collectively (individual and group images), 58.8% ( N = 258) of medical students were depicted as men, 39.9% ( N = 175) as women, 92.0% ( N = 404) with a light skin tone, 7.7% ( N = 34) with mid skin tone and 0% with dark skin tone. The gender distribution was a statistically significant variation from that of actual Australian medical students for individual images, for group images and for collective images. Among the images of individual medical students ( N = 25), DALL-E 3 generated 92% ( N = 23) as men and 100% were of light skin tone ( N = 25). Conclusion: This evaluation reveals the gender associated with genAI text-to-image generation using DALL-E 3 among Australian undergraduate medical students. Generated images included a disproportionately high proportion of white male medical students which is not representative of the diversity of medical students in Australia. The use of DALL-E 3 to produce depictions of medical students for education or promotion purposes should be done with caution.

Optical coherence tomography assessment of the impact of colchicine on non-culprit coronary plaque composition after myocardial infarction.

Low-dose colchicine reduces the risk of cardiovascular events after myocardial infarction (MI). The purpose of this study was to assess the effect of colchicine post-MI on coronary plaque morphology in non-culprit segments by optical coherence tomography (OCT). COCOMO-ACS was a double-blind, placebo-controlled trial that randomized 64 patients (median age 61.5 years; 9.4% female) with acute non-ST-segment elevation MI to colchicine 0.5 mg daily or placebo for a median of 17.8 months in addition to guideline-recommended therapy. Participants underwent serial OCT imaging within a matched segment of non-culprit coronary artery which contained at least one lipid-rich plaque causing ≥20% stenosis. The primary outcome was the change in minimum fibrous cap thickness (FCT) in non-culprit segments from baseline to final visit. Of those randomized, 57 (29 placebo, 28 colchicine) had evaluable imaging at baseline and follow-up. Overall, colchicine had no effect on relative (placebo +48.0±35.1% vs. colchicine +62.4±38.1%, P=0.18) or absolute changes in minimum FCT (+29.2±20.9 µm vs. +37.2±21.3 µm, P=0.18), or change in maximum lipid arc (-38.8±32.2° vs. -54.8±46.9°, P=0.18) throughout the imaged non-culprit segment. However, in patients assigned colchicine, cap rupture was less frequent (placebo 27.6% vs. colchicine 3.6%, P=0.03). In post-hoc analysis of 43 participants who had been followed for at least 16 months, minimum FCT increased to a greater extent in the colchicine group (placebo +38.7±25.4% vs. colchicine +64.7±34.1%, P=0.005). In this study, OCT failed to detect an effect of colchicine on the minimum FCT or maximum lipid arc of plaques in non-culprit segments post-MI. The post-hoc observation that minimum FCT increased to a greater extent with colchicine after more prolonged treatment suggests longer-term studies may be required to detect the effect of anti-inflammatory therapies on plaque morphology by OCT. Australian New Zealand Clinical Trials Registry Identifier, ACTRN12618000809235, registered on the 11th of May 2018.

Circulating monocytes decrease significantly following disease-directed therapy and may reflect disease expansion in Langerhans Cell Histiocytosis.

We aimed to examine the association between relative monocytosis and the recurrence of pulmonary Langerhans Cell Histiocytosis. Clinical, laboratory, radiographic and treatment data for 86 patients with a histopathological diagnosis of Langerhans Cell Histiocytosis over a 20-year duration. Parameters such as biological sex, age at diagnosis, time to diagnosis, molecular diagnostic data and imaging were collected. Treatment responses were assessed predominantly through radiography, with RECIST 1.1 criteria applied to MRI or CT scans and PERCIST utilized for serial PET imaging. Investigators also assessed peripheral blood absolute monocyte count at various time points, including initial diagnosis and the most recently available value. While peripheral blood absolute monocyte count between the earliest assessed timepoint and latest value did not differ, the mean value on progression (0.94K/µL), however, was significantly higher than that following re-institution of therapy (0.31, p = 0.000794. Our observation of relative monocytosis on LCH disease progression may be related to an increase in circulating LCH on disease progression or from increased monocyte production for later differentiation into mature dendritic cells that participate in MHC Class 1 upregulation. This trend is especially evident in pulmonary LCH which is incited by tissue trauma and irritation by environmental factors. The phenomena observed in our study parallel other non-LCH cohorts, specifically in published findings from our own group in patients with Rosai Dorfman and Erdheim Chester Disease. To further elucidate the molecular underpinnings of LCH and explore the etiology of this monocyte trend, expanded integrated genomic-transcriptomic sequencing analyses to evaluate the molecular character of LCH and ultimately clarify the origin of this monocyte trend are in progress. These studies are poised to offer invaluable insight to the molecular mechanisms underlying LCH, specifically as they pertain to monocyte signaling and differentiation.

Photometry, rotation period determination and dust coma numerical study of comet C/2017 K2 (PanStarrs)

C/2017 K2 (Pan-STARRS) is an Oort cloud comet discovered in May 2017. Ground observations have revealed that this long-period comet was active at a heliocentric distance beyond 20 au. Several studies observed this object when it was far from the Sun and proposed that, at such a distance, its activity is primarily driven by the sublimation of super-volatile ices such as CO and CO2.The aim of this paper is to analyze the comet’s dust behavior when it was much closer to the Sun. A series of images were taken on different observation routines between July and August 2022 with the 0.6 m Helen Sawyer Hogg (HSH) telescope at the Complejo Astronómico El Leoncito (CASLEO), using broadband V and R filters. The objective was to conduct a morphological, photometric, and numerical analysis of this comet.Digital filters were applied to enhance contrast in the cometary images, revealing an active region embedded within an isotropic coma. Analysis of the magnitudes and dust production rate from the A(0°)fρ parameter suggests a steady-state dust behavior, consistent with findings from other authors.Moreover, thanks to the images covering a significant time span, it was possible to determine the comet’s rotation period using a periodogram analysis with the Phase Dispersion Minimization method (PDM) and to calculate the coordinates of the rotation axis, yielding a rotation period of 14.24 h with a pole situated at the ecliptic longitude and latitude of (244°,−20°).Finally, to gain deeper insights into C/2017 K2’s dust behavior, observations were fitted to a newly developed theoretical model for studying dust comas. The analysis suggests that the comet’s dust coma was principally formed by large dust particles emitted at a velocity of 180ms−1.

Visual morbidity in macroprolactinoma: A retrospective cohort study.

The management of visual field damage in patients with macroprolactinomas is a major therapeutic challenge. We aimed to study the visual morbidity associated with macroprolactinoma and its outcomes following medical and surgical treatment. We aimed to identify predictors of visual recovery. We retrospectively reviewed patient's data including clinical presentation, serial pituitary magnetic resonance imaging, laboratory tests, visual symptoms and neuro-ophthalmologic examination, visual field tests and optical coherence tomography tests. The main outcome was complete visual field recovery. Descriptive analyses were conducted. Predictors of visual recovery were investigated. The study cohort included 150 patients with macroprolactinoma [median follow-up, 6.0 years (interquartile range (IQR) 2.9-10.6)]. At diagnosis, visual field defects were evident in 40 patients (26.7%). At the end of follow-up, 24 out of 39 available visual field tests (61.5%) exhibited complete recovery. Patients that achieved complete visual recovery had smaller macroadenomas at diagnosis [30.5 mm (15.0-80.0) vs. 42.0 mm (30.0-85.0), p < .01], lower baseline serum prolactin levels [1414 mcg/L (489-3586) vs. 4119 mcg/L (2715-6315), p < .01], lower rates of central hypogonadism (78.3% vs. 93.3%, p = .05) and central hypothyroidism (20.8% vs. 53.3%, p = .04), lower rates of compressive optic neuropathy (35.3% vs. 87.5%, p = .02) and a better visual acuity (better than 6/8 in both eyes, 93.7% vs. 28.6%, p < .01). In our cohort of 150 patients with macroprolactinoma, 40 patients (26.7%) presented with visual field defects, of which 61.5% achieved complete visual recovery with treatment. Patients that achieved complete visual recovery presented with smaller macroadenomas, lower serum prolactin levels, lower rates of central hypogonadism and central hypothyroidism, lower rates of compressive optic neuropathy and better visual acuity.

DNIM: Deep-sea netting intelligent enhancement and exposure monitoring using bio-vision

Intelligent monitoring of deep-sea nets is affected by light attenuation, light scattering, and limited dynamic range factors of the camera, which can cause color shift, low visibility, and over/underexposure in monitoring, resulting in reduced farming efficiency, and misdetection of biological behavior. Therefore, we propose a method for underwater net tank scene enhancement and exposure using multicolor space and bio-vision, called DNIM. Specifically, we first propose an intelligent enhancement and exposure monitoring method for deep-sea nets using bio-vision, which eliminates the effect of exposure on underwater imaging by introducing a bio-vision system that uses a brightness transformation function to generate a series of exposure images. Inspired by the image fusion method, we designed a color correction and visibility recovery method using bio-vision. In the Lab color model, color shifts in bio-vision are corrected by guiding feature transformations with contrast-constrained adaptive histogram equalization; in the RGB color model, depth information is recovered by creating a linear model for the depth of field of underwater blurred images based on the characteristics of the bio-vision system. To obtain more qualified results, we also propose an efficient perceptual fusion module to mix the output of visibility recovery and color correction. Finally, we propose two deep-sea net tank culture datasets: salmon bait-eating behavior dataset (SBBD) and salmon non-bait-eating behavior dataset (SNBD). By comparing the experimental analysis in four real scenario datasets, our DNIM achieved superior results compared to 16 advanced underwater enhancement methods. The code is publicly available at: https://github.com/An-Shunmin/DNIM.

Monopile-induced turbulence and sediment redistribution form visible wakes in offshore wind farms

Offshore wind farms are becoming an increasingly common feature in the marine environment as a renewable energy source. There is a growing body of evidence on the effects of wind farms on the seabed and its organisms. However, an important and understudied aspect of site development is the interaction of turbine foundations on the surrounding marine environment. Structures exert significant disturbance on tides, waves and currents; these are visible as optically-distinct, elongate wakes at the sea surface with elevated suspended particulate matter. Despite this, there is uncertainty on the mechanisms that lead to the visible manifestation of wakes at turbine foundations, primarily due to a lack of direct measurements. Here, in situ measurements along with a 15-year time series of satellite images of the Thanet offshore wind farm, located within the Thames Estuary, were used to investigate the formation of visible monopile wakes, and the effects these have on the surrounding water column. We show the optically distinct wakes are near-constant at Thanet; visible in &amp;gt;90% of all satellite images, yet no regional change in sea surface turbidity could be attributed to wind farm construction or operation. Monopile wake in situ water samples and acoustic Doppler current profiler (ADCP) backscatter measurements demonstrated colour change related to elevated sea surface sediment concentration. However, averaged water column measurements of suspended sediment within wakes, and upstream of monopiles, remained consistent. These measurements demonstrate that sediment was redistributed towards surface waters, rather than additional sediment becoming suspended in the wake. ADCP velocity measurements supported a mechanism of sediment lofting towards the surface, with enhanced vertically upwards flow recorded in wakes.

Restoring Atrial T-Tubules Augments Systolic Ca Upon Recovery From Heart Failure.

Transverse (t)-tubules drive the rapid and synchronous Ca2+ rise in cardiac myocytes. The virtual complete atrial t-tubule loss in heart failure (HF) decreases Ca2+ release. It is unknown if or how atrial t-tubules can be restored and how this affects systolic Ca2+. HF was induced in sheep by rapid ventricular pacing and recovered following termination of rapid pacing. Serial block-face scanning electron microscopy and confocal imaging were used to study t-tubule ultrastructure. Function was assessed using patch clamp, Ca2+, and confocal imaging. Candidate proteins involved in atrial t-tubule recovery were identified by western blot and expressed in rat neonatal ventricular myocytes to determine if they altered t-tubule structure. Atrial t-tubules were lost in HF but reappeared following recovery from HF. Recovered t-tubules were disordered, adopting distinct morphologies with increased t-tubule length and branching. T-tubule disorder was associated with mitochondrial disorder. Recovered t-tubules were functional, triggering Ca2+ release in the cell interior. Systolic Ca2+, ICa-L, sarcoplasmic reticulum Ca2+ content, and sarcoendoplasmic reticulum Ca2+ ATPase function were restored following recovery from HF. Confocal microscopy showed fragmentation of ryanodine receptor staining and movement away from the z-line in HF, which was reversed following recovery from HF. Acute detubulation, to remove recovered t-tubules, confirmed their key role in restoration of the systolic Ca2+ transient, the rate of Ca2+ removal, and the peak L-type Ca2+ current. The abundance of telethonin and myotubularin decreased during HF and increased during recovery. Transfection with these proteins altered the density and structure of tubules in neonatal myocytes. Myotubularin had a greater effect, increasing tubule length and branching, replicating that seen in the recovery atria. We show that recovery from HF restores atrial t-tubules, and this promotes recovery of ICa-L, sarcoplasmic reticulum Ca2+ content, and systolic Ca2+. We demonstrate an important role for myotubularin in t-tubule restoration. Our findings reveal a new and viable therapeutic strategy.

Development and Implementation of Postdischarge Text Messages to Adolescents With Suicidal Thoughts and Behaviors Through Caring Contacts: Implementation Study.

Youth suicide is a pressing public health concern, and transitions in care after a suicidal crisis represent a period of elevated risk. Disruptions in continuity of care and emotional support occur frequently. "Caring contacts" validating messages post discharge have the potential to enhance connections with patients and have been shown to improve outcomes. More recently, positive outcomes have been noted using caring contact text messages (SMS and MMS), which hold promise for engaging patients in a pediatric setting, but there are few studies describing the large-scale implementation of such an approach. This study aims to describe the process of developing and implementing automated caring contacts within a quality improvement framework, using a standardized series of supportive texts and images, for adolescents discharged from high-acuity programs at a large midwestern pediatric hospital. We describe lessons learned, including challenges and factors contributing to success. We implemented the caring contacts intervention in 3 phases. Phase 1 entailed developing supportive statements and images designed to promote hope, inclusivity, and connection in order to create 2 sets of 8 text messages and corresponding images. Phase 2 included piloting caring contacts manually in the hospital's Psychiatric Crisis Department and Inpatient Psychiatry Unit and assessing the feasibility of implementation in other services, as well as developing workflows and addressing legal considerations. Phase 3 consisted of implementing an automated process to scale within 4 participating hospital services and integrating enrollment into the hospital's electronic medical records. Process outcome measures included staff compliance with approaching and enrolling eligible patients and results from an optional posttext survey completed by participants. Compliance data are presented for 4062 adolescent patients eligible for caring contacts. Overall, 88.65% (3601/4062) of eligible patients were approached, of whom 52.43% (1888/3601) were enrolled. In total, 94.92% (1792/1888) of enrolled participants completed the program. Comparisons of the patients eligible, approached, enrolled, and completed are presented. Primary reasons for eligible patients declining include not having access to a mobile phone (686/1705, 40.23%) and caregivers preferring to discuss the intervention at a later time (754/1705, 44.22%). The majority of patients responding to the optional posttext survey reported that the texts made them feel moderately to very hopeful (219/264, 83%), supported (232/264, 87.9%), that peers would be helped by these texts (243/264, 92%), and that they would like to keep receiving texts given the option (227/264, 86%). This study describes the successful implementation of automated postdischarge caring contacts texts to scale with an innovative use of images and demonstrates how a quality improvement methodology resulted in a more effective and efficient process. This paper also highlights the potential for technology to enhance care for at-risk youth and create more accessible, inclusive, and sustainable prevention strategies.

Spatiotemporal change characteristics of NDVI and response to climate factors in the Jixi Wetland, Eastern China.

Exploring the spatiotemporal variation characteristics of vegetation in the confluent area of water systems in western Jinan and its response mechanism to climatic factors is of great significance for the scientific evaluation of the benefits of the water system connectivity project and eco-environmental protection and can provide a reference for ecotourism development in the Jixi wetland park. Based on the Landsat series of images and meteorological data, this study used ENVI to interpret the normalized difference vegetation index (NDVI) of the confluent area from 2010 to 2021, and the spatiotemporal change characteristics and trends of NDVI were quantitatively analyzed. The response of the growing-season NDVI (GSN) to climate factors and its time-lag effect were explored. The results showed that the overall change in the interannual NDVI in the confluent area from 2010 to 2021 was stable. The GSN in the confluent area was significantly positively correlated with precipitation, average temperature, and relative humidity in 37.64%, 25.52%, and 20.87% of the area respectively, and significantly negatively correlated with sunshine hours in 15.32% of the area. There was a time-lag effect on the response of the GSN to climate factors; the response to precipitation and sunshine hours lagged by 1month, and the response to average temperature and relative humidity was longer.

A Deep Learning Approach to Predict Recanalization First-Pass Effect following Mechanical Thrombectomy in Patients with Acute Ischemic Stroke.

Following endovascular thrombectomy in patients with large-vessel occlusion stroke, successful recanalization from 1 attempt, known as the first-pass effect, has correlated favorably with long-term outcomes. Pretreatment imaging may contain information that can be used to predict the first-pass effect. Recently, applications of machine learning models have shown promising results in predicting recanalization outcomes, albeit requiring manual segmentation. In this study, we sought to construct completely automated methods using deep learning to predict the first-pass effect from pretreatment CT and MR imaging. Our models were developed and evaluated using a cohort of 326 patients who underwent endovascular thrombectomy at UCLA Ronald Reagan Medical Center from 2014 to 2021. We designed a hybrid transformer model with nonlocal and cross-attention modules to predict the first-pass effect on MR imaging and CT series. The proposed method achieved a mean 0.8506 (SD, 0.0712) for cross-validation receiver operating characteristic area under the curve (ROC-AUC) on MR imaging and 0.8719 (SD, 0.0831) for cross-validation ROC-AUC on CT. When evaluated on the prospective test sets, our proposed model achieved a mean ROC-AUC of 0.7967 (SD, 0.0335) with a mean sensitivity of 0.7286 (SD, 0.1849) and specificity of 0.8462 (SD, 0.1216) for MR imaging and a mean ROC-AUC of 0.8051 (SD, 0.0377) with a mean sensitivity of 0.8615 (SD, 0.1131) and specificity 0.7500 (SD, 0.1054) for CT, respectively, representing the first classification of the first-pass effect from MR imaging alone and the first automated first-pass effect classification method in CT. Results illustrate that both nonperfusion MR imaging and CT from admission contain signals that can predict a successful first-pass effect following endovascular thrombectomy using our deep learning methods without requiring time-intensive manual segmentation.

Detection of glaucoma progression on longitudinal series of en-face macular optical coherence tomography angiography images with a deep learning model

Background/aimsTo design a deep learning (DL) model for the detection of glaucoma progression with a longitudinal series of macular optical coherence tomography angiography (OCTA) images.Methods202 eyes of 134 patients with...

Prediction of laser printers and cartridges based on three-dimensional profiles via discrimination analysis

Printer source prediction is an important task when examining questioned documents. While some research has provided methods to predict the source printer of documents, with the advent of compatible consumables, printer prediction could become more complex and difficult. Predicting the source printer after replacing cartridges and identifying the source of printer cartridges are unresolved issues that are rarely addressed in current research. Herein, we introduce a novel technique to predict the manufacturer, model, and cartridges of laser printers (i.e., compatible, and original cartridges) used to produce a given document. Document samples produced using eight laser printers and 247 cartridges were collected to establish a dataset. Common manufacturers included HP, Canon, Lenovo, and Epson. After obtaining white-light images and three-dimensional profile images of printed characters, a morphological analysis was conducted by questioned document examiners (QDEs) using microscopy. Microscopic image features across a series of images were also extracted and analyzed using algorithms. Then, six high-dimensional reduction algorithms were used to obtain between- and within-printer variations as well as between- and within-cartridge variations. Finally, we conducted principal component analysis (PCA) and discriminant analysis. For 40 % of the samples, mixed discrimination analysis (MDA) and fixed discrimination analysis (FDA) were employed to predict the manufacturer, model and cartridge of laser printers used to produce the questioned printed document; the remaining 60 % samples comprised the training dataset. In the prediction of manufacturer, model and cartridge, our method achieved mean accuracies of 95.5 %, 97.5 %, and 90.2 %, respectively. Hence, this technique could reasonably aid in predicting the manufacturer, model, and cartridge of a laser printer, even if different cartridges are loaded into printers.

In a Canine Model of Septic Shock, Cardiomyopathy Occurs Independent of Catecholamine Surges and Cardiac Microvascular Ischemia.

High levels of catecholamines are cardiotoxic and associated with stress-induced cardiomyopathies. Using a septic shock model that reproduces the reversible cardiomyopathy seen over 10 days associated with human septic shock, we investigated the effects of catecholamines on microcirculatory perfusion and cardiac dysfunction. Purpose-bred beagles received intrabronchial Staphylococcus aureus (n=30) or saline (n=6). The septic animals were than randomized to epinephrine (1 μg/kg per minute, n=15) or saline (n=15) infusions from 4 to 44 hours. Serial cardiac magnetic resonance imaging, catecholamine levels, and troponins were collected over 92 hours. Serial adenosine-stress perfusion cardiac magnetic resonance imaging was performed on septic animals randomized to receive saline (n=8 out of 15) or epinephrine (n=8 out of 15). High-dose sedation was given to suppress endogenous catecholamine release. Despite catecholamine levels largely remaining within the normal range throughout, by 48 hours, septic animals receiving saline versus nonseptic animals still developed significant worsening of left ventricular ejection fraction, circumferential strain, and ventricular-aortic coupling. In septic animals that received epinephrine versus saline infusions, plasma epinephrine levels increased 800-fold, but epinephrine produced no significant further worsening of left ventricular ejection fraction, circumferential strain, or ventricular-aortic coupling. Septic animals receiving saline had a significant increase in microcirculatory reserve without troponin elevations. Septic animals receiving epinephrine had decreased edema, blunted microcirculatory perfusion, and elevated troponin levels that persisted for hours after the epinephrine infusion stopped. Cardiac dysfunction during sepsis is not primarily due to elevated endogenous or exogenous catecholamines nor due to decreased microvascular perfusion-induced ischemia. However, epinephrine itself has potentially harmful long-lasting ischemic effects during sepsis including impaired cardiac microvascular perfusion that persists after stopping the infusion.

Real time precisely tracing the fluctuations of mitochondrial SO2 in cells during ferroptosis and tissues using a mitochondrial-immobilized ratiometric fluorescent probe

Mitochondrial sulfur dioxide (SO2) plays important roles in physiological and pathological activities. Unfortunately, it is lack of a reliable tool to precisely visualize the mitochondrial SO2 and elaborate its complicated functions in various cytoactivities. Here we report a mitochondrial-immobilized fluorescent probe PM-Cl consisting of coumarin and benzyl chloride modified benzothiazole, which enables selective visualization of mitochondrial SO2via chemical immobilization. The spectral results demonstrated that probe PM-Cl could respond to SO2 with high selectivity and sensitivity. Co-localization and the fluorescence of cytolysis extraction verified the excellent mitochondrial targeting and anchoring abilities. Due to the chemical immobilization, probe PM-Cl could firmly retain into mitochondria after stimulation of carbonyl cyanide m-chlorophenyl hydrazone (CCCP) and H2O2. Significantly, a series of fluorescence images are indicative of capability for detecting the fluctuations of SO2 in mitochondria during ferroptosis. Furthermore, PM-Cl also could visualize SO2 in myocardium and muscle tissues after the stimulation of CCCP. Taken together, probe PM-Cl is a very potential molecular tool for precisely detecting mitochondrial SO2 to explore its complex functions in physiological and pathological activities.

Chronic osteoarthritis caused by Propionibacterium australiense infection in a captive sand gazelle.

Osteoarthritis is a common cause of morbidity and mortality in geriatric gazelles. Propionibacterium australiense has been reported as a cause of systemic granulomas in cattle, but there are no descriptions of this bacteria infecting other species nor causing osteoarthritis, to our knowledge. An 8-y-old, castrated male, sand gazelle (Gazella leptoceros leptoceros) was managed for chronic, intermittent, progressive osteoarthritis of the right tarsus. Serial biopsies revealed pyogranulomatous dermatitis with intralesional bacteria. Serial diagnostic imaging identified osseous and soft tissue proliferation with draining tracts. Treatments over 1 y included broad-spectrum antibiotics, anti-inflammatories, joint debridement, and infusion with platelet-rich plasma and stem cells. Despite therapy, lameness persisted, azotemia developed, and subsequently, the animal was euthanized. On postmortem examination, the periarticular tissue of the right tarsus was markedly expanded by pyogranulomas and fibrosis. Histologically, the synovium, joint capsule, and overlying soft tissues were markedly expanded by pyogranulomas and numerous gram-positive and acid-fast-negative filamentous bacteria surrounded by Splendore-Hoeppli material. Within the joint, there was regionally extensive cartilage ulceration, osteonecrosis, osteolysis, and pannus formation. PCR assay of affected formalin-fixed, paraffin-embedded tissue amplified segments of 16S rRNA and β subunit of bacterial RNA polymerase (rpoB) genes with 99.7% and 95.6% identity to P. australiense. This bacterium should be considered a differential for chronic pyogranulomatous osteoarthritis in gazelles.