Towards regulatory generative AI in ophthalmology healthcare: a security and privacy perspective.

As the healthcare community increasingly harnesses the power of generative artificial intelligence (AI), critical issues of security, privacy and regulation take centre stage. In this paper, we explore the security and privacy risks of generative AI from model-level and data-level perspectives. Moreover, we elucidate the potential consequences and case studies within the domain of ophthalmology. Model-level risks include knowledge leakage from the model and model safety under AI-specific attacks, while data-level risks involve unauthorised data collection and data accuracy concerns. Within the healthcare context, these risks can bear severe consequences, encompassing potential breaches of sensitive information, violating privacy rights and threats to patient safety. This paper not only highlights these challenges but also elucidates governance-driven solutions that adhere to AI and healthcare regulations. We advocate for preparedness against potential threats, call for transparency enhancements and underscore the necessity of clinical validation before real-world implementation. The objective of security and privacy improvement in generative AI warrants emphasising the role of ophthalmologists and other healthcare providers, and the timely introduction of comprehensive regulations.

Exploring the optimal lower blood pressure boundary during endovascular thrombectomy in patients with large vessel occlusion.

BACKGROUND: Current guidelines advocate for maintaining BP level below 180/105 mmHg during EVT, determining the safe lower boundary remains primarily consensus-driven by experts. This study aims to delve into the correlation between various targets of lower boundary for systolic and diastolic BP (SBP and DBP) during EVT and 3-month functional outcomes. METHODS: A cohort study was conducted across two EVT-capable centers, enrolling patients with large artery occlusion undergoing EVT within 8 h of stroke onset. Mean BP values during EVT were meticulously recorded, and logistic regression models were utilized to evaluate the correlation between outcomes and diverse lower boundary targets for SBP and DBP. Additionally, logistic regression models investigated the relationship between periprocedural BP variability and subsequent outcomes. RESULTS: Among the 201 patients included, having a SBP higher than 130 or 140 mmHg showed an independent association with increased good functional outcomes at 3 months (adjusted odds ratio, aOR 2.80, 95% Cis, 1.26-6.39 for 140 mmHg; aOR 2.34, 95% Cis, 1.03-5.56 for 130 mmHg). Additionally, an SBP exceeding 130 mmHg was correlated with decreased 3-month mortality (aOR, 0.24, 95% CI 0.07-0.74). No significant relationship was observed between DBP and functional outcomes. Patients with higher periprocedural SBP coefficient variance exhibited a decreased rate of good functional outcomes at 3 months (aOR, 0.42, 95% CI, 0.18-0.96). CONCLUSIONS: A SBP range above 130-140 mmHg could potentially serve as a safe lower boundary during EVT, while minimizing BP fluctuations may correlate with improved post-EVT functional outcomes.

Undergarment Needs and Challenges for Breast Cancer Survivors: A Qualitative Study.

Purpose: Breast cancer surgery, even with reconstruction, can make it difficult for patients to find a bra that fits properly, is comfortable, and meets their aesthetic standards. We explored breast cancer survivors' experiences with bras over time to identify preferences, needs, and challenges throughout their journeys. Methods: Fifteen women who had undergone mastectomy and either delayed or immediate breast reconstruction participated in the study. Focus groups were conducted to explore the participants' current experiences with bras. They were also prompted to recall their experiences before mastectomy and immediately after reconstruction. The discussion included bra materials, styles, construction techniques, color, quality, and price. Results: Thematic analysis generated five major themes: "Sense of normalcy and personal well-being," "Struggles immediately following surgery," "Transitions in bra experiences and preference," "Practicality with outfit," and "Association between quality and price". Conclusion: Breast cancer survivors' well-being is linked to their experiences with bras and the associated purchasing process, and bra needs change throughout the cancer care journey. Survivors' experiences with bras impact their sense of normalcy and sense of control over significant bodily changes arising from cancer and its treatment. The study underscores the importance of future research on examining the relationship between survivors' quality of life and garment experiences, including factors such as color choices, closure options, and adjustability for individual needs.

Capsaicin reduces blood glucose and prevents prostate growth by regulating androgen, RAGE/IGF-1/Akt, TGF-ß/Smad signalling pathway and reversing epithelial-mesenchymal transition in streptozotocin-induced diabetic mice.

Type 2 diabetes mellitus (T2DM) is a metabolic disease. Diabetes increases the risk of benign prostatic hyperplasia (BPH). Capsaicin is extracted from chili peppers and possesses many pharmacological properties, including anti-diabetic, pain-relieving, and anti-cancer properties. This study aimed to investigate the effects of capsaicin on glucose metabolism and prostate growth in T2DM mice and uncover the related mechanisms. Mice model of diabetes was established by administering a high-fat diet and streptozotocin. Oral administration of capsaicin for 2 weeks inhibited prostate growth in testosterone propionate (TP)-treated mice. Furthermore, oral administration of capsaicin (5 mg/kg) for 2 weeks decreased fasting blood glucose, prostate weight, and prostate index in diabetic and TP-DM mice. Histopathological alterations were measured using hematoxylin & eosin (H&E) staining. The protein expression of 5α-reductase type II, androgen receptor (AR), and prostate-specific antigen (PSA) were upregulated in diabetic and TP-DM mice, but capsaicin reversed these effects. Capsaicin decreased the protein expression of p-AKT, insulin-like growth factor-1 (IGF-1), IGF-1R, and the receptor for advanced glycation end products (RAGE) in diabetic and TP-DM mice. Capsaicin also regulated epithelial-mesenchymal transition (EMT) and modulated the expression of fibrosis-related proteins, including E-cadherin, N-cadherin, vimentin, fibronectin, α-SMA, TGFBR2, TGF-ß1, and p-Smad in TP-DM mice. In this study, capsaicin alleviated diabetic prostate growth by attenuating EMT. Mechanistically, capsaicin affected EMT by regulating RAGE/IGF-1/AKT, AR, and TGF-ß/Smad signalling pathways. These results provide with new therapeutic approach for treating T2DM or T2DM-induced prostate growth.

Clinical factors associated with subsequent surgical intervention in women undergoing early medical termination of viable or non-viable pregnancies.

Introduction: Mifepristone-misoprostol treatment for medical abortion and miscarriage are safe and effective. This study aimed to assess clinical factors associated with subsequent surgical intervention after medical termination of early viable or non-viable pregnancy. Methods: This retrospective, single-center study included women who underwent medical abortion at Taipei Medical University between January 2010 and December 2019. A total of 1,561 subjects, with 1,080 viable and 481 non-viable pregnancies, who were treated with oral mifepristone 600 mg followed by misoprostol 600 mg 48 h later were included. Data of all pregnancies and medical termination of pregnancy were evaluated using regression analysis. The main outcome was successful termination of pregnancy. Results: The success rate of medical abortion was comparable in women with viable and non-viable (92.13% vs. 92.93%) pregnancies. Besides retained tissue, more existing pregnancies with ultrasonographic findings were found in the non-viable pregnancy group than in the viable pregnancy group (29.4% vs. 14.1%, p = 0.011). Multivariate analysis showed that previous delivery was an independent risk factor for failed medical abortion among all included cases. In women with viable pregnancy, longer gestational age [adjusted odds ratio (aOR): 1.483, 95% confidence interval (CI): 1.224-1.797, p < 0.001] and previous Cesarean delivery (aOR: 2.177, 95% CI: 1.167-40.62, p = 0.014) were independent risk factors for failed medical abortion. Number of Cesarean deliveries (aOR: 1.448, 95% CI: 1.029-2.039, p = 0.034) was an independent risk factor for failed medication abortion in women with non-viable pregnancies. Conclusion: This is the first cohort study to identify risk factors for subsequent surgical intervention in women with viable or non-viable pregnancies who had undergone early medically induced abortions. The success rate of medical abortion is comparable in women with viable and non-viable pregnancies. Previous delivery is an independent risk factor for failed medical abortion. Clinical follow-up may be necessary for women who are at risk of subsequent surgical intervention.

Machine Learning Prediction of Prediabetes in a Young Male Chinese Cohort with 5.8-Year Follow-Up.

The identification of risk factors for future prediabetes in young men remains largely unexamined. This study enrolled 6247 young ethnic Chinese men with normal fasting plasma glucose at the baseline (FPGbase), and used machine learning (Mach-L) methods to predict prediabetes after 5.8 years. The study seeks to achieve the following: 1. Evaluate whether Mach-L outperformed traditional multiple linear regression (MLR). 2. Identify the most important risk factors. The baseline data included demographic, biochemistry, and lifestyle information. Two models were built, where Model 1 included all variables and Model 2 excluded FPGbase, since it had the most profound effect on prediction. Random forest, stochastic gradient boosting, eXtreme gradient boosting, and elastic net were used, and the model performance was compared using different error metrics. All the Mach-L errors were smaller than those for MLR, thus Mach-L provided the most accurate results. In descending order of importance, the key factors for Model 1 were FPGbase, body fat (BF), creatinine (Cr), thyroid stimulating hormone (TSH), WBC, and age, while those for Model 2 were BF, white blood cell, age, TSH, TG, and LDL-C. We concluded that FPGbase was the most important factor to predict future prediabetes. However, after removing FPGbase, WBC, TSH, BF, HDL-C, and age were the key factors after 5.8 years.

Prehospital shock index multiplied by the alert/verbal/painful/unresponsive score as a predictor of clinical outcomes in traumatic injury.

OBJECTIVE: Various prediction scores have been developed to predict mortality in trauma patients, such as the shock index (SI), modified SI (mSI), age-adjusted SI (aSI), and the shock index (SI) multiplied by the alert/verbal/painful/unresponsive (AVPU) score (SIAVPU). The SIAVPU is a novel scoring system but its prediction accuracy for trauma outcomes remains in need of further validation. Therefore, we investigated the accuracy of four scoring systems, including SI, mSI, aSI, and SIAVPU, in predicting mortality, admission to the intensive care unit (ICU), and prolonged hospital length of stay ≥ 30 days (LOS).METHODS: This retrospective multicenter study used data from the Tzu Chi Hospital trauma database. The area under the receiver operating characteristic curve (AUROC) was determined for each outcome to assess their discrimination capabilities and comparing by Delong's test. Subgroup analyses were conducted to investigate the prediction accuracy of the SIAVPU in different patient populations.RESULTS: In total, 5355 patients were included in the analysis. The median of SIAVPU were significantly higher among patients at those with major injury (1.47 vs 0.63), those admitted to the ICU (0.73 vs 0.62), those with prolonged hospital LOS≥ 30 days (0.83 vs 0.64), and those with mortality (1.08 vs 0.64). The AUROC of the SIAVPU was significantly higher than that of the SI, mSI, and aSI for 24-hour mortality (AUROC: 0.845 vs 0.533, 0.540, and 0.678), 3-day mortality (AUROC: 0.803 vs 0.513, 0.524, and 0.688), 7-day mortality (AUROC: 0.755 vs 0.494, 0.505, and 0.648), in-hospital mortality (AUROC: 0.722 vs 0.510, 0.524, and 0.667), ICU admission (AUROC: 0.635 vs 0.547, 0.551, and 0.563). At the optimal cutoff value of 0.9, the SIAVPU had an accuracy of 82.2% for predicting 24-hour mortality, 82.8% for predicting 3-day mortality, of 82.8% for predicting 7-day mortality, of 82.5% for predicting in-hospital mortality, of 73.9% for predicting Intensive Care Unit (ICU) admission, and of 81.7% for predicting prolonged hospital LOS ≥30 days.CONCLUSIONS: Our results reveal that SIAVPU has better accuracy than the SI, mSI, and aSI for predicting 24-hour, 3-day, 7-day, and in-hospital mortality; ICU admission; and prolonged hospital LOS ≥30 days among patients with traumatic injury.

TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction.

Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases. However, the high cross-frame distribution variation due to rapid tracer kinetics poses a considerable challenge for inter-frame motion correction, especially for early frames where intensity-based image registration techniques often fail. To address this issue, we propose a novel method called Temporally and Anatomically Informed Generative Adversarial Network (TAI-GAN) that utilizes an all-to-one mapping to convert early frames into those with tracer distribution similar to the last reference frame. The TAI-GAN consists of a feature-wise linear modulation layer that encodes channel-wise parameters generated from temporal information and rough cardiac segmentation masks with local shifts that serve as anatomical information. Our proposed method was evaluated on a clinical 82Rb PET dataset, and the results show that our TAI-GAN can produce converted early frames with high image quality, comparable to the real reference frames. After TAI-GAN conversion, the motion estimation accuracy and subsequent myocardial blood flow (MBF) quantification with both conventional and deep learning-based motion correction methods were improved compared to using the original frames. The code is available at https://github.com/gxq1998/TAI-GAN.

Design and development of the DE-SPECT system: a clinical SPECT system for broadband multi-isotope imaging of peripheral vascular disease.

Objective Peripheral Vascular Disease (PVD) affects more than 230 million people worldwide and is one of the leading causes of disability among people over age 60. Nowadays, PVD remains largely underdiagnosed and undertreated, and requires the development of tailored diagnostic approaches. We present the full design of the Dynamic Extremity SPECT (DE-SPECT) system, the first organ-dedicated SPECT system for lower extremity imaging, based on 1-cm thick Cadmium Zinc Telluride (CZT) spectrometers and a dynamic dual field-of-view (FOV) synthetic compound-eye collimator. Approach The proposed DE-SPECT detection system consists of 48 1-cm thick 3D-position-sensitive CZT spectrometers arranged in a partial ring of 59 cm in diameter in a checkerboard pattern. The detection system is coupled with a compact dynamic synthetic compound-eye (SCE) collimator that allows the user to select between two different FOVs at any time during an imaging study: a wide-FOV (28-cm diameter) configuration for dual-leg or scout imaging or a high-resolution and high-sensitivity (HR-HS) FOV (16-cm diameter) for single-leg or focused imaging. Main Results The preliminary experimental data show that the CZT spectrometer achieves a 3D intrinsic spatial resolution of <0.75 mm FWHM and an excellent energy resolution over a broad energy range (2.6 keV FWHM at 218 keV, 3.3 keV at 440 keV). From simulations, the wide-FOV configuration offers a 0.034% averaged sensitivity at 140 keV and <8 mm spatial resolution, whereas the HR-HS configuration presents a peak central sensitivity of 0.07% at 140 keV and a ~5 mm spatial resolution. The dynamic SCE collimator enables the capability to perform joint reconstructions that would ensure an overall improvement in imaging performance. Significance The DE-SPECT system is a stationary and high-performance SPECT system that offers an excellent spectroscopic performance with a unique computer-controlled dual-FOV imaging capability, and a relatively high sensitivity for multi-tracer and multi-functional SPECT imaging of the extremities.

Association of tuberculosis risk with genetic polymorphisms of the immune checkpoint genes PDCD1, CTLA-4, and TIM3.

The immune checkpoint proteins were reported to involve to host resistance to Mycobacteria tuberculosis (Mtb). Here, we evaluated 11 single nucleotide polymorphisms (SNPs) in PDCD1, CTLA4, and HAVCR2 genes between participants with and without TB infection. Genomic DNA isolated from 285 patients with TB and 270 controls without TB infection were used to perform the genotyping assay. Odds ratios were used to characterize the association of 11 SNPs with TB risk. In this study, the various genotypes of the 11 SNPs did not differ significantly in frequency between the non-TB and TB groups. When patients were stratified by sex, however, men differed significantly from women in genotype frequencies at HAVCR2 rs13170556. Odds ratios indicated that rs2227982, rs13170556, rs231775, and rs231779 were sex-specifically associated with TB risk. In addition, the combinations of rs2227982/rs13170556 GA/TC in men and the A-C-C haplotype of rs231775-rs231777-rs231779 in women were significantly associated with TB risk. Our results indicate that rs2227982 in PDCD1 and rs13170556 in HAVCR2 are associated with increased TB susceptibility in men and that the CTLA4 haplotype appears protective against TB in women.

Caffeinated Chewing Gum Improves Basketball Shooting Accuracy and Physical Performance Indicators of Trained Basketball Players: A Double-Blind Crossover Trial.

(1) Background: This study investigated the effects of caffeinated chewing gum on the basketball-specific performance of trained basketball players. A double-blind, randomized crossover design was employed. (2) Methods: Fifteen participants (age: 20.9 ± 1.0 years; height: 180.9 ± 5.4 cm; mass: 77.2 ± 7.5 kg; training age: 8.2 ± 0.3 years) were recruited and divided into a caffeine trial (CAF) and placebo trial (PL). The participants in the CAF trial chewed gum containing 3 mg/kg of caffeine for 10 min, while those in the PL trial chewed a placebo gum without caffeine. Following a 15 min rest, all the participants completed basketball-specific performance tests. (3) Results: The free throw accuracy for the CAF trial was significantly higher than that for the PL trial (CAF: 79.0 ± 4.31%; PL: 73.0 ± 9.16%; p = 0.012; Cohen's d = 0.94). Additionally, the CAF trial demonstrated significantly better performance in the 20 m segmented dash (CAF: 2.94 ± 1.12 s; PL: 3.13 ± 0.10 s; p < 0.001; Cohen's d =1.8) and squats (p < 0.05), and exhibited lower fatigue indexes (CAF: 3.6 ± 1.6%; PL: 5.2 ± 1.6%; p = 0.009; Cohen's d =1.0). (4) Conclusions: These findings suggest that chewing gum containing 3 mg/kg of caffeine offers moderate-to-large improvements in key performance aspects relevant to professionally trained basketball players.

InsigHTable: Insight-driven Hierarchical Table Visualization with Reinforcement Learning.

Embedding visual representations within original hierarchical tables can mitigate additional cognitive load stemming from the division of users' attention. The created hierarchical table visualizations can help users understand and explore complex data with multi-level attributes. However, because of many options available for transforming hierarchical tables and selecting subsets for embedding, the design space of hierarchical table visualizations becomes vast, and the construction process turns out to be tedious, hindering users from constructing hierarchical table visualizations with many data insights efficiently. We propose InsigHTable, a mixed-initiative and insight-driven hierarchical table transformation and visualization system. We first define data insights within hierarchical tables, which consider the hierarchical structure in the table headers. Since hierarchical table visualization construction is a sequential decision-making process, InsigHTable integrates a deep reinforcement learning framework incorporating an auxiliary rewards mechanism. This mechanism addresses the challenge of sparse rewards in constructing hierarchical table visualizations. Within the deep reinforcement learning framework, the agent continuously optimizes its decision-making process to create hierarchical table visualizations to uncover more insights by collaborating with analysts. We demonstrate the usability and effectiveness of InsigHTable through two case studies and sets of experiments. The results validate the effectiveness of the deep reinforcement learning framework and show that InsigHTable can facilitate users to construct hierarchical table visualizations and understand underlying data insights.

Magnetic metal-organic frameworks as sensitive aptasensors for coronavirus spike protein.

Electrochemical biosensors, known for their low cost, sensitivity, selectivity, and miniaturization capabilities, are ideal for point-of-care devices. The magnetic metal-organic framework (MMOF), synthesized using the in-situ growth method, consists of ferric salt, magnetic nanoparticles, histidine, and benzene tetracarboxylic acid. MMOF was sequentially modified with aptamer-biotin and streptavidin-horseradish peroxidase, serving as a detector for spike protein and a transducer converting electrochemical signals using H2O2-hydroquinone on a screen-printed electrode. MMOF facilitates easy washing and homogeneous deposition on the working electrode with a magnet, enhancing sensitivity and reducing noise. The physical and electrochemical properties of the modified MMOFs were thoroughly characterized using various analytical techniques. The aptasensors' performance achieved a detection limit of 6 pM for voltammetry and 5.12 pM for impedance spectroscopy in human serum samples. This cost-effective, portable MMOF platform is suitable for rapid point-of-care testing for SARS-CoV-2 spike proteins.

Removing crosstalk signals in neuron activity by time multiplexed excitations in a two-photon all-optical physiology system.

The two-photon all-optical physiology system has attracted great interest in deciphering neuronal circuits in vivo, benefiting from its advantages in recording and modulating neuronal activities at single neuron resolutions. However, the interference, or crosstalk, between the imaging and photostimulation beams introduces a significant challenge and may impede the future application of voltage indicators in two-photon all-optical physiology system. Here, we propose the time multiplexed excitation method to distinguish signals from neuronal activities and crosstalks from photostimulation. In our system, the laser pulses of the imaging beam and photostimulation beam are synchronized, and a time delay is introduced into these pulses to separate the fluorescence signal generated by these two beams. We demonstrate the efficacy of our system in eliminating crosstalk signals from photostimulation and evaluate its influence on both genetically encoded calcium indicators (GECIs) and genetically encoded voltage indicators (GEVIs) through in vivo experiments.

High-resolution magnetic resonance vessel wall imaging in ischemic stroke and carotid artery atherosclerotic stenosis: A review.

Ischemic stroke is a significant burden on human health worldwide. Carotid Atherosclerosis stenosis plays an important role in the comprehensive assessment and prevention of ischemic stroke patients. High-resolution vessel wall magnetic resonance imaging has emerged as a successful technique for assessing carotid atherosclerosis stenosis. This advanced imaging modality has shown promise in effectively displaying a wide range of characteristics associated with the condition, leading to a comprehensive evaluation. High-resolution vessel wall magnetic resonance imaging not only enables a comprehensive evaluation of the instability of carotid atherosclerosis stenosis plaques but also provides valuable information for understanding the pathogenesis and predicting the prognosis of ischemic stroke patients. The purpose of this article is to review the application of high-resolution magnetic resonance imaging in ischemic stroke and carotid atherosclerotic stenosis.

DuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT.

Single-Photon Emission Computed Tomography (SPECT) is widely applied for the diagnosis of coronary artery diseases. Low-dose (LD) SPECT aims to minimize radiation exposure but leads to increased image noise. Limited-view (LV) SPECT, such as the latest GE MyoSPECT ES system, enables accelerated scanning and reduces hardware expenses but degrades reconstruction accuracy. Additionally, Computed Tomography (CT) is commonly used to derive attenuation maps (µ-maps) for attenuation correction (AC) of cardiac SPECT, but it will introduce additional radiation exposure and SPECT-CT misalignments. Although various methods have been developed to solely focus on LD denoising, LV reconstruction, or CT-free AC in SPECT, the solution for simultaneously addressing these tasks remains challenging and under-explored. Furthermore, it is essential to explore the potential of fusing cross-domain and cross-modality information across these interrelated tasks to further enhance the accuracy of each task. Thus, we propose a Dual-Domain Coarse-to-Fine Progressive Network (DuDoCFNet), a multi-task learning method for simultaneous LD denoising, LV reconstruction, and CT-free µ-map generation of cardiac SPECT. Paired dual-domain networks in DuDoCFNet are cascaded using a multi-layer fusion mechanism for cross-domain and cross-modality feature fusion. Two-stage progressive learning strategies are applied in both projection and image domains to achieve coarse-to-fine estimations of SPECT projections and CT-derived µ-maps. Our experiments demonstrate DuDoCFNet's superior accuracy in estimating projections, generating µ-maps, and AC reconstructions compared to existing single- or multi-task learning methods, under various iterations and LD levels. The source code of this work is available at https://github.com/XiongchaoChen/DuDoCFNet-MultiTask.

Use of Reverse Shock Index Multiplied by Simplified Motor Score in a Five-Level Triage System: Identifying Trauma in Adult Patients at a High Risk of Mortality.

Background and Objectives: The Taiwan Triage and Acuity Scale (TTAS) is reliable for triaging patients in emergency departments in Taiwan; however, most triage decisions are still based on chief complaints. The reverse-shock index (SI) multiplied by the simplified motor score (rSI-sMS) is a more comprehensive approach to triage that combines the SI and a modified consciousness assessment. We investigated the combination of the TTAS and rSI-sMS for triage compared with either parameter alone as well as the SI and modified SI. Materials and Methods: We analyzed 13,144 patients with trauma from the Taipei Tzu Chi Trauma Database. We investigated the prioritization performance of the TTAS, rSI-sMS, and their combination. A subgroup analysis was performed to evaluate the trends in all clinical outcomes for different rSI-sMS values. The sensitivity and specificity of rSI-sMS were investigated at a cutoff value of 4 (based on previous study and the highest score of the Youden Index) in predicting injury severity clinical outcomes under the TTAS system were also investigated. Results: Compared with patients in triage level III, those in triage levels I and II had higher odds ratios for major injury (as indicated by revised trauma score < 7 and injury severity score [ISS] ≥ 16), intensive care unit (ICU) admission, prolonged ICU stay (≥14 days), prolonged hospital stay (≥30 days), and mortality. In all three triage levels, the rSI-sMS < 4 group had severe injury and worse outcomes than the rSI-sMS ≥ 4 group. The TTAS and rSI-sMS had higher area under the receiver operating characteristic curves (AUROCs) for mortality, ICU admission, prolonged ICU stay, and prolonged hospital stay than the SI and modified SI. The combination of the TTAS and rSI-sMS had the highest AUROC for all clinical outcomes. The prediction performance of rSI-sMS < 4 for major injury (ISS ≥ 16) exhibited 81.49% specificity in triage levels I and II and 87.6% specificity in triage level III. The specificity for mortality was 79.2% in triage levels I and II and 87.4% in triage level III. Conclusions: The combination of rSI-sMS and the TTAS yielded superior prioritization performance to TTAS alone. The integration of rSI-sMS and TTAS effectively enhances the efficiency and accuracy of identifying trauma patients at a high risk of mortality.

Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification.

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve the quality and quantitative accuracy of Ki images by utilizing deep learning techniques to reduce the noise in dynamic PET images. We propose a novel denoising technique, Population-based Deep Image Prior (PDIP), which integrates population-based prior information into the optimization process of Deep Image Prior (DIP). Specifically, the population-based prior image is generated from a supervised denoising model that is trained on a prompts-matched static PET dataset comprising 100 clinical studies. The 3D U-Net architecture is employed for both the supervised model and the following DIP optimization process. We evaluated the efficacy of PDIP for noise reduction in 25%-count and 100%-count dynamic PET images from 23 patients by comparing with two other baseline techniques: the Prompts-matched Supervised model (PS) and a conditional DIP (CDIP) model that employs the mean static PET image as the prior. Both the PS and CDIP models show effective noise reduction but result in smoothing and removal of small lesions. In addition, the utilization of a single static image as the prior in the CDIP model also introduces a similar tracer distribution to the denoised dynamic frames, leading to lower Ki in general as well as incorrect Ki in the descending aorta. By contrast, as the proposed PDIP model utilizes intrinsic image features from the dynamic dataset and a large clinical static dataset, it not only achieves comparable noise reduction as the supervised and CDIP models but also improves lesion Ki predictions.

CTNNAL1 promotes the structural integrity of bronchial epithelial cells through the RhoA/ROCK1 pathway.

Adhesion molecules play critical roles in maintaining the structural integrity of the airway epithelium in airways under stress. Previously, we reported that catenin alpha-like 1 (CTNNAL1) is downregulated in an asthma animal model and upregulated at the edge of human bronchial epithelial cells (HBECs) after ozone stress. In this work, we explore the potential role of CTNNAL1 in the structural adhesion of HBECs and its possible mechanism. We construct a CTNNAL1 ‒/‒ mouse model with CTNNAL1-RNAi recombinant adeno-associated virus (AAV) in the lung and a CTNNAL1-silencing cell line stably transfected with CTNNAL1-siRNA recombinant plasmids. Hematoxylin and eosin (HE) staining reveals that CTNNAL1 ‒/‒ mice have denuded epithelial cells and structural damage to the airway. Silencing of CTNNAL1 in HBECs inhibits cell proliferation and weakens extracellular matrix adhesion and intercellular adhesion, possibly through the action of the cytoskeleton. We also find that the expressions of the structural adhesion-related molecules E-cadherin, integrin ß1, and integrin ß4 are significantly decreased in ozone-treated cells than in vector control cells. In addition, our results show that the expression levels of RhoA/ROCK1 are decreased after CTNNAL1 silencing. Treatment with Y27632, a ROCK inhibitor, abolished the expressions of adhesion molecules induced by ozone in CTNNAL1-overexpressing HBECs. Overall, the findings of the present study suggest that CTNNAL1 plays a critical role in maintaining the structural integrity of the airway epithelium under ozone challenge, and is associated with epithelial cytoskeleton dynamics and the expressions of adhesion-related molecules via the RhoA/ROCK1 pathway.