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Allergic bronchopulmonary aspergillosis (ABPA) is a hypersensitivity disease caused by Aspergillus fumigatus (Af), prevalent in persons with cystic fibrosis (CF) or asthma. In ABPA, Af proteases drive a T-helper cell-2 (Th2)-mediated allergic immune response leading to inflammation that contributes to permanent lung damage. Corticosteroids and antifungals are the mainstays of therapies for ABPA. However, their long-term use has negative sequelae. The treatment of patients with CF (pwCF) has been revolutionized by the efficacy of cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapy. Pharmacological improvement in CFTR function with highly effective elexacaftor/tezacaftor/ivacaftor (ETI) provides unprecedented improvements in lung function and other clinical outcomes of pwCF. The mechanism behind the improvement in patient outcomes is a continued topic of investigation as our understanding of the role of CFTR function evolves. As ETI therapy gains traction in CF management, understanding its potential impact on ABPA, especially on the allergic immune response pathways and Af infection becomes increasingly crucial for optimizing patient outcomes. This literature review aims to examine the extent of these findings and expand our understanding of the already published research focusing on the intersection between ABPA therapeutic approaches in CF and the rapid impact of the evolving CFTR modulator landscape. While our literature search yielded limited reports specifically focusing on the role of CFTR modulator therapy on CF-ABPA, findings from epidemiologic and retrospective studies suggest the potential for CFTR modulator therapies to positively influence pulmonary outcomes by addressing the underlying pathophysiology of CF-ABPA, especially by decreasing inflammatory response and Af colonization. Thus, this review highlights the promising scope of CFTR modulator therapy in decreasing the overall prevalence and incidence of CF-ABPA.

Allergic bronchopulmonary aspergillosis (ABPA) is a hypersensitivity disease caused by Aspergillus fumigatus (Af), prevalent in persons with cystic fibrosis (CF) or asthma. In ABPA, Af proteases drive a T-helper cell-2 (Th2)-mediated allergic immune response leading to inflammation that contributes to permanent lung damage. Corticosteroids and antifungals are the mainstays of therapies for ABPA. However, their long-term use has negative sequelae. The treatment of patients with CF (pwCF) has been revolutionized by the efficacy of cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapy. Pharmacological improvement in CFTR function with highly effective elexacaftor/tezacaftor/ivacaftor (ETI) provides unprecedented improvements in lung function and other clinical outcomes of pwCF. The mechanism behind the improvement in patient outcomes is a continued topic of investigation as our understanding of the role of CFTR function evolves. As ETI therapy gains traction in CF management, understanding its potential impact on ABPA, especially on the allergic immune response pathways and Af infection becomes increasingly crucial for optimizing patient outcomes. This literature review aims to examine the extent of these findings and expand our understanding of the already published research focusing on the intersection between ABPA therapeutic approaches in CF and the rapid impact of the evolving CFTR modulator landscape. While our literature search yielded limited reports specifically focusing on the role of CFTR modulator therapy on CF-ABPA, findings from epidemiologic and retrospective studies suggest the potential for CFTR modulator therapies to positively influence pulmonary outcomes by addressing the underlying pathophysiology of CF-ABPA, especially by decreasing inflammatory response and Af colonization. Thus, this review highlights the promising scope of CFTR modulator therapy in decreasing the overall prevalence and incidence of CF-ABPA. [ABSTRACT FROM AUTHOR]

This research sought to examine how exercise-related affective states compared with average daily affect. To answer this question, this investigation combined naturalistic methods (i.e., experience sampling) with a more typical exercise protocol. Participants were 36 university students enrolled in step aerobics classes. Participants were asked to carry Palm data recorders set to randomly cue them to complete a questionnaire to tap the affective dimensions of arousal (AD ACL; Thayer, 1989) five times per day over a 7-day period. In addition, participants were asked to complete the AD ACL immediately before, at the midpoint of exercise, and after a 15-min cool-down period after engaging in a bout of aerobic exercise in a class setting. Intensity of exercise was self-chosen, and mean intensity was "strong" (M = 5.28, SD = 1.73) based on Borg's 10-item RPE scale. Daily affect, based on the mean of experience sampling points, and preexercise scores were significantly different for the tension and tiredness subscales. Tension and tiredness were greater during daily recordings than during the preexercise baseline. Results suggest that researchers may be underestimating the tension- and tiredness-reducing effects of exercise if this finding is replicable. The limitations of this research, such as possible contamination by diurnal variations in affective states, are considered., There is considerable support for the ability of acute bouts of exercise to influence affective states (e.g., Arent, Landers, & Etnier, 2000; Landers & Petruzzello, 1994; Thayer, 1987a). Studies have [...]

275 undergraduate university students were asked to complete a battery concerning their health complaints, perceived stress, strenuous physical activity, and personality ('Big Five' traits). An hierarchical regression showed that Stress and Strenuous Physical Activity Participation, but not Personality, predicted the Number of Health Complaints in this sample. Also, there was a significant interaction for Stress by Strenuous Activity indicating individuals who did not frequently engage in strenuous leisure-time physical activity reported more health complaints than those who did. This finding corroborates the notion that physical activity (or fitness) may serve to attenuate the relation between stress and health complaints.

Study Design: Experimental in-vivo animal study.Objective: The aim of this study was to evaluate an Artificial Intelligence (AI)-enabled ultrasound imaging system's ability to detect, segment, classify, and display neural and other structures during trans-psoas spine surgery.Summary Of Background Data: Current methodologies for intraoperatively localizing and visualizing neural structures within the psoas are limited and can impact the safety of lateral lumbar interbody fusion (LLIF). Ultrasound technology, enhanced with AI-derived neural detection algorithms, could prove useful for this task.Methods: The study was conducted using an in vivo porcine model (50 subjects). Image processing and machine learning algorithms were developed to detect neural and other anatomic structures within and adjacent to the psoas muscle while using an ultrasound imaging system during lateral lumbar spine surgery (SonoVision,™ Tissue Differentiation Intelligence, USA). The imaging system's ability to detect and classify the anatomic structures was assessed with subsequent tissue dissection. Dice coefficients were calculated to quantify the performance of the image segmentation.Results: The AI-trained ultrasound system detected, segmented, classified, and displayed nerve, psoas muscle, and vertebral body surface with high sensitivity and specificity. The mean Dice coefficient score for each tissue type was >80%, indicating that the detected region and ground truth were >80% similar to each other. The mean specificity of nerve detection was 92%; for bone and muscle, it was >95%. The accuracy of nerve detection was >95%.Conclusion: This study demonstrates that a combination of AI-derived image processing and machine learning algorithms can be developed to enable real-time ultrasonic detection, segmentation, classification, and display of critical anatomic structures, including neural tissue, during spine surgery. AI-enhanced ultrasound imaging can provide a visual map of important anatomy in and adjacent to the psoas, thereby providing the surgeon with critical information intended to increase the safety of LLIF surgery.Level of Evidence: N/A. [ABSTRACT FROM AUTHOR]

To optimize the application of green roof technology, there is a need to quantify stormwater mitigation in advance of green roof construction. This study contributes toward meeting this need by assessing the utility of four hydrologic models for predicting green roof rainfall capture, including the: (1) curve number method, (2) characteristic runoff equation, (3) Hydrological Evaluation of Landfill Performance (HELP V3.9D) model, and (4) Storm Water Management Model (SWMM V5.1). Modeling results were compared to over twenty-four months of observed runoff data, collected between June 2011 and December 2013, from two full-scale green roofs in New York City (NYC). Both the curve number method and characteristic runoff equation had the highest Nash-Sutcliffe efficiency index (NSEI) between modeled and observed cumulative runoff depth per event (NSEI = 0.97) due to parameter calibration requirements, where error was mainly due to variations in green roof antecedent moisture conditions. The HELP model was originally intended for evaluation of a continuous landfill cover. As a result, HELP's inability to account for the non-vegetated areas on green roofs caused underestimation of runoff depth for most events (NSEI = 0.84). Alternatively, the SWMM model tended to overestimate event runoff depth (NSEI = 0.94), thought to be the result of its storage term parameterization. Model assessments point to the need for more robust parameter estimation methods, particularly for inputs that are statistical or difficult to measure directly, to improve pre-development accuracy of green roof performance models. [ABSTRACT FROM AUTHOR]

A ceramic ytterbium:yttrium aluminum garnet (Yb:YAG) thindisk laser is investigated at 15°C (288 K) and also at 80 K, where it behaves as a four-level laser. We introduce a new two-phase spray cooling method to cool the Yb:YAG. One system relies on R134a refrigerant while the other uses liquid nitrogen (LN2). The use of two systems allows the same disk to be tested at the two temperatures. When the Yb:YAG is cooled from room to cryogenic temperatures, the lasing threshold drops from 155 W to near 10 W, while the slope efficiency increases from 54% to a 63%. A 277 W laser with 520 W of pump is demonstrated. We also model the thermal and structural properties at these two temperatures and estimate the beam quality. [ABSTRACT FROM AUTHOR]