Outcomes of Upper Gastrointestinal Bleeding in Hospitalized COVID-19 Patients in the United States: A Propensity-score Matched Analysis of a Large National Database.

Patients with cirrhosis that are hospitalized with COVID-19 infection have been found to have worse outcomes. No comparative study has been conducted between gastrointestinal (GI) bleeding in patients with cirrhosis who are diagnosed with COVID-19. We utilized the National Inpatient Sample (NIS) database to perform a retrospective analysis of 24, 050 patients diagnosed with cirrhosis and COVID-19. The identified patients were separated into variceal bleeding, nonvariceal bleeding, and no (or neither) GI bleeding groups. After performing propensity sample matching and multivariate analysis of mortality, we found no significant differences in mortality among the three groups. However, the variceal bleed group had a shorter length of stay (5.67 days lower than the no-bleed group). Esophagogastroduodenoscopy (EGD) with intervention was associated with reduced mortality in the variceal and nonvariceal bleeding groups. Acute kidney injury was a strong predictor of mortality in both bleeding groups. A native American race was found to be associated with higher mortality in the nonvariceal bleeding group. Our study suggests that there are various pathophysiological processes among the three groups, with no significant mortality differences with cirrhosis complications of GI bleeding.

Revealing the nature of cardiovascular disease using DERGA, a novel data ensemble refinement greedy algorithm.

BACKGROUND: The study aimed to determine the most crucial parameters associated with CVD and employ a novel data ensemble refinement procedure to uncover the optimal pattern of these parameters that can result in a high prediction accuracy. METHODS AND RESULTS: Data were collected from 369 patients in total, 281 patients with CVD or at risk of developing it, compared to 88 otherwise healthy individuals. Within the group of 281 CVD or at-risk patients, 53 were diagnosed with coronary artery disease (CAD), 16 with end-stage renal disease, 47 newly diagnosed with diabetes mellitus 2 and 92 with chronic inflammatory disorders (21 rheumatoid arthritis, 41 psoriasis, 30 angiitis). The data were analyzed using an artificial intelligence-based algorithm with the primary objective of identifying the optimal pattern of parameters that define CVD. The study highlights the effectiveness of a six-parameter combination in discerning the likelihood of cardiovascular disease using DERGA and Extra Trees algorithms. These parameters, ranked in order of importance, include Platelet-derived Microvesicles (PMV), hypertension, age, smoking, dyslipidemia, and Body Mass Index (BMI). Endothelial and erythrocyte MVs, along with diabetes were the least important predictors. In addition, the highest prediction accuracy achieved is 98.64%. Notably, using PMVs alone yields a 91.32% accuracy, while the optimal model employing all ten parameters, yields a prediction accuracy of 0.9783 (97.83%). CONCLUSIONS: Our research showcases the efficacy of DERGA, an innovative data ensemble refinement greedy algorithm. DERGA accelerates the assessment of an individual's risk of developing CVD, allowing for early diagnosis, significantly reduces the number of required lab tests and optimizes resource utilization. Additionally, it assists in identifying the optimal parameters critical for assessing CVD susceptibility, thereby enhancing our understanding of the underlying mechanisms.

Adrenal cysts less than 10 cm can be safely observed.

BACKGROUND: Adrenal cysts are rare and appropriate management is unclear due to a lack of data on their natural history. Understanding adrenal cyst growth patterns would assist in clinical management. METHODS: This single-institution study included all adult patients diagnosed with simple adrenal cysts between 2004 and 2021. Baseline characteristics and outcomes of those who underwent resection (ADX) or observation (OBS) were compared using the chi-squared test, student's t-test, and Wilcoxon rank-sum test. Growth curves and sensitivity analysis were plotted for all patients who had follow-up imaging. RESULTS: We identified 77 patients with imaging-confirmed adrenal cysts. The majority were female (75.3%) and more than half were white (55.8%). One-third of patients underwent ADX, and the remaining were observed. ADX patients were younger (median age [IQR]: 55.5 y [45.0-68.2 y] vs. 44.2 y [38.7-55.0 y], p = 0.01) and more likely to be Hispanic (12% vs. 0%, p = 0.05). ADX patients presented with larger cysts (5.6 vs. 2.6 cm, p = 0.002). The median time from diagnosis to last follow-up was 1.1 y for ADX and 4.1 y for OBS. Average growth for OBS was 0.3 cm/y, while average growth for ADX was 3.9 cm/y. In ADX patients, cysts >10 cm grew significantly faster than cysts <10 cm (median growth rate 13.2 cm/y vs. 0.3 cm/y, p < 0.05). There was no adrenal malignancy diagnosis, hyperfunctionality, or observation-related complications (e.g., rupture). CONCLUSION: While size >4-6 cm has guided surgical referral for solid adrenal masses, this study demonstrates a size threshold of 10 cm, below which asymptomatic, simple adrenal cysts can safely be observed.

Association between acute peripancreatic fluid collections and early readmission in acute pancreatitis: A propensity-matched analysis.

BACKGROUND: Patients with acute pancreatitis (AP) frequently experience hospital readmissions, posing a significant burden to healthcare systems. Acute peripancreatic fluid collection (APFC) may negatively impact the clinical course of AP. It could worsen symptoms and potentially lead to additional complications. However, clinical evidence regarding the specific association between APFC and early readmission in AP remains scarce. Understanding the link between APFC and readmission may help improve clinical care for AP patients and reduce healthcare costs. AIM: To evaluate the association between APFC and 30-day readmission in patients with AP. METHODS: This retrospective cohort study is based on the Nationwide Readmission Database for 2016-2019. Patients with a primary diagnosis of AP were identified. Participants were categorized into those with and without APFC. A 1:1 propensity score matching for age, gender, and Elixhauser comorbidities was performed. The primary outcome was early readmission rates. Secondary outcomes included the incidence of inpatient complications and healthcare utilization. Unadjusted analyses used Mann-Whitney U and χ 2 tests, while Cox regression models assessed 30-day readmission risks and reported them as adjusted hazard ratios (aHR). Kaplan-Meier curves and log-rank tests verified readmission risks. RESULTS: A total of 673059 patients with the principal diagnosis of AP were included. Of these, 5.1% had APFC on initial admission. After propensity score matching, each cohort consisted of 33914 patients. Those with APFC showed a higher incidence of inpatient complications, including septic shock (3.1% vs 1.3%, P < 0.001), portal venous thrombosis (4.4% vs 0.8%, P < 0.001), and mechanical ventilation (1.8% vs 0.9%, P < 0.001). The length of stay (LOS) was longer for APFC patients [4 (3-7) vs 3 (2-5) days, P < 0.001], as were hospital charges ($29451 vs $24418, P < 0.001). For 30-day readmissions, APFC patients had a higher rate (15.7% vs 6.5%, P < 0.001) and a longer median readmission LOS (4 vs 3 days, P < 0.001). The APFC group also had higher readmission charges ($28282 vs $22865, P < 0.001). The presence of APFC increased the risk of readmission twofold (aHR 2.52, 95% confidence interval: 2.40-2.65, P < 0.001). The independent risk factors for 30-day readmission included female gender, Elixhauser Comorbidity Index ≥ 3, chronic pulmonary diseases, chronic renal disease, protein-calorie malnutrition, substance use disorder, depression, portal and splenic venous thrombosis, and certain endoscopic procedures. CONCLUSION: Developing APFC during index hospitalization for AP is linked to higher readmission rates, more inpatient complications, longer LOS, and increased healthcare costs. Knowing predictors of readmission can help target high-risk patients, reducing healthcare burdens.

Adding yeast extract to culture medium enhances replication of the avian coronavirus infectious bronchitis virus in chicken embryo kidney cells.

Infectious bronchitis virus (IBV), an avian coronavirus, can be isolated and cultured in tracheal organ cultures (TOCs), embryonated eggs and cell cultures, the first two of which are commonly used for viral isolation. Previous studies have suggested that foetal bovine serum (FBS) can inhibit coronavirus replication in cell cultures. In this study, the replication of IBV in chicken embryo kidney (CEK) cell cultures and the Leghorn hepatocellular carcinoma (LMH) cell line was assessed using two different cell culture media containing FBS or yeast extract (YE) and two different IBV strains. The highest concentrations of viral genomes were observed when the cell culture medium (CEK) contained YE. Similar results were observed in LMH cells. Examination of the infectivity by titration demonstrated that the cell lysate from CEK cell cultures in a medium including YE contained a higher median embryo infectious dose than that from CEK cell cultures in a medium containing FBS. These results indicate that improved replication of IBV in cell cultures can be achieved by replacing FBS with YE in the cell culture medium.

FDG PET in a Patient on a GLP-1 Agonist/Insulin Secretagogue.

ABSTRACT: With the increase in use of GLP-1 receptor agonists such as semaglutide (Ozempic, Wegovy, Rybelsus) in the population, nuclear medicine physicians should be aware of the possibility of nondiagnostic FDG PET scans due to these medications, which work partly by increasing insulin secretion. We demonstrate a case where a patient's use of such a medication presumptively led to muscular and myocardial uptake, complicating scan interpretation considerably. Clinicians should be aware of the presence of these drugs and their potential effect on biodistribution in FDG PET. Further study is needed to best understand the effects of these medications on FDG biodistribution.

Neighborhood Deprivation is Associated With Hospital Length of Stay, Discharge Disposition, and Readmission Rates for Patients Who Survive Hospitalization With Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: Traumatic brain injury (TBI) is a leading cause of disability in the United States. Limited research exists on the influence of area-level socioeconomic status and outcomes after TBI. This study investigated the correlation between the Area Deprivation Index (ADI) and (1) 90-day hospital readmission rates, (2) facility discharge, and (3) prolonged (≥5 days) hospital length of stay (LOS). METHODS: Single-center retrospective review of adult (18 years or older) patients who were admitted for TBI during 2018 was performed. Patients were excluded if they were admitted for management of a chronic or subacute hematoma. We extracted relevant clinical and demographic data including sex, comorbidities, age, body mass index, smoking status, TBI mechanism, and national ADI. We categorized national ADI rankings into quartiles for analysis. Univariate, multivariate, and area under the receiver operating characteristic curve (AUROC) analyses were performed to assess the relationship between ADI and 90-day readmission, hospital LOS, and discharge disposition. RESULTS: A total of 523 patients were included in final analysis. Patients from neighborhoods in the fourth ADI quartile were more likely to be Black (P = .007), have a body mass index ≥30 kg/m2 (P = .03), have a Charlson Comorbidity Index ≥5 (P = .004), and have sustained a penetrating TBI (P = .01). After controlling for confounders in multivariate analyses, being from a neighborhood in the fourth ADI quartile was independently predictive of 90-day hospital readmission (odds ratio [OR]: 1.35 [1.12-1.91], P = .011) (model AUROC: 0.82), discharge to a facility (OR: 1.46 [1.09-1.78], P = .03) (model AUROC: 0.79), and prolonged hospital LOS (OR: 1.95 [1.29-2.43], P = .015) (model AUROC: 0.85). CONCLUSION: After adjusting for confounders, including comorbidities, TBI mechanism/severity, and age, higher ADI was independently predictive of longer hospital LOS, increased risk of 90-day readmission, and nonhome discharge. These results may help establish targeted interventions to identify at-risk patients after TBI.

A hybrid swarm intelligence algorithm for region-based image fusion.

This paper proposes a novel multi-hybrid algorithm named DHPN, using the best-known properties of dwarf mongoose algorithm (DMA), honey badger algorithm (HBA), prairie dog optimizer (PDO), cuckoo search (CS), grey wolf optimizer (GWO) and naked mole rat algorithm (NMRA). It follows an iterative division for extensive exploration and incorporates major parametric enhancements for improved exploitation operation. To counter the local optima problems, a stagnation phase using CS and GWO is added. Six new inertia weight operators have been analyzed to adapt algorithmic parameters, and the best combination of these parameters has been found. An analysis of the suitability of DHPN towards population variations and higher dimensions has been performed. For performance evaluation, the CEC 2005 and CEC 2019 benchmark data sets have been used. A comparison has been performed with differential evolution with active archive (JADE), self-adaptive DE (SaDE), success history based DE (SHADE), LSHADE-SPACMA, extended GWO (GWO-E), jDE100, and others. The DHPN algorithm is also used to solve the image fusion problem for four fusion quality metrics, namely, edge-based similarity index ( Q A B / F ), sum of correlation difference (SCD), structural similarity index measure (SSIM), and artifact measure ( N A B / F ). The average Q A B / F = 0.765508 , S C D = 1.63185 , S S I M = 0.726317 , and N A B / F = 0.006617 shows the best combination of results obtained by DHPN with respect to the existing algorithms such as DCH, CBF, GTF, JSR and others. Experimental and statistical Wilcoxon's and Friedman's tests show that the proposed DHPN algorithm performs significantly better in comparison to the other algorithms under test.

Insights into calcific aortic valve stenosis: a comprehensive overview of the disease and advancing treatment strategies.

Aortic valve stenosis is a disease characterized by thickening and narrowing of the aortic valve (AV), most commonly due to calcification, which leads to left ventricular outflow obstruction called calcific aortic valve disease (CAVD). CAVD presents as a progressive clinical syndrome with cardiorespiratory symptoms, often with rapid deterioration. The modern-day pathophysiology of CAVD involves a complex interplay of genetic factors, chronic inflammation, lipid deposition, and valve calcification, with early CAVD stages resembling atherosclerosis. Various imaging modalities have been used to evaluate CAVD, with a recent trend of using advanced imaging to measure numerous AV parameters, such as peak jet velocity. Significant improvements in mortality have been achieved with transcatheter AV repair, but numerous therapeutics and modalities are being researched to delay the progression of CAVD. This article aims to provide a comprehensive review of CAVD, explore recent developments, and provide insights into future treatments with various novel modalities.

Fasting pancreatic polypeptide predicts incident microvascular and macrovascular complications of type 2 diabetes: An observational study.

AIMS: Pancreatic polypeptide (PP) is elevated in people with vascular risk factors such as type 2 diabetes or increased visceral fat. We investigated potential relationships between PP and microvascular and macrovascular complications of diabetes. MATERIALS AND METHODS: Animal study: Subcutaneous PP infusion for 4 weeks in high fat diet mouse model. Retinal mRNA submitted for Ingenuity Pathway Analysis. Human study: fasting PP measured in 1478 participants and vascular complications recorded over median 5.5 (IQR 4.9-5.8) years follow-up. RESULTS: Animal study: The retinal transcriptional response to PP was indicative of cellular stress and damage, and this footprint matched responses described in previously published studies of retinal disease. Of mechanistic importance the transcriptional landscape was consistent with upregulation of folliculin, a recently identified susceptibility gene for diabetic retinopathy. Human study: Adjusting for established risk factors, PP was associated with prevalent and incident clinically significant retinopathy (odds ratio (OR) 1.289 (1.107-1.501) p = 0.001; hazard ratio (HR) 1.259 (1.035-1.531) p = 0.0213), albuminuria (OR 1.277 (1.124-1.454), p = 0.0002; HR 1.608 (1.208-2.141) p = 0.0011), and macrovascular disease (OR 1.021 (1.006-1.037) p = 0.0068; HR 1.324 (1.089-1.61), p = 0.0049), in individuals with type 2 diabetes, and progression to diabetes in non-diabetic individuals (HR 1.402 (1.081-1.818), p = 0.0109). CONCLUSIONS: Elevated fasting PP is independently associated with vascular complications of diabetes and affects retinal pathways potentially influencing retinal neuronal survival. Our results suggest possible new roles for PP-fold peptides in the pathophysiology of diabetes complications and vascular risk stratification.

Virtual reality as an engaging and enjoyable method for delivering emergency clinical simulation training: a prospective, interventional study of medical undergraduates.

BACKGROUND: It is a requirement that medical students are educated in emergencies and feel well prepared for practice as a doctor, yet national surveys show that many students feel underprepared. Virtual reality (VR), combined with 360-degree filming, provides an immersive, realistic, and interactive simulation experience. Unlike conventional in-person simulation, it is scalable with reduced workforce demands. We sought to compare students' engagement and enjoyment of VR simulation to desktop computer-based simulation. METHODS: We conducted a prospective, interventional, evaluation study. The study was carried out on final year medical students undertaking their Pre-Foundation Assistantship (n = 116) at Imperial College School of Medicine (ICSM) in London. We compared objective engagement, subjective engagement, and subjective enjoyment of VR simulation to desktop computer-based simulation using cardiac arrest and life-threatening asthma scenarios. Engagement was measured objectively using students' physiological parameters, including heart rate and eye tracking, and facilitator observations using the validated 'Behavioural Engagement Related to Instruction' (BERI) protocol. Students' subjective engagement and enjoyment levels were measured using a post-session survey. RESULTS: Students' maximum heart rates were significantly higher during VR simulation with a mean difference of 4.2 beats per minute (3.2 to 5.2, p < 0.001), and eye tracking showed they spent a significantly greater mean percentage of time of 6.4% (5.1 to 7.7, p < 0.001) focusing on the scenarios in VR compared to standard desktop. Qualitative data showed students enjoyed and felt engaged with the sessions, which provided a safe space for learning. CONCLUSIONS: Our study shows that students found VR simulations enjoyable and were more engaged compared to standard desktop simulation. This suggests that 360-degree VR simulation experiences provide students with immersive, realistic training, which is scalable, giving them the unique opportunity to manage emergencies and work within emergency teams, which would not typically occur during traditional training.

First use of a new extended reality tool for preoperative planning in coronary artery bypass surgery: a case-report.

A 73-year-old male presented with angina symptoms and was diagnosed with three-vessel coronary artery disease by use of computed tomography angiography and coronary angiography. This diagnosis necessitated coronary artery bypass grafting (CABG) surgery. A custom made AI-driven algorithm was used to generate a patient-specific three-dimensional coronary artery model from computed tomography angiography imaging data. This framework enabled precise segmentation and reconstruction of the coronary vasculature, yielding an accurate anatomical and pathological representation. Subsequently, this generated model was integrated into a novel extended reality tool for preoperative planning and intraoperative guidance in CABG surgery. Both preoperatively and intraoperatively, the tool augmented spatial orientation and facilitated precise stenosis localization, thereby enhancing the surgeon's operative proficiency. This case report underscores the utility of advanced extended reality tools in cardiovascular surgery, emphasizing their pivotal role in refining surgical planning and execution.

Studying phonon coherence with a quantum sensor.

Nanomechanical oscillators offer numerous advantages for quantum technologies. Their integration with superconducting qubits shows promise for hardware-efficient quantum error-correction protocols involving superpositions of mechanical coherent states. Limitations of this approach include mechanical decoherence processes, particularly two-level system (TLS) defects, which have been widely studied using classical fields and detectors. In this manuscript, we use a superconducting qubit as a quantum sensor to perform phonon number-resolved measurements on a piezoelectrically coupled phononic crystal cavity. This enables a high-resolution study of mechanical dissipation and dephasing in coherent states of variable size ( n ¯ ≃ 1 - 10 phonons). We observe nonexponential relaxation and state size-dependent reduction of the dephasing rate, which we attribute to TLS. Using a numerical model, we reproduce the dissipation signatures (and to a lesser extent, the dephasing signatures) via emission into a small ensemble (N = 5) of rapidly dephasing TLS. Our findings comprise a detailed examination of TLS-induced phonon decoherence in the quantum regime.

In-depth analysis of ChatGPT's performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions.

ChatGPT has garnered attention as a multifaceted AI chatbot with potential applications in medicine. Despite intriguing preliminary findings in areas such as clinical management and patient education, there remains a substantial knowledge gap in comprehensively understanding the chances and limitations of ChatGPT's capabilities, especially in medical test-taking and education. A total of n = 2,729 USMLE Step 1 practice questions were extracted from the Amboss question bank. After excluding 352 image-based questions, a total of 2,377 text-based questions were further categorized and entered manually into ChatGPT, and its responses were recorded. ChatGPT's overall performance was analyzed based on question difficulty, category, and content with regards to specific signal words and phrases. ChatGPT achieved an overall accuracy rate of 55.8% in a total number of n = 2,377 USMLE Step 1 preparation questions obtained from the Amboss online question bank. It demonstrated a significant inverse correlation between question difficulty and performance with rs = -0.306; p < 0.001, maintaining comparable accuracy to the human user peer group across different levels of question difficulty. Notably, ChatGPT outperformed in serology-related questions (61.1% vs. 53.8%; p = 0.005) but struggled with ECG-related content (42.9% vs. 55.6%; p = 0.021). ChatGPT achieved statistically significant worse performances in pathophysiology-related question stems. (Signal phrase = "what is the most likely/probable cause"). ChatGPT performed consistent across various question categories and difficulty levels. These findings emphasize the need for further investigations to explore the potential and limitations of ChatGPT in medical examination and education.

Hybrid 3C-silicon carbide-lithium niobate integrated photonic platform.

In this paper, we demonstrate a novel hybrid 3C-silicon carbide-lithium niobate (3C-SiC-LN) platform for passive and active integrated nanophotonic devices enabled through wafer bonding. These devices are fabricated by etching the SiC layer, with the hybrid optical mode power distributed between SiC and LN layers through a taper design. We present a racetrack resonator-based electro-optic (EO) phase shifter where the resonator is fabricated in SiC while using LN for EO-effect (r33≈ 27 pm/V). The proposed phase shifter demonstrates efficient resonance wavelength tuning with low voltage-length product (Vπ.Lπ ≈ 2.18 V cm) using the EO effect of LN. This hybrid SiC-LN platform would enable high-speed, low-power, and miniaturized photonic devices (e.g., modulators, switches, filters) operable over a broad range of wavelengths (visible to infrared) with applications in both classical and quantum nanophotonics.

A Multimodel-Based Screening Framework for C-19 Using Deep Learning-Inspired Data Fusion.

In recent times, there has been a notable rise in the utilization of Internet of Medical Things (IoMT) frameworks particularly those based on edge computing, to enhance remote monitoring in healthcare applications. Most existing models in this field have been developed temperature screening methods using RCNN, face temperature encoder (FTE), and a combination of data from wearable sensors for predicting respiratory rate (RR) and monitoring blood pressure. These methods aim to facilitate remote screening and monitoring of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and COVID-19. However, these models require inadequate computing resources and are not suitable for lightweight environments. We propose a multimodal screening framework that leverages deep learning-inspired data fusion models to enhance screening results. A Variation Encoder (VEN) design proposes to measure skin temperature using Regions of Interest (RoI) identified by YoLo. Subsequently, the multi-data fusion model integrates electronic records features with data from wearable human sensors. To optimize computational efficiency, a data reduction mechanism is added to eliminate unnecessary features. Furthermore, we employ a contingent probability method to estimate distinct feature weights for each cluster, deepening our understanding of variations in thermal and sensory data to assess the prediction of abnormal COVID-19 instances. Simulation results using our lab dataset demonstrate a precision of 95.2%, surpassing state-of-the-art models due to the thoughtful design of the multimodal data-based feature fusion model, weight prediction factor, and feature selection model.

Virtual Reality for Pain and Anxiety Management in Cardiac Surgery and Interventional Cardiology.

Pain and anxiety are common in patients undergoing cardiac surgery and percutaneous cardiac interventions. Virtual reality (VR) is an emerging non-pharmacological tool for pain and anxiety management. However, its application around cardiac procedures remains relatively unexplored. In this review, we perform a targeted non-systematic literature review to assess the current state-of-the-art of VR for pain and anxiety management in patients undergoing cardiac procedures. Contexts of interest were preprocedural, periprocedural, and postprocedural applications. Existing trials show inconsistent results. The majority of studies in the preprocedural (7 studies, n = 302), periprocedural (1 study, n = 99), and postprocedural stage (4 studies, n = 214) demonstrate significant reduction of pain and anxiety through VR distraction therapy or VR patient education. However, larger-scale trials (2 preprocedural studies [n = 233], 1 periprocedural study [n = 32], 2 postprocedural studies [n = 300]) report no effect. Current literature on effectiveness of VR for pain and anxiety management in cardiac surgery and interventional cardiology remains inconclusive.

Applications of Artificial Intelligence for Pediatric Cancer Imaging.

Artificial intelligence (AI) is transforming medical imaging of adult patients. However, its utilization in pediatric oncology imaging remains constrained, in part due to the inherent data scarcity associated with childhood cancers. Pediatric cancers are rare, and imaging technologies are evolving rapidly, leading to insufficient data of a particular type to effectively train these algorithms. The small market size of pediatrics compared to adults could also contribute to this challenge, as market size is a driver of commercialization. This article provides an overview of the current state of AI applications for pediatric cancer imaging, including applications for medical image acquisition, processing, reconstruction, segmentation, diagnosis, staging, and treatment response monitoring. While current developments are promising, impediments due to diverse anatomies of growing children and nonstandardized imaging protocols have led to limited clinical translation thus far. Opportunities include leveraging reconstruction algorithms to achieve accelerated low-dose imaging and automating the generation of metric-based staging and treatment monitoring scores. Transfer-learning of adult-based AI models to pediatric cancers, multi-institutional data sharing, and ethical data privacy practices for pediatric patients with rare cancers will be keys to unlocking AI's full potential for clinical translation and improved outcomes for these young patients.

Characterisation of the tracheal transcriptional response of chickens to chronic infection with Mycoplasma synoviae.

Mycoplasma synoviae causes infectious synovitis and respiratory tract infections in chickens and is responsible for significant economic losses in the poultry industry. Effective attachment and colonisation of the trachea is critical for the persistence of the organism and progression of the disease it causes. The respiratory tract infection is usually sub-clinical, but concurrent infection with infectious bronchitis virus (IBV) is known to enhance the pathogenicity of M. synoviae. This study aimed to explore differentially expressed genes in the tracheal mucosa, and their functional categories, during chronic infection with M. synoviae, using a M. synoviae-IBV infection model. The transcriptional profiles of the trachea were assessed 2 weeks after infection using RNA sequencing. In chickens infected with M. synoviae or IBV, only 1 or 8 genes were differentially expressed compared to uninfected chickens, respectively. In contrast, the M. synoviae-IBV infected chickens had 621 upregulated and 206 downregulated genes compared to uninfected chickens. Upregulated genes and their functional categories were suggestive of uncontrolled lymphoid cell proliferation and an ongoing pro-inflammatory response. Genes associated with anti-inflammatory effects, pathogen removal, apoptosis, regulation of the immune response, airway homoeostasis, cell adhesion and tissue regeneration were downregulated. Overall, transcriptional changes in the trachea, 2 weeks after infection with M. synoviae and IBV, indicate immune dysregulation, robust inflammation and a lack of cytotoxic damage during chronic infection. This model provides insights into the pathogenesis of chronic infection with M. synoviae.

Racial Disparities in Outcomes Following Surgical Fixation of Traumatic Thoracolumbar Fractures: A National Database Analysis.

OBJECTIVE: This study aims to assess race as an independent risk factor for postoperative complications after surgical fixation of traumatic thoracolumbar fractures for African American and Asian American patients compared with White patients. METHODS: The 2011-2021 American College of Surgeons - National Surgical Quality Improvement Program (ACS-NSQIP) dataset was used to identify patients undergoing fusion surgeries for thoracolumbar spine fractures. Patient comorbidity burden was assessed using a modified 5-item frailty index score (mFI-5). Chi-squared and ANOVA tests were used to compare baseline clinical characteristics between groups. Multivariate analysis was performed to compare African American and Asian American patients with White patients controlling for age, BMI, and American Society of Anesthesiologists (ASA) score. RESULTS: African American patients experienced longer operative times compared to Asian American and White patients (3.74 ± 1.87 hours vs. 3.04 ± 1.71 hours and 3.48 ± 1.81 hours, P < 0.001). African American and Asian American patients demonstrated higher comorbidity burden with mFI-5>2 compared to White patients (30.7% and 25.6% vs. 19.9%, P < 0.001). African American and Asian American patients had a higher risk of postoperative complications than White patients (22.4% and 20% vs. 19.7%, P < 0.001). African American race was an independent risk factor of postoperative 30-day morbidity (OR 1.19, CI 1.11-1.28, P < 0.001). CONCLUSIONS: African American and Asian American patients undergoing thoracolumbar fusion surgeries exhibit disproportionate comorbidity burden, longer LOS, and greater postoperative complications compared with White patients. Furthermore, the African American race was associated with an increased rate of 30-day postoperative complications.