Taraxasterol attenuates zearalenone-induced kidney damage in mice by modulating oxidative stress and endoplasmic reticulum stress.

Taraxasterol is one of the bioactive ingredients from traditional Chinese herb Taraxacum, which exhibits multiple pharmacological activities and protective effects. However, the underlying influence and mechanism of its use against kidney damage caused from zearalenone (ZEA) remain unexplored. The ZEA-induced kidney damage model of mice was established by feeding diets containing ZEA (2 mg/kg), and taraxasterol (5 and 10 mg/kg) was administered by gavage for 28 days. Results demonstrated taraxasterol increased average daily gain (ADG) and average daily feed intake (ADFI), reduced feed-to-gain ratio (F/G) and kidney index of mice induced by ZEA. Taraxasterol alleviated histopathological changes of kidney, reduced ZEA residue and the levels of blood urea nitrogen (BUN), uric acid (UA), and creatinine (CRE). Concurrently, taraxasterol reduced the contents of oxidative stress indicator reactive oxygen species (ROS) and malondialdehyde (MDA), and increased the activities of antioxidant enzymes catalase (CAT), total superoxide dismutase (T-SOD), and glutathione peroxidase (GSH-Px). Further, taraxasterol up-regulated the mRNA and protein expression of nuclear factor erythroid-2-related factor 2 (Nrf2), GSH-Px, NAD(P)H quinone oxidoreductase 1 (NQO1), and heme oxygenase-1 (HO-1), and down-regulated the mRNA and protein expression of KELCH like ECH associated protein (Keap1) in Nrf2/Keap1 pathway. Taraxasterol down-regulated the mRNA and protein expression of immunoglobulin binding protein (Bip), C/EBP homologous protein (CHOP), Bcl-2 associated X (Bax), cysteine protease (Caspase)-12, and Caspase-3, and up-regulated B-cell lymphoma 2 (Bcl-2) expression in endoplasmic reticulum stress pathway. This study suggests that taraxasterol attenuates ZEA-induced mouse kidney damage through the modulation of Nrf2/Keapl pathway to play antioxidant role and endoplasmic reticulum stress pathway to enhance anti-apoptotic ability. It will provide a basis for taraxasterol as a potential drug to prevent and treat ZEA-induced kidney damage.

Multidimensional frailty as a predictor of mortality among older adults: a systematic review and meta-analysis.

OBJECTIVE: This systematic review examined studies that assessed the relationship between mortality risk and multidimensional frailty. The pooled risk of mortality was estimated via a meta-analysis. DESIGN: A systematic review and meta-analysis. METHODS: A systematic search for potentially eligible literature was conducted on January 2, 2023, using five electronic databases: Web of Science, CINAHL, PubMed, the Cochrane Library and Embase. This review included cohort or longitudinal studies examining the association between multidimensional frailty/prefrailty and mortality in older adults. The quality of the included studies was evaluated via the Quality in Prognosis Studies (QUIPS) tool. Two independent researchers identified eligible studies and extracted the data. The data analyses were performed via STATA, version 15.0. RESULTS: A total of 24 studies with 34,664 participants were included. The 24 studies were published between 2012 and 2022, with most studies being performed in Italy (n = 16). The sample sizes of the included studies ranged from 71 to 12,020. Most included studies were conducted in hospital settings. The QUIPS bias assessment results showed that the most frequent source of potential bias was study confounding. The meta-analysis results showed that multidimensional frailty was a significant predictor of mortality (HR = 5.48, 95% CI = 3.91-7.67, p < 0.001). In addition, multidimensional prefrailty was also a significant predictor of mortality (HR = 2.56, 95% CI = 2.17-3.02, p < 0.001). The results of the meta-analysis using the ORs revealed that multidimensional frailty was a risk factor for mortality in older people (OR = 4.59, 95% CI = 2.47-8.55, p < 0.05). CONCLUSIONS AND IMPLICATIONS: This systematic review of the relationship between multidimensional frailty and mortality found that multidimensional frailty/prefrailty is a predictor of mortality. More studies should be conducted in community dwelling populations and nursing homes.

Glioma stem cells remodel immunotolerant microenvironment in GBM and are associated with therapeutic advancements.

Glioma is the most common primary tumor of the central nervous system (CNS). Glioblastoma (GBM) is incurable with current treatment strategies. Additionally, the treatment of recurrent GBM (rGBM) is often referred to as terminal treatment, necessitating hospice-level care and management. The presence of the blood-brain barrier (BBB) gives GBM a more challenging or "cold" tumor microenvironment (TME) than that of other cancers and gloma stem cells (GSCs) play an important role in the TME remodeling, occurrence, development and recurrence of giloma. In this review, our primary focus will be on discussing the following topics: niche-associated GSCs and macrophages, new theories regarding GSC and TME involving pyroptosis and ferroptosis in GBM, metabolic adaptations of GSCs, the influence of the cold environment in GBM on immunotherapy, potential strategies to transform the cold GBM TME into a hot one, and the advancement of GBM immunotherapy and GBM models.

Med-Query: Steerable Parsing of 9-DoF Medical Anatomies with Query Embedding.

Automatic parsing of human anatomies at the instance-level from 3D computed tomography (CT) is a prerequisite step for many clinical applications. The presence of pathologies, broken structures or limited field-of-view (FOV) can all make anatomy parsing algorithms vulnerable. In this work, we explore how to leverage and implement the successful detection-then-segmentation paradigm for 3D medical data, and propose a steerable, robust, and efficient computing framework for detection, identification, and segmentation of anatomies in CT scans. Considering the complicated shapes, sizes, and orientations of anatomies, without loss of generality, we present a nine degrees of freedom (9-DoF) pose estimation solution in full 3D space using a novel single-stage, non-hierarchical representation. Our whole framework is executed in a steerable manner where any anatomy of interest can be directly retrieved to further boost inference efficiency. We have validated our method on three medical imaging parsing tasks: ribs, spine, and abdominal organs. For rib parsing, CT scans have been annotated at the rib instance-level for quantitative evaluation, similarly for spine vertebrae and abdominal organs. Extensive experiments on 9-DoF box detection and rib instance segmentation demonstrate the high efficiency and effectiveness of our framework (with the identification rate of 97.0% and the segmentation Dice score of 90.9%), compared favorably against several strong baselines (e.g., CenterNet, FCOS, and nnU-Net). For spine parsing and abdominal multi-organ segmentation, our method achieves competitive results on par with stateof-the-art methods on the public CTSpine1K dataset and FLARE22 competition, respectively. Our annotations, code, and models are available at: Med-Query.

A highly sensitive electrochemical immunosensor based on rGO-PEI-Ag nanocomposites for the detection of tilmicosin.

A label-free electrochemical immunosensor was developed to rapidly detect tilmicosin (TMC) residues in pork and milk. The immunosensor was constructed by immobilizing a high-affinity monoclonal antibody against TMC on an rGO-PEI-Ag nanocomposite-modified electrode. The rGO-PEI-Ag nanocomposites were prepared by mixing polyethyleneimine (PEI) modified reduced graphene oxide (rGO) with AgNO3 solution. The prepared rGO-PEI-Ag nanocomposites showed good redox activity and conductivity, as characterized by ultraviolet-visible spectroscopy (UV-Vis), transmission electron microscopy (TEM), and X-ray diffraction (XRD). During the preparation process, staphylococcal protein A (SPA) was added to targetedly bind the Fc segment of the monoclonal antibody. The immunosensor showed a low detection limit (LOD) of 0.0013 ng/mL, a linear range of 0.01-100 ng/mL, and recoveries ranging from 92.77 to 100.02% in pork and 92.26-101.23% in milk. Furthermore, the immunosensor exhibited good stability, reproducibility, and specificity in detecting TMC in pork and milk real samples.

Hybrid Operating Room for the Treatment of Spetzler-Martin Grade III-V Brain Arteriovenous Malformation: An Institutional Experience.

AIM: To report our institutional experience of the one-stop treatment of Spetzler-Martin grade (SMG) III-V brain arteriovenous malformations (BAVMs) in a hybrid operating room. MATERIAL AND METHODS: Clinical data obtained from all the patients with SMG III-V BAVMs who underwent one-stop treatment in a hybrid operating room were analyzed. The measures included imaging characteristics, intraoperative blood loss, postoperative complications, residual lesions, and the presence of postoperative recurrence. Outcomes were assessed using the Glasgow outcome scale (GOS) score at six months post-surgery. RESULTS: A total of 16 patients were included in this study, 7 of whom underwent endovascular embolization followed by microsurgical resection and 9 underwent intraoperative cerebral angiography-assisted microsurgery. The average intraoperative blood loss was 473.3 mL. A remnant of BAVMs was found on the intraoperative cerebral angiography of one patient. Two patients underwent decompressive craniectomy due to postoperative cerebral swelling, including one patient with occipital lobe cerebral infarction and aphasia. No mortality was recorded. At the six-month postoperative follow-up visit, the GOS scores were 3 (n=4, 25.0%), 4 (n=4, 25.0%), and 5 (n=8, 50.0%). No recurrence was noted on brain digital subtraction angiography (DSA) in any of the postoperative reexaminations. CONCLUSION: A hybrid operating room can fully combine the advantages of microsurgery and endovascular interventions, allowing for a high resection rate in the surgical treatment of SMG III-V BAVMs and a low rate of postoperative complications.

Expert Consensus on the Application of Stem Cells in Psoriasis Research and Clinical Trials.

Psoriasis is an immune-mediated, chronic, relapsing, inflammatory, systemic disease induced by individual-environmental interactions, and is often lifelong because of the difficulty of treatment. In recent years, a variety of targeted therapies, including biologics, have improved the lesions and quality of life of most psoriasis patients, but they still do not address the problem of relapse and may be associated with decreased efficacy or adverse events such as infections over time. Therefore, there is an urgent need for breakthroughs in psoriasis treatment and in relapse-delaying and non-pharmacologic strategies, and stem cell therapy for psoriasis has emerged. In recent years, research on stem cell therapy for psoriasis has received a lot of attention, however, there is no reference standard as well as consensus in this field of research. Therefore, according to the latest consensus and guidelines, combined with relevant literature reports, clinical practice experience and the results of discussions with experts, this consensus specifies the types of stem cells commonly used in the treatment of psoriasis, the methods, dosages, and routes of stem cell therapy for psoriasis, as well as the clinical evaluations (efficacy and safety) of stem cell therapy for psoriasis. In addition, this consensus also provides normative standards for the processes of collection, preparation, preservation and quality control of stem cells and their related products, as well as recommendations for the management of stem cells during infusion for the treatment of psoriasis. This consensus provides the latest specific reference standards and practice guidelines for the field of stem cell therapy for psoriasis.

Corrigendum: Patients with juvenile idiopathic arthritis have decreased clonal diversity in the CD8+ T cell repertoire response to influenza vaccination.

[This corrects the article DOI: 10.3389/fimmu.2024.1306490.].

Health-related quality of life among pediatric patients with acute lymphoblastic leukemia: An exploratory cross-sectional study.

BACKGROUND: Improved survival rates broadened the pediatric oncology focus to include health-related quality of life (HRQoL). This cross-sectional study aimed to examine HRQoL by treatment phase and disease risk level in pediatric patients with B-cell acute lymphoblastic leukemia (B-ALL), including those in early survivorship. PROCEDURE: A subset of data from a larger prospective cohort study was analyzed. Data were collected from 73 patients (73 parent reports and 28 self-reports). Parent proxy and self-report PROMIS measures assessed HRQoL across treatment phases (early intensive, maintenance, and off treatment) and disease risk groups (standard vs high). Analyses assessed the relationship between parent proxy and patient self-reports and the differences in HRQoL among treatment phases and risk groups. RESULTS: Parent proxy reports generally indicated worse fatigue, pain interference, and mobility compared with patient self-reports. Self-reports in the early intensive treatment group suggested worse depressive symptoms, fatigue, mobility, and upper extremity function compared with those in later phases. Parent proxy reports showed worse fatigue and depressive symptoms in early intensive treatment group relative to those in later phases. Patient self-reports in the maintenance group demonstrated the best peer relationships scores. Parent proxy reports in the high-risk group reported significantly higher depressive symptoms and fatigue compared with the standard-risk group. CONCLUSIONS: Differences in HRQoL suggest targets for further assessment and intervention. The early treatment and immediate post-survivorship periods may represent particularly critical time points. Longitudinal studies with larger and diverse samples should further explore HRQoL trajectories in this population.

Exploring Porous Flow Behavior of the Decomposed Gas from CH4 Hydrate in Clayey Sediments by Molecular Dynamics Simulation.

A fundamental understanding of the fluid flow mechanism during CH4 hydrate dissociation in nanoscale clayey sediments from the molecular perspective can provide invaluable information for macroscale natural gas hydrate (NGH) exploration. In this work, the fluid flow behaviors of the decomposed gas from CH4 hydrate within clayey nanopores under different temperature conditions are revealed by molecular dynamics (MD) simulation. The simulation results indicate that the key influencing factors of gas-water flow in nanoscale clayey sediments include the diffusion and the random migration of gas molecules. The influencing mechanisms of fluid flow in nanopores are closely related with the temperature conditions. Under a low temperature condition, the gas diffusion process is impeded by the secondary hydrate formation, leading to the decline in gas transport velocity within nanopores. However, it is still noteworthy that the gas-water fluid flow channels are not completely blocked by the occurrence of secondary hydrate. Under a high temperature condition, the significant phenomenon of water migration during gas flow is observed, which can be ascribed to the gas-liquid entrainment effect in nanopores of the clayey sediment. These results may provide valuable implications and fundamental evidence for improving gas production efficiency in future field tests of NGH exploitation in marine sediments.

Diagnosis of Alzheimer's disease: Towards accuracy and accessibility.

Alzheimer's disease (AD) is a serious dementia afflicting aging population and is characterized by cognitive decline, amyloid-ß plaques, and neurofibrillary tangles. AD substantially impairs the life quality of the victims and poses a heavy burden on the society at large. The number of people with dementia due to AD, prodromal AD, and preclinical AD is estimated to stand at roughly 3.2, 69, and 315 million worldwide, respectively. Current clinical diagnosis is based on clinical symptoms, and clinical research demonstrated that positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers had excellent diagnostic performance. However, the application of CSF biomarker tests and PET are restricted by the invasiveness and high cost. The presence of clinical symptoms means that AD pathology has been progressing for many years, and only a few drugs have been approved for the traetemnt of AD. Therefore, early diagnosis is extremely important for controlling the outcomes caused by AD. In this review, we provided an overview of developing clinical diagnostic criteria, diagnostic strategies under clinical research, developing blood based-biomarker assays, and promising nanotechnologically-based assays.

Correction: Surface mobility gradient and emergent facilitation in glassy films.

Correction for 'Surface mobility gradient and emergent facilitation in glassy films' by Qiang Zhai et al., Soft Matter, 2024, https://doi.org/10.1039/D4SM00221K.

A Study on Predicting the Deviation of Jet Trajectory Falling Point under the Influence of Random Wind.

As one of the main external factors affecting the fire extinguishing accuracy of sprinkler systems, it is necessary to analyze and study random wind. However, in practical applications, there is little research on the impact of random wind on sprinkler fire extinguishing points. To address this issue, a new random wind acquisition system was constructed in this paper, and a method for predicting jet trajectory falling points in Random Forest (RF) under the influence of random wind was proposed, and compared with the commonly used prediction model Support Vector Machine (SVM). The method in this article reduces the error in the x direction of the 50 m prediction result from 2.11 m to 1.53 m, the error in the y direction from 0.64 m to 0.6 m, and the total mean absolute error (MAE) from 31.3 to 23.5. Simultaneously, predict the falling points of jet trajectory at different distances under the influence of random wind, to demonstrate the feasibility of the proposed method in practical applications. The experimental results show that the system and method proposed in this article can effectively improve the influence of random wind on the falling points of a jet trajectory. In summary, the image acquisition system and error prediction method proposed in this article have many potential applications in fire extinguishing.

Firefighting Water Jet Trajectory Detection from Unmanned Aerial Vehicle Imagery Using Learnable Prompt Vectors.

This research presents an innovative methodology aimed at monitoring jet trajectory during the jetting process using imagery captured by unmanned aerial vehicles (UAVs). This approach seamlessly integrates UAV imagery with an offline learnable prompt vector module (OPVM) to enhance trajectory monitoring accuracy and stability. By leveraging a high-resolution camera mounted on a UAV, image enhancement is proposed to solve the problem of geometric and photometric distortion in jet trajectory images, and the Faster R-CNN network is deployed to detect objects within the images and precisely identify the jet trajectory within the video stream. Subsequently, the offline learnable prompt vector module is incorporated to further refine trajectory predictions, thereby improving monitoring accuracy and stability. In particular, the offline learnable prompt vector module not only learns the visual characteristics of jet trajectory but also incorporates their textual features, thus adopting a bimodal approach to trajectory analysis. Additionally, OPVM is trained offline, thereby minimizing additional memory and computational resource requirements. Experimental findings underscore the method's remarkable precision of 95.4% and efficiency in monitoring jet trajectory, thereby laying a solid foundation for advancements in trajectory detection and tracking. This methodology holds significant potential for application in firefighting systems and industrial processes, offering a robust framework to address dynamic trajectory monitoring challenges and augment computer vision capabilities in practical scenarios.

A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction.

In the quest for sustainable urban development, precise quantification of urban green space is paramount. This research delineates the implementation of a Cosine Adaptive Particle Swarm Optimization Long Short-Term Memory (CAPSO-LSTM) model, utilizing a comprehensive dataset from Beijing (1998-2021) to train and test the model. The CAPSO-LSTM model, which integrates a cosine adaptive mechanism into particle swarm optimization, advances the optimization of long short-term memory (LSTM) network hyperparameters. Comparative analyses are conducted against conventional LSTM and Partical Swarm Optimization (PSO)-LSTM frameworks, employing mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) as evaluative benchmarks. The findings indicate that the CAPSO-LSTM model exhibits a substantial improvement in prediction accuracy over the LSTM model, manifesting as a 66.33% decrease in MAE, a 73.78% decrease in RMSE, and a 57.14% decrease in MAPE. Similarly, when compared to the PSO-LSTM model, the CAPSO-LSTM model demonstrates a 58.36% decrease in MAE, a 65.39% decrease in RMSE, and a 50% decrease in MAPE. These results underscore the efficacy of the CAPSO-LSTM model in enhancing urban green space area prediction, suggesting its significant potential for aiding urban planning and environmental policy formulation.

Ultrasound-assisted deep eutectic solvents extraction of polysaccharides from Loquat leaf: Process optimization and bioactivity study.

Loquat leaves are the by-product of loquat fruit production. Polysaccharides are one of the main active ingredients in loquat leaves. In this study, polysaccharides were extracted from loquat leaves by ultrasonic-assisted deep eutectic solvents (DESs) extraction method. Further, the extracted crude loquat leaf polysaccharides (CLLP) were purified and separated via S-8 resin and DEAE-52 cellulose column chromatography, respectively. Additionally, the effects of polysaccharides on activity of sperm in boar semen preserved in medium at 17 °C, were evaluated preliminarily. DES, composed of choline chloride/ethylene glycol (1:6, molar ratio), was proved to be the suitable solvent for LLP extraction. The optimized extraction conditions were water content 44 %, liquid-solid ratio 1:29 (g/g), extraction temperature 61 °C and extraction time 98 min. Under these conditions, the LLP yield was 57.82 ± 1.50 mg/g. A homogeneous polysaccharide (LLP1-2, Mw: 2.17 × 104 Da) was isolated from CLLP. Its total sugar, uronic acid and protein contents were 76.31 ± 1.25 %, 14.19 ± 0.67 % and 3.28 ± 0.42 %, respectively. Further, 800 µg/mL LLP1-2 could effectively enhance the antioxidant activity of sperm. This study laid a foundation for DESs and column chromatography in the field of polysaccharide extraction and separation, proving that LLP can be used as a natural antioxidant for sperm preservation.

Outcomes of a dexamethasone-prednisone combination treatment course for status asthmaticus.

OBJECTIVES: Dexamethasone has become the standard of care for pediatric patients with status asthmaticus in the emergency department (ED) setting. Inpatient providers often must decide between continuing the second dose of dexamethasone or transitioning to prednisone. The effectiveness of receiving dexamethasone followed by prednisone (combination therapy) compared to only prednisone or dexamethasone remains unclear. This study compares patient characteristics and ED reutilization/hospital readmission outcomes of dexamethasone, prednisone, and combination therapy for inpatient asthma management. METHODS: A retrospective study was conducted at our tertiary children's hospital of children aged 2 to 18 years hospitalized between March 2016 and December 2018 with a primary discharge diagnosis of asthma, reactive airway disease, or bronchospasm. The differences between steroid groups were compared using Fisher's exact or Chi-square tests for categorical variables, and a Kruskal-Wallis test for continuous variables. A multivariable logistic regression was performed to analyze ED reutilization and hospital readmission rates. RESULTS: 1697 subjects met inclusion criteria. 115 (6.8%) patients received dexamethasone, 597 (35.2%) received prednisone, and 985 (58.0%) received combination therapy. Patients prescribed combination therapy had a lower exacerbation severity than patients prescribed prednisone, but higher severity than patients prescribed dexamethasone (p < .001, p = .001, respectively). Dexamethasone and combination therapy were not associated with increased 30-day ED reutilization/hospital readmissions compared to prednisone (p > .05). CONCLUSIONS: In our study, most patients hospitalized for status asthmaticus received combination therapy. Despite the differences in severity between steroid groups, outcomes of combination therapy and dexamethasone monotherapy, as measured by frequency of ED reutilizations/hospital readmissions, are comparable to prednisone monotherapy.

Patients with juvenile idiopathic arthritis have decreased clonal diversity in the CD8+ T cell repertoire response to influenza vaccination.

Recurrent exposures to a pathogenic antigen remodel the CD8+ T cell compartment and generate a functional memory repertoire that is polyclonal and complex. At the clonotype level, the response to the conserved influenza antigen, M158-66 has been well characterized in healthy individuals, but not in patients receiving immunosuppressive therapy or with aberrant immunity, such as those with juvenile idiopathic arthritis (JIA). Here we show that patients with JIA have a reduced number of M158-66 specific RS/RA clonotypes, indicating decreased clonal richness and, as a result, have lower repertoire diversity. By using a rank-frequency approach to analyze the distribution of the repertoire, we found several characteristics of the JIA T cell repertoire to be akin to repertoires seen in healthy adults, including an amplified RS/RA-specific antigen response, representing greater clonal unevenness. Unlike mature repertoires, however, there is more fluctuation in clonotype distribution, less clonotype stability, and more variable IFNy response of the M158-66 specific RS/RA clonotypes in JIA. This indicates that functional clonal expansion is altered in patients with JIA on immunosuppressive therapies. We propose that the response to the influenza M158-66 epitope described here is a general phenomenon for JIA patients receiving immunosuppressive therapy, and that the changes in clonal richness and unevenness indicate a retarded and uneven generation of a mature immune response.

Aerosol sources and transport paths co-control the atmospheric bacterial diversity over the coastal East China Sea.

Airborne bacteria along with chemical composition of aerosols were investigated during five sampling seasons at an offshore island of the East China Sea. Bacterial diversity was the lowest in spring, the highest in winter, and similar between the autumns of 2019 and 2020, suggesting remarkably seasonal variation but little interannual change. Geodermatophilus (Actinobacteria) was the indicator genus of mineral dust (MD) showed higher proportion in spring than in other seasons. Mastigocladopsis_PCC-10914 (Cyanobacteria) as the indicator of sea salt (SS) demonstrated the highest percentages in both autumns, when the air masses mainly passed over the ocean prior to the sampling site. The higher proportions of soil-derived genera Rubellimicrobium and Craurococcus (both Proteobacteria) and extremophile Chroococcidiopsis_SAG_2023 (Cyanobacteria) were found in summer and winter, respectively. Our study explores the linkage between aerosol source and transport path and bacterial composition, which has implication to understanding of land-sea transmission of bacterial taxa.

Machine learning risk stratification for high-risk infant follow-up of term and late preterm infants.

BACKGROUND: Term and late preterm infants are not routinely referred to high-risk infant follow-up programs at neonatal intensive care unit (NICU) discharge. We aimed to identify NICU factors associated with abnormal developmental screening and develop a risk-stratification model using machine learning for high-risk infant follow-up enrollment. METHODS: We performed a retrospective cohort study identifying abnormal developmental screening prior to 6 years of age in infants born ≥34 weeks gestation admitted to a level IV NICU. Five machine learning models using NICU predictors were developed by classification and regression tree (CART), random forest, gradient boosting TreeNet, multivariate adaptive regression splines (MARS), and regularized logistic regression analysis. Performance metrics included sensitivity, specificity, accuracy, precision, and area under the receiver operating curve (AUC). RESULTS: Within this cohort, 87% (1183/1355) received developmental screening, and 47% had abnormal results. Common NICU predictors across all models were oral (PO) feeding, follow-up appointments, and medications prescribed at NICU discharge. Each model resulted in an AUC > 0.7, specificity >70%, and sensitivity >60%. CONCLUSION: Stratification of developmental risk in term and late preterm infants is possible utilizing machine learning. Applying machine learning algorithms allows for targeted expansion of high-risk infant follow-up criteria. IMPACT: This study addresses the gap in knowledge of developmental outcomes of infants ≥34 weeks gestation requiring neonatal intensive care. Machine learning methodology can be used to stratify early childhood developmental risk for these term and late preterm infants. Applying the classification and regression tree (CART) algorithm described in the study allows for targeted expansion of high-risk infant follow-up enrollment to include those term and late preterm infants who may benefit most.