Importance of soil ecoenzyme stoichiometry for efficient polycyclic aromatic hydrocarbon biodegradation.

Efficient remediation of soil contaminated by polycyclic aromatic hydrocarbons (PAHs) is challenging. Several studies have focused on the role of degrading consortia. However, to determine whether soil ecoenzyme stoichiometry influences PAH degradation under biostimulation and bioaugmentation, this study initially characterized soil ecoenzyme stoichiometry via a PAH degradation experiment and subsequently designed a validation experiment to answer this question. The results showed that inoculation of PAH degradation consortia ZY-PHE plus vanillate efficiently degraded phenanthrene with a K value of 0.471 (depending on first-order kinetics), followed by treatment with ZY-PHE and control. Ecoenzyme stoichiometry data revealed that the EEAC:N, vector length and angle increased before day five and decreased during the degradation process. In contrast, EEAN:P decreased and then increased. These results indicated that the rapid PAH degradation period induced more C limitation and organic P mineralization. Correlation analysis indicated that the degradation rate K was negatively correlated with vector length, EEAC:P, and EEAN:P, suggesting that C limitation and relatively less efficient P mineralization could inhibit biodegradation. Therefore, incorporating liable carbon and acid phosphatase or soluble P promoted PAH degradation in soils with ZY-PHE. This study provides novel insights into the relationship between soil ecoenzyme stoichiometry and PAH degradation. It is suggested that soil ecoenzyme stoichiometry be evaluated before designing bioremeiation stragtegies for PAH contanminated soils.

Integration of Co Single Atoms and Ni Clusters on Defect-Rich ZrO2 for Strong Photothermal Coupling Boosts Photocatalytic CO2 Reduction.

We report a solvothermal method for the synthesis of an oxygen vacancy-enriched ZrO2 photocatalyst with Co single atoms and Ni clusters immobilized on the surface. This catalyst presents superior performance for the reduction of CO2 in H2O vapor, with a CO yield reaching 663.84 µmol g-1 h-1 and a selectivity of 99.52%. The total solar-to-chemical energy conversion efficiency is up to 0.372‰, which is among the highest reported values. The success, on one hand, depends on the Co single atoms and Ni clusters for both extended spectrum absorption and serving as dual-active centers for CO2 reduction and H2O dissociation, respectively; on the other hand, this is attributed to the enhanced photoelectric and thermal effect induced by concentrated solar irradiation. We demonstrate that an intermediate impurity state is formed by the hybridization of the d-orbital of single-atom Co with the molecular orbital of H2O, enabling visible-light-driven excitation over the catalyst. In addition, Ni clusters play a crucial role in altering the adsorption configuration of CO2, with the localized surface plasmon resonance effect enhancing the activation and dissociation of CO2 induced by visible-near-infrared light. This study provides valuable insights into the synergistic effect of the dual cocatalyst toward both efficient photothermal coupling and surface redox reactions for solar CO2 reduction.

Complete mitochondrial genome sequence and phylogenetic analysis of Tylopilus brunneirubens (Boletales, Basidiomycota).

Tylopilus brunneirubens is a common species in southern China. It is known for brown to dark brown pileus, white context turning reddish brown or rust brown when touched and distinct reticulation on the upper stem. However, little is known about its mitochondrial genome and its relationship with other boletes. Our analysis revealed that the mitochondrial genome of this species is a circular DNA molecule that spans 32,389 bp. It contains 15 core protein-coding genes, 24 transfer RNA genes, and two ribosomal RNA genes. The base composition of the mitochondrial genome is as follows: A (37.20%), C (11.32%), G (12.48%), and T (39.00%), with a GC content of 23.80%. Furthermore, a phylogenetic tree based on 24 mitochondrial genomes provided valuable insights into the phylogenetic relationships of Tylopilus brunneirubens with other boletes for the first time.

Effectiveness and Safety of Pyrotinib-Based Therapy in the Treatment of HER2-Positive Breast Cancer Patients with Brain Metastases: A Multicenter Real-World Study.

BACKGROUND: Approximately 30% to 50% of patients with human epidermal growth factor receptor 2-positive metastatic breast cancer develop brain metastasis (BMs). Pyrotinib has shown promising efficacy in these patients. However, real-world evidence supporting its use is scarce. Therefore, we evaluate the efficacy and safety of pyrotinib-based regimens in the real world. MATERIALS AND METHODS: We enrolled patients with BMs from various healthcare facilities in China's Shandong region and used an updated breast-graded prognostic assessment (breast-GPA) to predict survival outcomes. RESULTS: Efficacy and toxicity were assessed in 101 patients. Overall, the median progression-free survival (PFS) was 11.0 months (95% CI, 7.6-14.4 months). PFS was shorter in patients with a breast-GPA of 0 to 2.0 (P< .001). Previous treatment with pertuzumab plus trastuzumab (P = .039) and varying numbers of BMs (P = .028) had a significant positive correlation with PFS. Additionally, radiotherapy (P = .033) for BMs, especially pyrotinib concurrent with radiotherapy (P = .013), significantly prolonged the PFS. In patients with a breast-GPA of 0 to 2.0, a significant difference in PFS was observed depending on whether the brain was the first metastatic site (P< .001). Furthermore, a breast-GPA (0-2.0 vs. 2.5-4.0), and radiotherapy for BMs were found to be independent predictors of PFS. Overall, the objective response rate was 42.6%, while the disease control rate was 88.1%. Diarrhea emerged as the most common adverse event. CONCLUSION: Pyrotinib-based therapy is effective and tolerable in human epidermal growth factor receptor 2-positive metastatic breast cancer with BMs. Patients who underwent radiotherapy for BMs, particularly those who received pyrotinib concurrently with radiotherapy, exhibited a more favorable prognosis.

Systematic Evaluation of Ultrasonic In-Line Inspection Techniques for Oil and Gas Pipeline Defects Based on Bibliometric Analysis.

The global reliance on oil and gas pipelines for energy transportation is increasing. As the pioneering review in the field of ultrasonic defect detection for oil and gas pipelines based on bibliometric methods, this study employs visual analysis to identify the most influential countries, academic institutions, and journals in this domain. Through cluster analysis, it determines the primary trends, research hotspots, and future directions in this critical field. Starting from the current global industrial ultrasonic in-line inspection (ILI) detection level, this paper provides a flowchart for selecting detection methods and a table for defect comparison, detailing the comparative performance limits of different detection devices. It offers a comprehensive perspective on the latest ultrasonic pipeline detection technology from laboratory experiments to industrial practice.

A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data.

BACKGROUND: Survival prediction using high-dimensional molecular data is a hot topic in the field of genomics and precision medicine, especially for cancer studies. Considering that carcinogenesis has a pathway-based pathogenesis, developing models using such group structures is a closer mimic of disease progression and prognosis. Many approaches can be used to integrate group information; however, most of them are single-model methods, which may account for unstable prediction. METHODS: We introduced a novel survival stacking method that modeled using group structure information to improve the robustness of cancer survival prediction in the context of high-dimensional omics data. With a super learner, survival stacking combines the prediction from multiple sub-models that are independently trained using the features in pre-grouped biological pathways. In addition to a non-negative linear combination of sub-models, we extended the super learner to non-negative Bayesian hierarchical generalized linear model and artificial neural network. We compared the proposed modeling strategy with the widely used survival penalized method Lasso Cox and several group penalized methods, e.g., group Lasso Cox, via simulation study and real-world data application. RESULTS: The proposed survival stacking method showed superior and robust performance in terms of discrimination compared with single-model methods in case of high-noise simulated data and real-world data. The non-negative Bayesian stacking method can identify important biological signal pathways and genes that are associated with the prognosis of cancer. CONCLUSIONS: This study proposed a novel survival stacking strategy incorporating biological group information into the cancer prognosis models. Additionally, this study extended the super learner to non-negative Bayesian model and ANN, enriching the combination of sub-models. The proposed Bayesian stacking strategy exhibited favorable properties in the prediction and interpretation of complex survival data, which may aid in discovering cancer targets.

MOF-derived multi-"hotspot" 3D Au/MOF-808 (Zr) nanostructures as SERS substrates for the ultrasensitive determination of thiram.

A convenient self-assembly method is proposed for synthesis of 3D Au/MOF-808 (Zr) composite nanostructures with a cerium metal-organic framework loaded with gold nanoparticles. We combine adsorption properties of MOF materials with surface plasmon resonance of noble metals to construct hotspot-dense 3D Au/MOF-808 (Zr) SERS substrates, by using a two-step method of solvothermal and reduction reactions. The results show that optimal SERS substrates are obtained from a volume ratio of gold nanoparticles to MOF-808 (Zr) solution of 4:1 and a self-assembly time of 2 h. Rhodamine 6G (R6G) is used as a molecular probe to characterize and analyze SERS properties of substrates of 3D Au/MOF-808 (Zr) prepared under the optimal process conditions, where the substrates are capable to detect R6G concentrations down to 10-10 M with a relative standard deviation of 8.81%. Finally, we applied the SERS substrates of 3D Au/MOF-808 (Zr) to the detection of pesticide thiram, and establish a quantitative determination method. 3D Au/MOF-808 (Zr) provides a sensitive detection of thiram in lake water by SERS with a detection limit of 1.49 × 10-9 M. Application tests show that a SERS enhancement factor of the MOF-based SERS substrates for the detection of thiram can be significantly increased to 5.91 × 105. Thus, the above results indicate that such substrate has high sensitivity, good adsorption, homogeneity, and reproducibility, which can be extended for sensitive detection of pesticide residues in food and environment.

Efficacy and safety of pyrotinib combined with albumin-bound paclitaxel as first-line treatment for HER2-positive metastatic breast cancer in patients previously treated with adjuvant and/or neoadjuvant trastuzumab therapy: The stage 1 results of a single-arm, phase 2 prospective clinical trial.

OBJECTIVE: It has been observed that the prognosis of patients with HER2-positive metastatic breast cancer has improved significantly with HER2-targeted agents. However, there is still a lack of evidence regarding first-line anti-HER2 treatment options for patients who have received adjuvant and/or neoadjuvant trastuzumab for HER2-positive metastatic breast cancer. Besides, there are no reliable markers that can predict the efficacy of anti-HER2 treatment in these patients. METHODS: Patients who have received adjuvant and/or neoadjuvant trastuzumab for HER2-positive metastatic breast cancer were enrolled. Pyrotinib plus albumin-bound paclitaxel were used as first-line treatment. The primary endpoint was the objective response rate (ORR). The safety profile was also assessed. In order to explore predictive biomarkers using Olink technology, blood samples were collected dynamically. RESULTS: From December 2019 to August 2023, the first stage of the study involved 27 eligible patients. It has not yet reached the median PFS despite the median follow-up being 17.8 months. Efficacy evaluation showed that the ORR was 92.6%, and the DCR was 100%. Adverse events of grade 3 or higher included diarrhoea (29.6%), leukopenia (11.1%), neutropenia (25.9%), oral mucositis (3.7%), and hand-foot syndrome (3.7%). Toll-like receptor 3 (TLR3) and Proto-oncogene tyrosine-protein kinase receptor (RET) were proteins with significant relevance to PFS in these patients. CONCLUSIONS: This study demonstrates that pyrotinib plus albumin-bound paclitaxel as a first-line treatment regimen shows good efficacy and manageable safety for patients who have received adjuvant and/or neoadjuvant trastuzumab for HER2-positive metastatic breast cancer. Besides, a significant association was identified between the expression levels of TLR3 and RET and the PFS in patients.

Sedimentary Paleoenvironment and Organic Matter Enrichment Characteristics of Lacustrine Shahezi Shale in Songliao Basin: Insights from the Continental Scientific Drilling.

The lacustrine shale of the Shahezi Formation in the Songliao Basin has obvious organic matter enrichment characteristics and great potential for oil and gas resources. At present, the understanding of the sedimentary paleoenvironment and organic matter enrichment characteristics of the lacustrine shale of the Shahezi Formation is relatively weak. Therefore, taking the international continental scientific drilling Program (ICDP) borehole Songke-2 (SK-2) with continuous and whole Shahezi cores as the research object, combined with organic geochemistry, elemental geochemistry, and logging data, the sedimentary paleoenvironment and organic matter enrichment mechanism were studied. The results show that the organic matter of Shahezi shale is generally in the high to over mature stage. The kerogen type of organic matter is mainly II2-III. The organic matter is mainly derived from the lake basin's own algae and terrestrial higher plants. The total organic carbon (TOC) content of Shahezi shale is relatively high, and the TOC is mainly distributed between 1% and 2%. The Shahezi Formation is dominated by clay shale and siliceous shale, and experienced moderate chemical weathering during deposition. According to the analysis of organic geochemistry and elemental geochemistry data, the paleoenvironment of organic matter deposition in Shahezi shale was dominated by warm and humid climate in the early stage, and then experienced multiple cooling and arid periods. The climate type turned to semihumid-semiarid, with stable terrigenous debris input, low deposition rate, brackish water salinity and oxygen-rich-oxygen-poor water environment. The sedimentary period of Shahezi Formation is in the Cretaceous oceanic anoxic Aptian-Albian stage. During the oceanic anoxic event, the anoxic sedimentary environment and the frequent volcanic activity have an important impact on the organic matter enrichment. The oceanic anoxic event and volcanic activity are the main causes of water body hypoxia in the lake basin. The nutrients brought by volcanic activity are also one of the reasons for promoting the growth of lake basin organisms, creating good conditions for organic matter enrichment. The enrichment of organic matter in Shahezi Formation is the result of the interaction and coupling of various factors such as paleoclimate, paleoenvironment, paleoproductivity, water environment, terrestrial input, and major geological events. And, the organic matter enrichment model of Shahezi Formation shale is established.

Resource utilization of MSWI fly ash supporting TiO2/BiOCl nanocomposite for enhanced photocatalytic degradation of sodium isopropyl xanthate: Mechanism and performance evaluation.

The removal of organic pollutants in water environments and the resource utilization of solid waste are two pressing issues around the world. Facing the increasing pollution induced by discharge of mining effluents containing sodium isopropyl xanthate (SIPX), in this work, municipal solid waste incineration fly ash (MSWI FA) was pretreated by hydrothermal method to produce stabilized FA, which was then innovatively used as support for the construction of FA/TiO2/BiOCl nanocomposite (FTB) with promoted photocatalytic activity under visible light and natural sunlight. When the content of FA was 20 wt% and the mass ratio of TiO2 to BiOCl was 4:6, a remarkable performance for the optimal FTB (20-FTB-2) was achieved. Characterizations demonstrated that TiO2 and BiOCl uniformly dispersed on FA contributing to high surface area and broad light adsorption of FTB, which exhibits excellent adsorption capacity and light response ability. Build in electric field formed in the interface of TiO2/BiOCl heterojunction revealed by density functional theory calculations accelerated the separation of photoinduced e- and h+, leading to high efficiency for SIPX degradation. The synergetic effect combined with adsorption and photocatalytic degradation endowed 20-FTB-2 superior SIPX removal efficiency over 99% within 30 min under visible light and natural sunlight irradiation. The photocatalytic degradation pathways of SIPX were determined through theoretical calculations and characterizations, and the toxic byproduct CS2 was effectively eliminated through oxidation of •O2-. For 20-FTB-2, reusability of photocatalyst was showed by cycle tests, also the concentrations of main heavy metals (Pb, Zn, Cu, Cr, and Cd) in the liquid phases released during photocatalyst preparation process (< 1 mg/L) and photodegradation process (< 8.5 µg/L) proved the satisfactory stability with low toxicity. This work proposed a novel strategy to develop efficient and stable support-based photocatalysts by utilizing MSWI FA and realize its resource utilization.

A novel method for quantitative determination of multiple substances using Raman spectroscopy combined with CWT.

The identification of mixed solutions is a challenging and important subject in chemical analysis. In this paper, we propose a novel workflow that enables rapid qualitative and quantitative detection of mixed solutions. We use a methanol-ethanol mixed solution as an example to demonstrate the superiority of this workflow. The workflow includes the following steps: (1) converting Raman spectra into Raman images through CWT; (2) using MobileNetV3 as the backbone network, improved multi-label and multi-channel synchronization enables simultaneous prediction of multiple mixture concentrations; and (3) using transfer learning and multi-stage training strategies for training to achieve accurate quantitative analysis. We compare six traditional machine learning algorithms and two deep learning models to evaluate the performance of our new method. The experimental results show that our model has achieved good prediction results when predicting the concentration of methanol and ethanol, and the coefficient of determination R2 is greater than 0.999. At different concentrations, both MAPE and RSD outperform other models, which demonstrates that our workflow has outstanding analytical capabilities. Importantly, we have solved the problem that current quantitative analysis algorithms for Raman spectroscopy are almost unable to accurately predict the concentration of multiple substances simultaneously. In conclusion, it is foreseeable that this non-destructive, automated, and highly accurate workflow can further advance Raman spectroscopy.

Decoding Polysaccharides from Two Pichia Yeasts and Their Molecular Interaction with Wine Fruity Esters.

This study extensively characterized yeast polysaccharides (YPs) from Pichia fermentans (PF) and Pichia kluyveri (PK), with a specific focus on their structural attributes and their interaction with wine fruity esters in a model wine system. By finely tuning enzymatic reactions based on temperature, pH, and enzyme dosage, an optimal YP yield of 77.37% was achieved, with a specific mass ratio of cellulase, pectinase, and protease set at 3:5:2. There were four YP fractions (YPPF-W, YPPF-N, YPPK-W, and YPPK-N) isolated from the two yeasts. YPPF-N and YPPK-N were identified as glucans based on monosaccharide analysis and Fourier-transform infrared spectroscopy analysis. "Specific degradation-methylation-nuclear magnetic" elucidated YPPF-W's backbone structure as 1,3-linked α-l-Man and 1,6-linked α-d-Glc residues, while YPPK-W displayed a backbone structure of 1,3-linked α-Man residues, indicative of a mannoprotein nature. Isothermal titration calorimetry revealed spontaneous interactions between YPPK-W/YPPF-W and fruity esters across temperatures (25-45 °C), with the strongest interaction observed at 30 °C. However, distinct esters exhibited varying interactions with YPPK-W and YPPF-W, attributed to differences in molecular weights and hydrophobic characteristics. While shedding light on these intricate interactions, further experimental data is essential for a comprehensive understanding of yeast polysaccharides' or mannoproteins' impact on fruity esters. This research significantly contributes to advancing our knowledge of yeast polysaccharides' role in shaping the nuanced sensory attributes of wine.

Desertivirga arenae gen. nov., sp. nov. and Desertivirga brevis sp. nov., isolated from desert soil, and reclassification of Pedobacter xinjiangensis as Desertivirga xinjiangensis comb. nov. and Pedobacter mongoliensis as Paradesertivirga mongoliensis gen.nov., comb. nov.

Two novel bacterial strains, designated as SYSU D00823T and SYSU D00873T, were isolated from sandy soil of the Gurbantunggut Desert in Xinjiang, north-west China. SYSU D00823T and SYSU D00873T shared 99.0 % 16S rRNA gene sequence identity, and were both most closely related to Pedobacter xinjiangensis 12157T with 96.1 % and 96.0 % similarities, respectively. Phylogenetic and phylogenomic analyses revealed that the two isolates and P. xinjiangensis 12157T formed a separate distinct cluster in a stable subclade with the nearby species Pedobacter mongoliensis 1-32T, as well as the genera Pararcticibacter and Arcticibacter. Furthermore, P. mongoliensis 1-32T formed a separate deep-branching lineage and did not form a cluster with members of the genus Pedobacter. The average nucleotide identity and digital DNA-DNA hybridization values between SYSU D00823T and SYSU D00873T and related species were well below the thresholds for species delineation (<81.0 % and <24.0 %, respectively). The genomes of SYSU D00823T and SYSU D00873T were 6.19 and 6.43 Mbp in size with 40.4 % and 40.5 % DNA G+C contents, respectively. The predominant fatty acids (>10 %) of SYSU D00823T and SYSU D00873T were iso-C15 : 0, iso-C17 : 0 3-OH and summed feature 3 (C16 : 1 ω7c and/or C16 : 1 ω6c). Menaquinone-7 was the only respiratory quinone. The major polar lipids were phosphatidylethanolamine, glycosphingolipid, aminoglycolipid/glycolipid, aminophospholipid and three or four unidentified polar lipids. These data indicated that strains SYSU D00823T and SYSU D00873T should be assigned to two novel species of a new genus within the family Sphingobacteriaceae, for which the names Desertivirga arenae gen. nov., sp. nov. and Desertivirga brevis sp. nov. are proposed. The type strains are SYSU D00823T (=CGMCC 1.18630T=MCCC 1K04973T=KCTC 82278T) and SYSU D00873T (=CGMCC 1.18629T=MCCC 1K04974T=KCTC 82281T), respectively. Accordingly, the reclassification of P. xinjiangensis as Desertivirga xinjiangensis comb. nov., and P. mongoliensis as Paradesertivirga mongoliensis gen. nov., comb. nov. are also proposed.

Expression of genes related to gonadal development and construction of gonadal DNA methylation maps of Trachinotus blochii under hypoxia.

Chronic hypoxia can affect the growth and metabolism of fish and potentially impact gonadal development through epigenetic regulation. Trachinotus blochii (Golden pompano) is widely cultured near the coast and is sensitive to low oxygen conditions. We found that hypoxia and reoxygenation processes acted on multiple targets on the HPG axis, leading to endocrine disorders. Changes in the expression of key genes in the brain (gnrh), pituitary (fsh and lh), ovaries (cyp19a1a, foxl2, and er), and testes (dmrt1, ar, sox9, and gsdf) were associated with significant decreases in estrogen and testosterone levels. Hypoxia and reoxygenation lead to changes in DNA methylation levels in the gonads. Hypoxia upregulated the expression of dnmt1, dnmt3a, dnmt3b, tet1, and tet2 in females and dnmt3a and dnmt3b in males, while reoxygenation down-regulated the expression of dnmt1, dnmt3a, dnmt3b, tet1, and tet2 in males. Whole genome methylation sequencing showed that the number of differentially methylated regions was highest on chromosome 10 (5192) and lowest on chromosome 24 (275). Differentially methylated genes in females and males, as well as between males and females, were enriched in the oxytocin signaling pathway, fatty acid metabolism pathway, and HIF-1a pathway. In summary, hypoxia and reoxygenation can induce endocrine disorders, affect the expression of HPG axis genes, change the methylation pattern and modification pattern of gonad DNA, and then have potential effects on gonad development.

Generation of allogeneic CAR-NKT cells from hematopoietic stem and progenitor cells using a clinically guided culture method.

Cancer immunotherapy with autologous chimeric antigen receptor (CAR) T cells faces challenges in manufacturing and patient selection that could be avoided by using 'off-the-shelf' products, such as allogeneic CAR natural killer T (AlloCAR-NKT) cells. Previously, we reported a system for differentiating human hematopoietic stem and progenitor cells into AlloCAR-NKT cells, but the use of three-dimensional culture and xenogeneic feeders precluded its clinical application. Here we describe a clinically guided method to differentiate and expand IL-15-enhanced AlloCAR-NKT cells with high yield and purity. We generated AlloCAR-NKT cells targeting seven cancers and, in a multiple myeloma model, demonstrated their antitumor efficacy, expansion and persistence. The cells also selectively depleted immunosuppressive cells in the tumor microenviroment and antagonized tumor immune evasion via triple targeting of CAR, TCR and NK receptors. They exhibited a stable hypoimmunogenic phenotype associated with epigenetic and signaling regulation and did not induce detectable graft versus host disease or cytokine release syndrome. These properties of AlloCAR-NKT cells support their potential for clinical translation.

An all-inclusive model for predicting invasive bacterial infection in febrile infants age 7-60 days.

BACKGROUND: Invasive bacterial infections (IBIs) in febrile infants are rare but potentially devastating. We aimed to derive and validate a predictive model for IBI among febrile infants age 7-60 days. METHODS: Data were abstracted retrospectively from electronic records of 37 emergency departments (EDs) for infants with a measured temperature >=100.4 F who underwent an ED evaluation with blood and urine cultures. Models to predict IBI were developed and validated respectively using a random 80/20 dataset split, including 10-fold cross-validation. We used precision recall curves as the classification metric. RESULTS: Of 4411 eligible infants with a mean age of 37 days, 29% had characteristics that would likely have excluded them from existing risk stratification protocols. There were 196 patients with IBI (4.4%), including 43 (1.0%) with bacterial meningitis. Analytic approaches varied in performance characteristics (precision recall range 0.04-0.29, area under the curve range 0.5-0.84), with the XGBoost model demonstrating the best performance (0.29, 0.84). The five most important variables were serum white blood count, maximum temperature, absolute neutrophil count, absolute band count, and age in days. CONCLUSION: A machine learning model (XGBoost) demonstrated the best performance in predicting a rare outcome among febrile infants, including those excluded from existing algorithms. IMPACT: Several models for the risk stratification of febrile infants have been developed. There is a need for a preferred comprehensive model free from limitations and algorithm exclusions that accurately predicts IBIs. This is the first study to derive an all-inclusive predictive model for febrile infants aged 7-60 days in a community ED sample with IBI as a primary outcome. This machine learning model demonstrates potential for clinical utility in predicting IBI.