https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2026.1730470/full https://www.frontiersin.org/files/Articles/1730470/fped-14-1730470-HTML/image_m/fped-14-1730470-t003.jpg Table 3. Comparison of intraoperative and postoperative oxygenation, recovery time, and postoperativ https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2026.1749293/full https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-g001.jpg Figure 1. Intubation measurement procedure guided by FIVE. (a) Carina; (b) 1 cm above the carina; (c https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-g002.jpg Figure 2. Flow diagram of study participants. https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-t001.jpg Table 1. General characteristics of infants by age group. https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-t002.jpg Table 2. Comparison of the accuracy of ETT positioning between the formula method and FIVE guidance. https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-g003.jpg Figure 3. Correlation of weight and height with intubation depth under FIVE guidance in infants aged https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-t003.jpg Table 3. Spearman analysis of gender, age in months, height, weight, and BSA with intubation depth u https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-t004.jpg Table 4. Establishment of a new intubation depth prediction formula using linear regression. https://www.frontiersin.org/files/Articles/1749293/fmed-13-1749293-HTML/image_m/fmed-13-1749293-g004.jpg Figure 4. Bland-Altman agreement analysis between FIVE-guided intubation depth and formula-based cal https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2026.1767391/full https://www.frontiersin.org/files/Articles/1767391/fmed-13-1767391-HTML/image_m/fmed-13-1767391-g001.jpg Figure 1. DKK2 is highly expressed in AML. (A) Box plot for DKK2 levels in normal and cancer tissues https://www.frontiersin.org/files/Articles/1767391/fmed-13-1767391-HTML/image_m/fmed-13-1767391-g002.jpg Figure 2. Knockdown DKK2 inhibited AML cell growth, migration, and induced apoptosis. (A) The mRNA e https://www.frontiersin.org/files/Articles/1767391/fmed-13-1767391-HTML/image_m/fmed-13-1767391-g003.jpg Figure 3. Up-regulated DKK2 promotes AML cell growth, proliferation, and metastasis. (A) The mRNA ex https://www.frontiersin.org/files/Articles/1767391/fmed-13-1767391-HTML/image_m/fmed-13-1767391-t001.jpg Table 1. The Binding energy of suitable drug candidates for targeting DKK2. https://www.frontiersin.org/files/Articles/1767391/fmed-13-1767391-HTML/image_m/fmed-13-1767391-g004.jpg Figure 4. Molecular docking simulation of DKK2 and evodiamine. (A) Three-dimensional (3D) interactio https://www.frontiersin.org/files/Articles/1767391/fmed-13-1767391-HTML/image_m/fmed-13-1767391-g005.jpg Figure 5. Overexpression DKK2 can rescue the anti-tumor effect for evodiamine. (A) CCK-8 assay was u https://www.frontiersin.org/files/Articles/1767391/fmed-13-1767391-HTML/image_m/fmed-13-1767391-g006.jpg Figure 6. DKK2 overexpression accelerates AML progression of THP-1 cells in NSG immunodeficient mice https://www.frontiersin.org/journals/sports-and-active-living/articles/10.3389/fspor.2026.1714194/full https://www.frontiersin.org/files/Articles/1714194/fspor-08-1714194-HTML/image_m/fspor-08-1714194-g001.jpg Figure 1. Mechanisms of injury and comprehensive prevention pathways in Ultimate Frisbee. A conceptu https://www.frontiersin.org/files/Articles/1714194/fspor-08-1714194-HTML/image_m/fspor-08-1714194-g002.jpg Figure 2. PRISMA 2020 flow diagram describing the literature search and study selection process. The https://www.frontiersin.org/files/Articles/1714194/fspor-08-1714194-HTML/image_m/fspor-08-1714194-t001.jpg Table 1. Summary of epidemiological study characteristics, injury definitions, and reported incidenc https://www.frontiersin.org/files/Articles/1714194/fspor-08-1714194-HTML/image_m/fspor-08-1714194-g003.jpg Figure 3. Injury distribution and types in Ultimate Frisbee. Proportional anatomical distribution of https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2026.1828695/full https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-g001.jpg Figure 1. Flowchart of patient enrollment. AR, allergic rhinitis; SLIT, sublingual immunotherapy. https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-t001.jpg Table 1. The baseline characteristics of the patients. https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-g002.jpg Figure 2. Variations in TNSS (A), TMS (B), CSMS (C), and VAS (D) scores at baseline, 1.5 years, and https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-g003.jpg Figure 3. Variations in MLK score at baseline, 1.5 years, and 3 years of SLIT treatment. MLK, modifi https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-g004.jpg Figure 4. Representative endoscopic findings at baseline, 1.5 years, and 3 years of SLIT in 2 patien https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-g005.jpg Figure 5. Variations in serum total IgE (A) and Eosinophil counts (B) at baseline and after 3 years https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-g006.jpg Figure 6. (A) Severity of patients’ symptoms at baseline, 1.5 years, and 3 years of SLIT treatment; https://www.frontiersin.org/files/Articles/1828695/fimmu-17-1828695-HTML/image_m/fimmu-17-1828695-t002.jpg Table 2. Analysis of adverse events during the study. https://www.frontiersin.org/journals/education/articles/10.3389/feduc.2026.1812349/full https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-t001.jpg Table 1. Summary of student survey statistics. https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-g001.jpg Figure 1. PRIGEL internship model. https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-t002.jpg Table 2. PRIGEL internship time structure. https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-t003.jpg Table 3. Evaluation results from 10 experts on the industry internship model. https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-t004.jpg Table 4. Content validity of the internship industry model. https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-t005.jpg Table 5. Expert and practitioner evaluation of the PRIGEL guidebook. https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-t006.jpg Table 6. Content validity of the guidebook. https://www.frontiersin.org/files/Articles/1812349/feduc-11-1812349-HTML/image_m/feduc-11-1812349-t007.jpg Table 7. User responses from lecturers, students, and industry representatives. https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2026.1827817/full https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-t001.jpg Table 1. Nutritional differences in two-group silage (n = 10). https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-g001.jpg Figure 1. (A) Alpha diversity indices of silage bacteria, (B) beta-diversity analysis of silage bact https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-g002.jpg Figure 2. (A) Phylum-level composition and (B) genus-level composition. https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-g003.jpg Figure 3. Radar chart showing the sensory flavor traits of distinct metabolites, along with a networ https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-g004.jpg Figure 4. (A) Volcano plot illustrating the screening of differential metabolites, (B) OPLS-DA analy https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-g005.jpg Figure 5. Receiver operating characteristic (ROC) analysis was used to assess the predictive accurac https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-g006.jpg Figure 6. (A) Bubble plot of KEGG pathway enrichment analysis, (B) VIP analysis of differential meta https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-t002.jpg Table 2. Composition of differential metabolites in two types of silage. https://www.frontiersin.org/files/Articles/1827817/fmicb-17-1827817-HTML/image_m/fmicb-17-1827817-g007.jpg Figure 7. Correlation analysis between silage metabolomics and microbiome. This heatmap illustrates https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2026.1786880/full https://www.frontiersin.org/files/Articles/1786880/fnins-20-1786880-HTML-r2/image_m/fnins-20-1786880-g001.jpg Figure 1. CONSORT flow diagram shows participant enrollment, allocation, follow-up, and analysis, to https://www.frontiersin.org/files/Articles/1786880/fnins-20-1786880-HTML-r2/image_m/fnins-20-1786880-g002.jpg Figure 2. Characterization of dried A. subulatum fruits used for the preparation of MA2-24 extract u https://www.frontiersin.org/files/Articles/1786880/fnins-20-1786880-HTML-r2/image_m/fnins-20-1786880-t001.jpg Table 1. CNS vital data points. https://www.frontiersin.org/files/Articles/1786880/fnins-20-1786880-HTML-r2/image_m/fnins-20-1786880-g003.jpg Figure 3. CNS vital signs–shifting attention test (CNSVS-SAT) outcomes showing changes from baseline https://www.frontiersin.org/files/Articles/1786880/fnins-20-1786880-HTML-r2/image_m/fnins-20-1786880-g004.jpg Figure 4. CNS vital signs–symbol digit coding (CNSVS-SDC) test outcomes showing changes from baselin https://www.frontiersin.org/files/Articles/1786880/fnins-20-1786880-HTML-r2/image_m/fnins-20-1786880-g005.jpg Figure 5. CNS vital signs–Stroop test outcomes show changes from baseline. (A) Simple reaction time https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2026.1819089/full https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-t001.jpg Table 1. Descriptive statistics. https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-g001.jpg Figure 1. Trajectory of the VoA by age in the subjective age dimension. Compiled based on the 2018, https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-g002.jpg Figure 2. Trajectory of the VoA by age in the perceived old age dimension. Compiled based on the 201 https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-t002.jpg Table 2. Growth curve model regression results for the VoA among older adults. https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-g003.jpg Figure 3. Age trajectories of subjective age for older adults across generations. Compiled based on https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-g004.jpg Figure 4. Age trajectories of perceived old age for older adults across generations. Compiled based https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-g005.jpg Figure 5. Balance test plot. Compiled based on the 2018, 2020, and 2023 waves of CLASS data. https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-t003.jpg Table 3. Summary of average treatment effect results. https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-g006.jpg Figure 6. Age trajectories of subjective age for older adults across generations after matching. Com https://www.frontiersin.org/files/Articles/1819089/fpubh-14-1819089-HTML/image_m/fpubh-14-1819089-g007.jpg Figure 7. Age trajectories of perceived old age for older adults across generations after matching. https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1552007/full https://www.frontiersin.org/files/Articles/1552007/fonc-15-1552007-HTML-r1/image_m/fonc-15-1552007-g001.jpg Figure 1. Comparison of LAPTM4B-24 (24kDa) and LAPTM4B-35 (35kDa) protein structures, highlighting k https://www.frontiersin.org/files/Articles/1552007/fonc-15-1552007-HTML-r1/image_m/fonc-15-1552007-g002.jpg Figure 2. Role and regulatory mechanism of LAPTM4B in tumors. (A) Overexpression of LAPTM4B leads to https://www.frontiersin.org/files/Articles/1552007/fonc-15-1552007-HTML-r1/image_m/fonc-15-1552007-t001.jpg Table 1. LAPTM4B with Interacting proteins and potential functions. https://www.frontiersin.org/files/Articles/1552007/fonc-15-1552007-HTML-r1/image_m/fonc-15-1552007-g003.jpg Figure 3. lncRNA-miRNA regulation of LAPTM4B gene expression in cancer. https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2026.1781882/full https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-t001.jpg Table 1. General data on patients with colorectal cancer. https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-t002.jpg Table 2. Duration time of OIPN. https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-t003.jpg Table 3. Frequency of OIPN. https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-t004.jpg Table 4. OIPN severity classification. https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-t005.jpg Table 5. Comparison of nutritional status in patients with colorectal cancer. https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-g001.jpg Figure 1. Metabolite classification proportion (%). https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-g002.jpg Figure 2. (A,B) Permutation sequencing results of PLS-DA mode in positive ion (+) mode in the OIPN v https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-g003.jpg Figure 3. (A–C) Distribution and change trend of differential metabolites of OIPN vs. CONT in the wh https://www.frontiersin.org/files/Articles/1781882/fnut-13-1781882-HTML/image_m/fnut-13-1781882-g004.jpg Figure 4. (A–C) Histogram of influence factors in OIPN vs. CONT samples on the metabolic pathway in https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1669835/full https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-g001.jpg Figure 1. Flowchart of patient inclusion. AD, Alzheimer’s disease; AV45-PET, 18F-florbetapir positro https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-t001.jpg Table 1. Comparison of patient demographics, clinical features, and neuropsychological scales betwee https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-g002.jpg Figure 2. Schematic diagram and scatter bar chart of brain regions with differences. The brain diagr https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-t002.jpg Table 2. Comparison of gut microbiota diversity between the ID and non-ID groups. https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-g003.jpg Figure 3. The differential presentation of gut microbiota. (A) The top 30 relative abundance of micr https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-g004.jpg Figure 4. PET-microbiota-PSQI relationships. (A,B) Correlation matrix heat maps of gut microbiota wi https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-g005.jpg Figure 5. Observed versus predicted FDG uptake in right and left thalamus regions. This scatter plot https://www.frontiersin.org/files/Articles/1669835/fneur-16-1669835-HTML/image_m/fneur-16-1669835-t003.jpg Table 3. Multiple correlation analysis of the ID group following centered log-ratio (CLR) transforma https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2025.1572968/full https://www.frontiersin.org/files/Articles/1572968/fphar-16-1572968-HTML/image_m/fphar-16-1572968-t001.jpg Table 1. Participants demographics. https://www.frontiersin.org/files/Articles/1572968/fphar-16-1572968-HTML/image_m/fphar-16-1572968-t002.jpg Table 2. Opioid type and dosage frequency (N = 36 medicines, based on 30 prescription). https://www.frontiersin.org/files/Articles/1572968/fphar-16-1572968-HTML/image_m/fphar-16-1572968-t003.jpg Table 3. Duration of opioid prescription (N = 36 medicines, based on 30 prescription).