Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts.

BACKGROUND: A major challenge in epidemiology is knowing when an exposure effect is large enough to be clinically important, in particular how to interpret a difference in mean outcome in unexposed/exposed groups. Where it can be calculated, the proportion/percentage beyond a suitable cut-point is useful in defining individuals at high risk to give a more meaningful outcome. In this simulation study we compute differences in outcome means and proportions that arise from hypothetical small effects in vulnerable sub-populations. METHODS: Data from over 28,000 mother/child pairs belonging to the Environmental influences on Child Health Outcomes Program were used to examine the impact of hypothetical environmental exposures on mean birthweight, and low birthweight (LBW) (birthweight < 2500g). We computed mean birthweight in unexposed/exposed groups by sociodemographic categories (maternal education, health insurance, race, ethnicity) using a range of hypothetical exposure effect sizes. We compared the difference in mean birthweight and the percentage LBW, calculated using a distributional approach. RESULTS: When the hypothetical mean exposure effect was fixed (at 50, 125, 167 or 250g), the absolute difference in % LBW (risk difference) was not constant but varied by socioeconomic categories. The risk differences were greater in sub-populations with the highest baseline percentages LBW: ranging from 3.1-5.3 percentage points for exposure effect of 125g. Similar patterns were seen for other mean exposure sizes simulated. CONCLUSIONS: Vulnerable sub-populations with greater baseline percentages at high risk fare worse when exposed to a small insult compared to the general population. This illustrates another facet of health disparity in vulnerable individuals.

A Gene Cluster of Mitochondrial Complexes Contributes to the Cognitive Decline of COVID-19 Infection.

"Brain fog," a persistent cognitive impairment syndrome, stands out as a significant neurological aftermath of coronavirus disease 2019 (COVID-19). Yet, the underlying mechanisms by which COVID-19 induces cognitive deficits remain elusive. In our study, we observed an upregulation in the expression of genes linked to the inflammatory response and oxidative stress, whereas genes associated with cognitive function were downregulated in the brains of patients infected with COVID-19. Through single-nucleus RNA sequencing (snRNA-seq) analysis, we found that COVID-19 infection triggers the immune responses in microglia and astrocytes and exacerbates oxidative stress in oligodendrocytes, oligodendrocyte progenitors (OPCs), and neurons. Further investigations revealed that COVID-19 infection elevates LUC7L2 expression, which inhibits mitochondrial oxidative phosphorylation (OXPHOS) and suppresses the expression of mitochondrial complex genes such as MT-ND1, MT-ND2, MT-ND3, MT-ND4L, MT-CYB, MT-CO3, and MT-ATP6. A holistic approach to protect mitochondrial complex function, rather than targeting a single molecular, should be an effective therapeutic strategy to prevent and treat the long-term consequences of "long COVID."

Maxillary impacted canine replacing a central incisor with root resorption: Multidisciplinary treatment in a preadolescent patient.

Maxillary canines are often impacted, which can result in tooth disorders and adversely affect occlusal and facial development. The case report describes complete bilateral impaction of maxillary canines and significant root resorption of a central incisor. The multidisciplinary approach is the optimal strategy for addressing impacted maxillary canines.

Multi-omics and pharmacological characterization of patient-derived glioma cell lines.

Glioblastoma (GBM) is the most common brain tumor and remains incurable. Primary GBM cultures are widely used tools for drug screening, but there is a lack of genomic and pharmacological characterization for these primary GBM cultures. Here, we collect 50 patient-derived glioma cell (PDGC) lines and characterize them by whole genome sequencing, RNA sequencing, and drug response screening. We identify three molecular subtypes among PDGCs: mesenchymal (MES), proneural (PN), and oxidative phosphorylation (OXPHOS). Drug response profiling reveals that PN subtype PDGCs are sensitive to tyrosine kinase inhibitors, whereas OXPHOS subtype PDGCs are sensitive to histone deacetylase inhibitors, oxidative phosphorylation inhibitors, and HMG-CoA reductase inhibitors. PN and OXPHOS subtype PDGCs stably form tumors in vivo upon intracranial transplantation into immunodeficient mice, whereas most MES subtype PDGCs fail to form tumors in vivo. In addition, PDGCs cultured by serum-free medium, especially long-passage PDGCs, carry MYC/MYCN amplification, which is rare in GBM patients. Our study provides a valuable resource for understanding primary glioma cell cultures and clinical translation and highlights the problems of serum-free PDGC culture systems that cannot be ignored.

Discovery of KT-474─a Potent, Selective, and Orally Bioavailable IRAK4 Degrader for the Treatment of Autoimmune Diseases.

Interleukin-1 receptor associated kinase 4 (IRAK4) is an essential mediator of the IL-1R and TLR signaling pathways, both of which have been implicated in multiple autoimmune conditions. Hence, blocking the activity of IRAK4 represents an attractive approach for the treatment of autoimmune diseases. The activity of this serine/threonine kinase is dependent on its kinase and scaffolding activities; thus, degradation represents a potentially superior approach to inhibition. Herein, we detail the exploration of structure-activity relationships that ultimately led to the identification of KT-474, a potent, selective, and orally bioavailable heterobifunctional IRAK4 degrader. This represents the first heterobifunctional degrader evaluated in a nononcology indication and dosed to healthy human volunteers. This molecule successfully completed phase I studies in healthy adult volunteers and patients with atopic dermatitis or hidradenitis suppurativa. Phase II clinical trials in both of these indications have been initiated.

Spectral analysis enhanced net (SAE-Net) to classify breast lesions with BI-RADS category 4 or higher.

Early ultrasound screening for breast cancer reduces mortality significantly. The main evaluation criterion for breast ultrasound screening is the Breast Imaging-Reporting and Data System (BI-RADS), which categorizes breast lesions into categories 0-6 based on ultrasound grayscale images. Due to the limitations of ultrasound grayscale imaging, lesions with categories 4 and 5 necessitate additional biopsy for the confirmation of benign or malignant status. In this paper, the SAE-Net was proposed to combine the tissue microstructure information with the morphological information, thus improving the identification of high-grade breast lesions. The SAE-Net consists of a grayscale image branch and a spectral pattern branch. The grayscale image branch used the classical deep learning backbone model to learn the image morphological features from grayscale images, while the spectral pattern branch is designed to learn the microstructure features from ultrasound radio frequency (RF) signals. Our experimental results show that the best SAE-Net model has an area under the receiver operating characteristic curve (AUROC) of 12% higher and a Youden index of 19% higher than the single backbone model. These results demonstrate the effectiveness of our method, which potentially optimizes biopsy exemption and diagnostic efficiency.

NAD+ metabolic enzyme inhibitor as radiosensitizer for malignant meningioma and its modulation of P53 expression.

Surgical resection followed by radiotherapy (RT) is recommended for malignant meningioma but poor outcome is unavoidable. To improve the efficacy of RT in malignant meningioma, a targeted radiosensitizer could be added. Nicotinamide phosphoribosyltransferase (NAMPT), highly expressed in high-grade meningiomas may have a role in determining the radioresponse. Here, we evaluated the impact of NAMPT inhibition on radiosensitivity in malignant meningioma in vivo and in vitro. IOMM-Lee and TTMM705 cells were treated with NAMPT inhibition (FK866 or shRNA NAMPT) before irradiation. The subsequent clonogenic assay demonstrated significantly increased radiosensitivity. Combination treatment with FK866 and irradiation significantly increased the number of G2/M-phase cells, the percentage of apoptotic cells and the γ-H2A.X level compared to FK866 or RT alone. We examined the effect of NAMPT inhibition on NMI and p53 expression in IOMM-Lee and TTMM705 cells. NAMPT inhibition by FK866 and shRNA treatment increased NMI, p53, CDKN1A and BAX expression. Additionally, we assessed the efficacy of FK866/RT combination treatment in vivo. The combination treatment exhibited increased antitumor efficacy compared to either treatment alone. The Ki-67 level was significantly lower and the p53 and γ-H2A.X level was significantly higher in the combination treatment group than in any of the other three groups. In conclusion, these results indicate that FK866 improves radiosensitivity in malignant meningioma, an effect that may be attributed to the increase in p53 expression.

Multi-Shell Nanourchin-Integrated Dual Mode Lateral Flow Immunoassay for Sensitive and Rapid Detection of Clinical Cardiac Myosin-Binding Protein C.

Cardiac myosin-binding protein C (cMyBP-C) is a novel cardiac marker of acute myocardial infarction (AMI) and acute cardiac injuries (ACI). Construction of point-of-care testing techniques capable of sensing cMyBP-C with high sensitivity and precision is urgently needed. Herein, we synthesized an Au@NGQDs@Au/Ag multi-shell nanoUrchins (MSNUs), and then applied it in a colorimetric/SERS dual-mode immunoassay for detection of cMyBP-C. The MSNUs displayed superior stability, colorimetric brightness, and SERS enhancement ability with an enhanced factor of 5.4 × 109, which were beneficial to improve the detection capability of test strips. The developed MSNU-based test strips can achieve an ultrasensitive immunochromatographic assay of cMyBP-C in both colorimetric and SERS modes with the limits of detection as low as 19.3 and 0.77 pg/mL, respectively. Strikingly, this strip was successfully applied to analyze actual plasma samples with significantly better sensitivity, negative predictive value, and accuracy than commercially available gold test strips. Notably, this method possessed a wide range of application scenarios via combining with a color recognizer application named Color Grab on the smartphone, which can meet various needs of different users. Overall, our MSNU-based test strip as a mobile health monitoring tool shows excellent sensitivity, reproducibility, and rapid detection of the cMyBP-C, which holds great potential for the early clinic diagnosis of AMI and ACI.

Ultrasound wavelet spectra enable direct tissue recognition and full-color visualization.

Traditional brightness-mode ultrasound imaging is primarily constrained by the low specificity among tissues and the inconsistency among sonographers. The major cause is the imaging method that represents the amplitude of echoes as brightness and ignores other detailed information, leaving sonographers to interpret based on organ contours that depend highly on specific imaging planes. Other ultrasound imaging modalities, color Doppler imaging or shear wave elastography, overlay motion or stiffness information to brightness-mode images. However, tissue-specific scattering properties and spectral patterns remain unknown in ultrasound imaging. Here we demonstrate that the distribution (size and average distance) of scattering particles leads to characteristic wavelet spectral patterns, which enables tissue recognition and high-contrast ultrasound imaging. Ultrasonic wavelet spectra from similar particle distributions tend to cluster in the eigenspace according to principal component analysis, whereas those with different distributions tend to be distinguishable from one another. For each distribution, a few wavelet spectra are unique and act as a fingerprint to recognize the corresponding tissue. Illumination of specific tissues and organs with designated colors according to the recognition results yields high-contrast ultrasound imaging. The fully-colorized tissue-specific ultrasound imaging potentially simplifies the interpretation and promotes consistency among sonographers, or even enables the applicability for non-professionals.

Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy.

Molecular genetics is highly related with prognosis of high-grade glioma. Accordingly, the latest WHO guideline recommends that molecular subgroups of the genes, including IDH, 1p/19q, MGMT, TERT, EGFR, Chromosome 7/10, CDKN2A/B, need to be detected to better classify glioma and guide surgery and treatment. Unfortunately, there is no preoperative or intraoperative technology available for accurate and comprehensive molecular subgrouping of glioma. Here, we develop a deep learning-assisted fiber-optic Raman diagnostic platform for accurate and rapid molecular subgrouping of high-grade glioma. Specifically, a total of 2,354 fingerprint Raman spectra was obtained from 743 tissue sites (astrocytoma: 151; oligodendroglioma: 150; glioblastoma (GBM): 442) of 44 high-grade glioma patients. The convolutional neural networks (ResNet) model was then established and optimized for molecular subgrouping. The mean area under receiver operating characteristic curves (AUC) for identifying the molecular subgroups of high-grade glioma reached 0.904, with mean sensitivity of 83.3%, mean specificity of 85.0%, mean accuracy of 83.3%, and mean time expense of 10.6 s. The diagnosis performance using ResNet model was shown to be superior to PCA-SVM and UMAP models, suggesting that high dimensional information from Raman spectra would be helpful. In addition, for the molecular subgroups of GBM, the mean AUC reached 0.932, with mean sensitivity of 87.8%, mean specificity of 83.6%, and mean accuracy of 84.1%. Furthermore, according to saliency maps, the specific Raman features corresponding to tumor-associated biomolecules (e.g. nucleic acid, tyrosine, tryptophan, cholesteryl ester, fatty acid, and collagen) were found to contribute to the accurate molecular subgrouping. Collectively, this study opens up new opportunities for accurate and rapid molecular subgrouping of high-grade glioma, which would assist optimal surgical resection and instant post-operative decision-making.

The urinary microbiota composition and functionality of calcium oxalate stone formers.

Background: Accumulated evidences indicate that dysbiosis of the urinary microbiota is associated with kidney stone formation. In the present study, we aimed to investigate the urinary microbiota composition and functionality of patients with calcium oxalate stones and compare it with those of healthy individuals. Method: We collected bladder urine samples from 68 adult patients with calcium oxalate stones and 54 age-matched healthy controls by transurethral catheterization. 16S rRNA gene and shotgun sequencing were utilized to characterize the urinary microbiota and functionality associated with calcium oxalate stones. Results: After further exclusion, a total of 100 subjects was finally included and analyzed. The diversity of the urinary microbiota in calcium oxalate stone patients was not significantly different from that of healthy controls. However, the urinary microbiota structure of calcium oxalate stone formers significantly differed from that of healthy controls (PERMANOVA, r = 0.026, P = 0.019). Differential representation of bacteria (e.g., Bifidobacterium) and several enriched functional pathways (e.g., threonine biosynthesis) were identified in the urine of calcium oxalate stone patients. Conclusion: Our results showed significantly different urinary microbiota structure and several enriched functional pathways in calcium oxalate stone patients, which provide new insight into the pathogenesis of calcium oxalate stones.

Discovery of KT-413, a Targeted Protein Degrader of IRAK4 and IMiD Substrates Targeting MYD88 Mutant Diffuse Large B-Cell Lymphoma.

Developing therapies for the activated B-cell like (ABC) subtype of diffuse large B-cell lymphomas (DLBCL) remains an area of unmet medical need. A subset of ABC DLBCL tumors is driven by activating mutations in myeloid differentiation primary response protein 88 (MYD88), which lead to constitutive activation of interleukin-1 receptor associated kinase 4 (IRAK4) and cellular proliferation. IRAK4 signaling is driven by its catalytic and scaffolding functions, necessitating complete removal of this protein and its escape mechanisms for complete therapeutic suppression. Herein, we describe the identification and characterization of a dual-functioning molecule, KT-413 and show it efficiently degrades IRAK4 and the transcription factors Ikaros and Aiolos. KT-413 achieves concurrent degradation of these proteins by functioning as both a heterobifunctional degrader and a molecular glue. Based on the demonstrated activity and safety of KT-413 in preclinical studies, a phase 1 clinical trial in B-cell lymphomas, including MYD88 mutant ABC DLBCL, is currently underway.

Constitutive type-1 interferons signaling activity in malignant gliomas.

PURPOSE: Recent studies revealed a pro-tumor effect of constitutive Type-1 interferons (IFN-I) production and the downstream signaling activity in several malignancies. In contrast, heterogeneity and clinical significance of the signaling activity in gliomas remain unknown. Thus, we aimed to depict the heterogeneity and clinical significance of constitutive Type-1 interferon (IFN-I) production and the downstream signaling activity in gliomas. METHODS: We utilized multiplex immunofluorescence (mIF) on a 364 gliomas tissue microarray from our cohort. Moreover, we conducted bioinformatic analyses on the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases to investigate the heterogeneity and clinical significance of constitutive IFN-I signaling activity in gliomas. RESULTS: We observed high heterogeneity of the constitutive IFN-I signaling activity among glioma subtypes. Signaling increased with the WHO malignancy grade while decreasing in the gliomas with IDH mutations. Additionally, high IFN-I activity served as an independent predictor of unfavorable outcomes, and global DNA hypermethylation in IDH-mutant gliomas was associated with decreased IFN-I signaling activity. Positive correlations were observed between the IFN-I activity and glioma-associated inflammation, encompassing both anti-tumor and pro-tumor immune responses. Furthermore, the IFN-I activity varied significantly among tumor and immune cells in the glioma microenvironment (GME). Notably, a distinct pattern of IFN-I signaling activity distribution in GME cells was observed among glioma subtypes, and the pattern was independently associated with patient overall survival. CONCLUSIONS: Constitutive IFN-I signaling activity varies significantly among glioma subtypes and represents a potential indicator for increased glioma inflammation and unfavorable clinical outcomes.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort.

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

Profiling of the Proteins Interacting with Amyloid Beta Peptides in Clinical Samples by PACTS-TPP.

The accumulation of amyloid beta (Aß1-42) results in neurotoxicity and is strongly related to neurodegenerative disorders, especially Alzheimer's disease (AD), but the underlying molecular mechanism is still poorly understood. Therefore, there is an urgent need for researchers to discover the proteins that interact with Aß1-42 to determine the molecular basis. Previously, we developed peptide-ligand-induced changes in the abundance of proTeinS (PACTS)-assisted thermal proteome profiling (TPP) to identify proteins that interact with peptide ligands. In the present study, we applied this technique to analyze clinical samples to identify Aß1-42-interacting proteins. We detected 115 proteins that interact with Aß1-42 in human frontal lobe tissue. Pathway enrichment analysis revealed that the differentially expressed proteins were involved mainly in neurodegenerative diseases. Further orthogonal validation revealed that Aß1-42 interacted with the AD-associated protein mitogen-activated protein kinase 3 (MAPK3), and knockdown of the Aß1-42 amyloid precursor protein (APP) inhibited the MAPK signaling pathway, suggesting potential functional roles for Aß1-42 in interacting with MAPK3. Overall, this study demonstrated the application of the PACTS-TPP in clinical samples and provided a valuable data source for research on neurodegenerative diseases.

Association of body mass index with clinical outcome of primary WHO grade 4 glioma.

Background: The prognostic value of body mass index (BMI) in primary WHO grade 4 gliomas is not widely acknowledged. This study aims to assess the survival outcomes of patients with different BMIs. Methods: Real-world data of patients diagnosed with primary WHO grade 4 (2021 version) glioma was assessed. All 127 patients admitted in this study were administered with standard-of-care from September 2018 to September 2021. The outcomes of overall survival and progression-free survival were analyzed. Results: The baseline characteristics of clinical features, molecular features, and secondary treatment in BMI subsets showed no significant difference. The survival analyses showed a significantly superior overall survival (OS) in the overweight group compared to the normal weight group. A trend of better OS in the overweight group compared to the obesity group was observed. The univariate Cox regression demonstrated patients of round-BMI 25 and 26 had superior OS outcomes. Conclusion: In this real-world setting, patients with a BMI between 24 and 28 have superior overall survival. Patients in the proper BMI range may acquire survival benefits undergoing standard-of-care of primary WHO grade 4 gliomas. The prospective studies on a larger scale on these subsets of patients are necessary to solve the paradox of BMI in glioma.

Mogrol-mediated enhancement of radiotherapy sensitivity in non-small cell lung cancer: a mechanistic study.

This study investigated mogrol's impact on non-small cell lung cancer (NSCLC) radiosensitivity and underlying mechanisms, using various methods including assays, bioinformatics, and xenograft models. CCK-8, clonogenic, flow cytometry, TUNEL, and Western blot assays evaluated mogrol and radiation effects on NSCLC viability and apoptosis. Ubiquitin-specific protease 22 (USP22) expression in NSCLC patient tissues was determined by RT-qPCR and Western blot. A xenograft model validated mogrol's effects on tumor growth. Bioinformatics identified four ubiquitin-specific proteases, including USP22, in NSCLC. Kaplan-Meier analysis confirmed USP22's value in lung cancer survival. Human Protein Atlas (HPA) database analysis indicated higher USP22 expression in lung cancer tissues. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis implicated ERK1/2 in NSCLC progression, and molecular docking showed stability between mogrol and ERK1/2. Further in vivo and in vitro experiments have demonstrated that mogrol enhances the inhibitory effect of radiation on NSCLC cell viability and clonogenic capacity. Cell viability and clonogenic capacity are reduced by >50%, and an increase in cellular apoptosis is observed, with apoptotic levels reaching 10%. USP22 expression was significantly elevated in NSCLC tissues, particularly in radiotherapy-resistant patients. Mogrol downregulated USP22 expression by inhibiting the ERK/CREB pathway, lowering COX2 expression. Mogrol also enhanced radiation's inhibition of tumor growth in mice. Mogrol enhances NSCLC radiosensitivity by downregulating USP22 via the ERK/CREB pathway, leading to reduced COX2 expression.NEW & NOTEWORTHY Mogrol enhances non-small cell lung cancer (NSCLC) cell sensitivity to radiotherapy by downregulating USP22 through the ERK/CREB pathway, reducing COX2 expression. These findings highlight mogrol's potential as an adjunct to improve NSCLC radiotherapy and open avenues for further research and clinical applications.

Targeting the tumor microenvironment in primary central nervous system lymphoma: Implications for prognosis.

Primary central nervous system lymphoma (PCNSL) is a rare extranodal non-Hodgkin lymphoma, and there is limited research on its tumor microenvironment (TME). Nevertheless, more and more studies have evidence that TME has essential effects on tumor cell proliferation, immune escape, and drug resistance. Thus, it is critical to elucidate the role of TME in PCNSL. The understanding of the PCNSL TME is gradually unfolding, including factors that distinguish it from systemic diffuse large B-cell lymphoma (DLBCL). The TME in PCNSL exhibits both transcriptional and spatial intratumor heterogeneity. Cellular interactions between tumor cells and stroma cells reveal immune evasion signaling. The comparative analysis between PCNSL and DLBCL suggests that PCNSL is more likely to be an immunologically deficient tumor. In PCNSL, T cell exhaustion and downregulation of macrophage immune function are accompanied by suppressive microenvironmental factors such as M2 polarized macrophages, endothelin B receptor, HLA depletion, PD-L1, and TIM-3. MMP-9, Integrin-ß1, and ICAM-1/LFA-1 play crucial roles in transendothelial migration towards the CNS, while CXCL13/CXCR5, CD44, MAG, and IL-8 are essential for brain parenchymal invasion. Further, macrophages, YKL-40, CD31, CD105, PD-1/PD-L1 axis, osteopontin, galectin-3, aggregative perivascular tumor cells, and HLA deletion may contribute to poor outcomes in patients with PCNSL. This article reviews the effect of various components of TME on the progression and prognosis of PCNSL patients to identify novel therapeutic targets.

Prenatal air pollution exposure is associated with inflammatory, cardiovascular, and metabolic biomarkers in mothers and newborns.

BACKGROUND: Prenatal air pollution exposure has been associated with individual inflammatory, cardiovascular, and metabolic biomarkers in mothers and neonates. However, studies of air pollution and a comprehensive panel of biomarkers across maternal and cord blood samples remain limited. Few studies used data-driven methods to identify biomarker groupings that converge biomarkers from multiple biological pathways. This study aims to investigate the impacts of prenatal air pollution on groups of biomarkers in maternal and cord blood samples. METHODS: In the Maternal And Developmental Risks from Environmental and Social Stressors (MADRES) cohort, 87 biomarkers were quantified from 45 trimester 1 maternal blood and 55 cord blood samples. Pregnancy and trimester 1-averaged concentrations of particulate matter ≤2.5 µm and ≤10 µm in diameter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3) were estimated, using inverse distance squared weighted spatial interpolation from regulatory air monitoring stations. Traffic-related NOx was assessed using California Line Source Dispersion Model: freeway/highway roads, non-freeway major roads, non-freeway minor roads, and their sum as total NOx. Elastic Net (EN) regression within the rexposome R package was used to group biomarkers and assess their associations with air pollution. RESULTS: In maternal samples, trimester 1-averaged PM10 was associated with elevated inflammation biomarkers and lowered cardiovascular biomarkers. NO2 exhibited positive associations with cardiovascular and inflammation markers. O3 was inversely associated with inflammation, metabolic, and cardiovascular biomarkers. In cord blood, pregnancy-averaged PM2.5 was associated with higher cardiovascular biomarkers and lower metabolic biomarkers. PM10 was associated with lower inflammation and higher cardiovascular biomarkers. Total and major road NOx was associated with lower cardiovascular biomarkers. CONCLUSION: Prenatal air pollution exposure was associated with changes in biomarkers related to inflammation, cardiovascular, metabolic, cancer, and neurological function in both mothers and neonates. This study shed light on mechanisms by which air pollution can influence biological function during pregnancy.

The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study.

PURPOSE: Currently, there remains a scarcity of established preoperative tests to accurately predict the isocitrate dehydrogenase (IDH) mutation status in clinical scenarios, with limited research has explored the potential synergistic diagnostic performance among metabolite, perfusion, and diffusion parameters. To address this issue, we aimed to develop an imaging protocol that integrated 2-hydroxyglutarate (2HG) magnetic resonance spectroscopy (MRS) and intravoxel incoherent motion (IVIM) by comprehensively assessing metabolic, cellular, and angiogenic changes caused by IDH mutations, and explored the diagnostic efficiency of this imaging protocol for predicting IDH mutation status in clinical scenarios. METHODS: Patients who met the inclusion criteria were categorized into two groups: IDH-wild type (IDH-WT) group and IDH-mutant (IDH-MT) group. Subsequently, we quantified the 2HG concentration, the relative apparent diffusion coefficient (rADC), the relative true diffusion coefficient value (rD), the relative pseudo-diffusion coefficient (rD*) and the relative perfusion fraction value (rf). Intergroup differences were estimated using t-test and Mann-Whitney U test. Finally, we performed receiver operating characteristic (ROC) curve and DeLong's test to evaluate and compare the diagnostic performance of individual parameters and their combinations. RESULTS: 64 patients (female, 21; male, 43; age, 47.0 ± 13.7 years) were enrolled. Compared with IDH-WT gliomas, IDH-MT gliomas had higher 2HG concentration, rADC and rD (P < 0.001), and lower rD* (P = 0.013). The ROC curve demonstrated that 2HG + rD + rD* exhibited the highest areas under curve (AUC) value (0.967, 95%CI 0.889-0.996) for discriminating IDH mutation status. Compared with each individual parameter, the predictive efficiency of 2HG + rADC + rD* and 2HG + rD + rD* shows a statistically significant enhancement (DeLong's test: P < 0.05). CONCLUSIONS: The integration of 2HG MRS and IVIM significantly improves the diagnostic efficiency for predicting IDH mutation status in clinical scenarios.