High-dimensional Ageome Representations of Biological Aging across Functional Modules.

The aging process involves numerous molecular changes that lead to functional decline and increased disease and mortality risk. While epigenetic aging clocks have shown accuracy in predicting biological age, they typically provide single estimates for the samples and lack mechanistic insights. In this study, we challenge the paradigm that aging can be sufficiently described with a single biological age estimate. We describe Ageome, a computational framework for measuring the epigenetic age of thousands of molecular pathways simultaneously in mice and humans. Ageome is based on the premise that an organism's overall biological age can be approximated by the collective ages of its functional modules, which may age at different rates and have different biological ages. We show that, unlike conventional clocks, Ageome provides a high-dimensional representation of biological aging across cellular functions, enabling comprehensive assessment of aging dynamics within an individual, in a population, and across species. Application of Ageome to longevity intervention models revealed distinct patterns of pathway-specific age deceleration. Notably, cell reprogramming, while rejuvenating cells, also accelerated aging of some functional modules. When applied to human cohorts, Ageome demonstrated heterogeneity in predictive power for mortality risk, and some modules showed better performance in predicting the onset of age-related diseases, especially cancer, compared to existing clocks. Together, the Ageome framework offers a comprehensive and interpretable approach for assessing aging, providing insights into mechanisms and targets for intervention.

Untargeted metabolomic analysis reveals different metabolites associated with response to mepolizumab and omalizumab in asthma.

Background: There is limited evidence on biomarkers associated with response to the monoclonal antibodies currently approved for asthma treatment. We sought to identify circulatory metabolites associated with response to treatment with mepolizumab or omalizumab. Methods: We conducted global metabolomic profiling of pre-treatment plasma samples from 100 patients with moderate-to-severe asthma who initiated mepolizumab (n=31) or omalizumab (n=69). The primary outcome was the change in exacerbations within 12 months of therapy. Negative binomial models were used to assess the association between each metabolite and exacerbations, adjusting for age, sex, body mass index, baseline exacerbations and inhaled corticosteroid use. Chemical similarity enrichment analysis (ChemRICH) was conducted to identify chemical subclasses associated with treatment response. Results: The mean age of the mepolizumab group was 58.7 years with on average 2.9 exacerbations over the year prior to initiation of biologic therapy. The mean age in the omalizumab group was 48.8 years with 1.5 exacerbations in the preceding year. Patients with higher levels of two tocopherol metabolites were associated with more exacerbations on mepolizumab (δ-carboxyethyl hydroxychroman (CEHC) (p=2.65E-05, false discovery rate (FDR=0.01) and δ-CEHC glucuronide (p=2.47E-06, FDR=0.003)). Higher levels of six androgenic steroids, three carnitine metabolites and two bile acid metabolites were associated with decreased exacerbations in the omalizumab group. In enrichment analyses, xanthine metabolites (cluster FDR=0.0006) and tocopherol metabolites (cluster FDR=0.02) were associated with worse mepolizumab response, while androgenic steroids (cluster FDR=1.9E-18), pregnenolone steroids (cluster p=3.2E-07, FDR=1.4E-05) and secondary bile acid metabolites (cluster p=0.0003, FDR=0.006) were the top subclasses associated with better omalizumab response. Conclusion: This study identifies distinct metabolites associated with response to mepolizumab and omalizumab, with androgenic steroids associated with response to both mepolizumab and omalizumab.

Enhanced PM2.5 estimation across China: An AOD-independent two-stage approach incorporating improved spatiotemporal heterogeneity representations.

In China, population growth and aging have partially negated the public health benefits of air pollution control measures, underscoring the ongoing need for precise PM2.5 monitoring and mapping. Despite its prevalence, the satellite-derived Aerosol Optical Depth (AOD) method for estimating PM2.5 concentrations often encounters significant spatial data gaps. Additionally, current research still needs better representation of PM2.5 spatiotemporal heterogeneity. Addressing these challenges, we developed a two-stage model employing the Extreme Gradient Boosting (XGBoost) algorithm. By incorporating improved spatiotemporal factors, we achieved high-precision and full-coverage daily 1-km PM2.5 mappings across China for the year 2020 without utilizing AOD products. Specifically, Model 1 develops improved temporal encodings and a terrain classification factor (DC), while Model 2 constructs an enhanced spatial autocorrelation term (Ps) by integrating observed and estimated values. Notably, Model 2 excelled in 10-fold sample-based cross-validation, achieving a coefficient of determination of 0.948, a mean absolute error of 3.792 µg/m³, a root mean square error of 7.144 µg/m³, and a mean relative error of 14.171%. Feature importance and Shapley Additive exPlanations (SHAP) analyses determined the relative importance of predictors in model training and outcome prediction, while correlation analysis identified strong links between improved temporal encodings, PM2.5 concentrations, and significant meteorological factors. Two-way Partial Dependence Plots (PDPs) further explored the interactions among these factors and their impact on PM2.5 levels. Compared to traditional methods, improved temporal encodings align more closely with seasonal variations and synergize more effectively with meteorological factors. Besides, the structured nature of DC aids in model training, while the improved Ps more effectively captures PM2.5's spatial autocorrelation, outperforming traditional Ps. Overall, this study effectively represents spatiotemporal information, thereby boosting model accuracy and enabling seamless large-scale PM2.5 estimations. It provides deep insights into variables and models, providing significant implications for future air pollution research.

Network Analysis Reveals Protein Modules Associated with Childhood Respiratory Diseases.

Background: The first year of life is a period of rapid immune development that can impact health trajectories and the risk of developing respiratory-related diseases, such as asthma, recurrent infections, and eczema. However, the biology underlying subsequent disease development remains unknown. Methods: Using weighted gene correlation network analysis (WGCNA), we derived modules of highly correlated immune-related proteins in plasma samples from children at age 1 year (N=294) from the Vitamin D Antenatal Asthma Reduction Trial (VDAART). We applied regression analyses to assess relationships between protein modules and development of childhood respiratory diseases up to age 6 years. We then characterized genomic, environmental, and metabolomic factors associated with modules. Results: WGCNA identified four protein modules at age 1 year associated with incidence of childhood asthma and/or recurrent wheeze (Padj range: 0.02-0.03), respiratory infections (Padj range: 6.3×10-9-2.9×10-6), and eczema (Padj=0.01) by age 6 years; three modules were associated with at least one environmental exposure (Padj range: 2.8×10-10-0.03) and disrupted metabolomic pathway(s) (Padj range: 2.8×10-6-0.04). No genome-wide SNPs were identified as significant genetic risk factors for any protein module. Relationships between protein modules with clinical, environmental, and 'omic factors were temporally sensitive and could not be recapitulated in protein profiles at age 6 years. Conclusion: These findings suggested protein profiles as early as age 1 year predicted development of respiratory-related diseases through age 6 and were associated with changes in pathways related to amino acid and energy metabolism. These may inform new strategies to identify vulnerable individuals based on immune protein profiling.

Gold brocade coated CoFe PBA with enhanced peroxidase-like activity for a chemiluminescent imaging immunoassay.

Traditional chemiluminescence (CL) imaging immunoassays usually rely on natural enzymes as catalytic probes, which has hampered their extensive application due to the susceptibility to inactivation of natural enzymes. In response, a gold brocade coated CoFe Prussian blue analogue (CoFe PBA@Au brocade) with enhanced peroxidase-like activity was synthesized and utilized as a powerful label probe for constructing a highly sensitive CL imaging immunosensor targeting disease biomarkers with excellent performance. This research offers a universal strategy for enhancing the sensitivity of CL imaging immunoassays and further expands the application of PBA nanozymes.

A genome-wide association study of mass spectrometry proteomics using the Seer Proteograph platform.

Genome-wide association studies (GWAS) with proteomics are essential tools for drug discovery. To date, most studies have used affinity proteomics platforms, which have limited discovery to protein panels covered by the available affinity binders. Furthermore, it is not clear to which extent protein epitope changing variants interfere with the detection of protein quantitative trait loci (pQTLs). Mass spectrometry-based (MS) proteomics can overcome some of these limitations. Here we report a GWAS using the MS-based Seer Proteograph™ platform with blood samples from a discovery cohort of 1,260 American participants and a replication in 325 individuals from Asia, with diverse ethnic backgrounds. We analysed 1,980 proteins quantified in at least 80% of the samples, out of 5,753 proteins quantified across the discovery cohort. We identified 252 and replicated 90 pQTLs, where 30 of the replicated pQTLs have not been reported before. We further investigated 200 of the strongest associated cis-pQTLs previously identified using the SOMAscan and the Olink platforms and found that up to one third of the affinity proteomics pQTLs may be affected by epitope effects, while another third were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein expression. The present study demonstrates the complementarity of the different proteomics approaches and reports pQTLs not accessible to affinity proteomics, suggesting that many more pQTLs remain to be discovered using MS-based platforms.

In Vitro and In Vivo Analyses Reveal Tumor-Derived Exosome miR-558 Promotes Angiogenesis in Tongue Squamous Cell Carcinoma by Targeting Heparinase.

This study aimed to investigate the role of miR-558 in tumor angiogenesis by targeting heparinase (HPSE) in tongue squamous cell carcinoma (TSCC)-derived exosomes. In the present study, the role of exosome miR-558 in angiogenesis in vitro and in vivo was investigated by cell proliferation, migration, tube formation, subcutaneous tumor formation in mice, and in vivo Matrigel plug assay. The target genes of miR-558 were detected by means of dual luciferase assay. It was found that TSCC cells secrete miR-558 into the extracellular environment, with exosome as the carrier. Human umbilical vein endothelial cells (HUVEC) ingested exosomes, which not only increased the expression level of miR-558, but also enhanced their proliferation, migration, and tube formation functions. In vivo Matrigel plug assay demonstrated that TSCC cell-derived exosome miR-558 promoted neovascularization in vivo. Compared with negative control cells, TSCC cells overexpressing miR-558 formed subcutaneous tumors in nude mice, with larger volume, heavier mass, and more vascularization. Dual luciferase assay confirmed that HPSE was the direct target gene regulated by miR-558. HPSE promoted the proliferation, migration, and tube formation of HUVECs, and the knockout of HPSE could downregulate the pro-angiogenic effect of miR-558. In summary, miR-558 in TSCC exosomes promotes the proliferation, migration, and tube formation of HUVECs by targeting HPSE, and enhancing tumor angiogenesis.

Quantifying the stochastic component of epigenetic aging.

DNA methylation clocks can accurately estimate chronological age and, to some extent, also biological age, yet the process by which age-associated DNA methylation (DNAm) changes are acquired appears to be quasi-stochastic, raising a fundamental question: how much of an epigenetic clock's predictive accuracy could be explained by a stochastic process of DNAm change? Here, using DNAm data from sorted immune cells, we build realistic simulation models, subsequently demonstrating in over 22,770 sorted and whole-blood samples from 25 independent cohorts that approximately 66-75% of the accuracy underpinning Horvath's clock could be driven by a stochastic process. This fraction increases to 90% for the more accurate Zhang's clock, but is lower (63%) for the PhenoAge clock, suggesting that biological aging is reflected by nonstochastic processes. Confirming this, we demonstrate that Horvath's age acceleration in males and PhenoAge's age acceleration in severe coronavirus disease 2019 cases and smokers are not driven by an increased rate of stochastic change but by nonstochastic processes. These results significantly deepen our understanding and interpretation of epigenetic clocks.

Metabolite signatures associated with microRNA miR-143-3p serve as drivers of poor lung function trajectories in childhood asthma.

BACKGROUND: Lung function trajectories (LFTs) have been shown to be an important measure of long-term health in asthma. While there is a growing body of metabolomic studies on asthma status and other phenotypes, there are no prospective studies of the relationship between metabolomics and LFTs or their genomic determinants. METHODS: We utilized ordinal logistic regression to identify plasma metabolite principal components associated with four previously-published LFTs in children from the Childhood Asthma Management Program (CAMP) (n = 660). The top significant metabolite principal component (PCLF) was evaluated in an independent cross-sectional child cohort, the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) (n = 1151) and evaluated for association with spirometric measures. Using meta-analysis of CAMP and GACRS, we identified associations between PCLF and microRNA, and SNPs in their target genes. Statistical significance was determined using an false discovery rate-adjusted Q-value. FINDINGS: The top metabolite principal component, PCLF, was significantly associated with better LFTs after multiple-testing correction (Q-value = 0.03). PCLF is composed of the urea cycle, caffeine, corticosteroid, carnitine, and potential microbial (secondary bile acid, tryptophan, linoleate, histidine metabolism) metabolites. Higher levels of PCLF were also associated with increases in lung function measures and decreased circulating neutrophil percentage in both CAMP and GACRS. PCLF was also significantly associated with microRNA miR-143-3p, and SNPs in three miR-143-3p target genes; CCZ1 (P-value = 2.6 × 10-5), SLC8A1 (P-value = 3.9 × 10-5); and TENM4 (P-value = 4.9 × 10-5). INTERPRETATION: This study reveals associations between metabolites, miR-143-3p and LFTs in children with asthma, offering insights into asthma physiology and possible interventions to enhance lung function and long-term health. FUNDING: Molecular data for CAMP and GACRS via the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung, and Blood Institute (NHLBI).

Contraceptive Use Among Traditional Medicare And Medicare Advantage Enrollees.

Medicare is the primary source of health insurance coverage for reproductive-age people with Social Security Disability Insurance. However, Medicare does not require contraceptive coverage for pregnancy prevention, and little is known about contraceptive use in traditional Medicare and Medicare Advantage. We analyzed Medicare and Optum data to assess variations in contraceptive use and methods used by traditional Medicare and Medicare Advantage enrollees, as well as among enrollees with and without noncontraceptive clinical indications. Clinically indicated contraceptives are used for reasons other than pregnancy prevention, including menstrual regulation or to treat acne, menorrhagia, and endometriosis. Contraceptive use was higher among Medicare Advantage enrollees than traditional Medicare enrollees, but use in both populations was low compared with contraceptive use among Medicaid enrollees. We found significant variation by Medicare type with respect to contraceptive methods used. Relative to traditional Medicare, the probability of long-acting reversible contraception was more than three times higher in Medicare Advantage, and the probability of tubal sterilization was more than ten times higher. Overall, Medicare enrollees with noncontraceptive clinical indications had twice the probability of contraceptive use as those without them. Medicare coverage of all contraceptive methods without cost sharing would help address financial barriers to contraceptives and support the reproductive autonomy of disabled enrollees.

A new small molecule DoNA binding to CAG repeat RNA.

We here report a new molecule DoNA binding to a CAG repeat RNA. DoNA is a dimer of the NA molecule that we previously reported. NA binds with high affinity to a CAG repeat DNA but not significantly to a CAG repeat RNA. Binding analyses using SPR and CSI-TOF MS indicated a significant increase in the affinity of DoNA to a single stranded CAG repeat RNA compared to NA. Systematic investigation of the RNA motifs bound by DoNA using hairpin RNA models revealed that DoNA binds to the CAG units at overhang and terminal positions, and notably, it binds to the structurally flexible internal and hairpin loop region.

Actin filament-associated protein 1-antisense RNA1 promotes the development and invasion of tongue squamous cell carcinoma via the AFAP1-AS1/miR-133a-5p/ZIC2 axis.

BACKGROUND: The present study aimed to explore the biological role and underlying mechanism of the long non-coding RNA actin filament-associated protein 1-antisense RNA1 (lncRNA AFAP1-AS1) in the progression of tongue squamous cell carcinoma (TSCC). METHODS: A quantitative reverse transcriptase-PCR (RT-qPCR) was conducted to assess relative levels of the miR-133a-5p, lncRNAs AFAP1-AS1 and zinc finger family member 2 (ZIC2) in TSCC cell lines and specimens, whereas ZIC2 protein levels were measured using western blotting. After modifying the levels of expression of lncRNA AFP1-AS1, miR-133a-5p and ZIC2 using lentivirus or plasmid transfection, we examined AKT/epithelial-mesenchymal transition signaling pathway alterations, in vivo carcinogenesis of TSCC in nude mice and in vitro malignant phenotypes. A dual-luciferase reporter assay was conducted to confirm the targeting relationship between ZIC2 and miR-133a-5p, as well as between miR-133a-5p and lncRNA AFAP1-AS1. Based on The Cancer Genome Atlas (TCGA) database, we additionally validated AFP1-AS1. The potential biological pathway for AFP1-AS1 was investigated using gene set enrichment analysis (GSEA). We also evaluated the clinical diagnostic capacities of AFP1-AS1 and clustered the most potential biomarkers with the Mfuzz expression pattern. Finally, we also made relevant drug predictions for AFP1-AS1. RESULTS: In TSCC cell lines and specimens, lncRNA AFAP1-AS1 was upregulated. ZIC2 was upregulated in TSCC cells as a result of lncRNA AFAP1-AS1 overexpression, which also promoted TSCC cell migration, invasion, viability, and proliferation. Via the microRNA sponge effect, it was found that lncRNA AFAP1-AS1 could upregulate ZIC2 by competitively inhibiting miR-133a-5p. Interestingly, knockdown of ZIC2 reversed the biological roles of lncRNA AFAP1-AS1 with respect to inducing malignant phenotypes in TSCC cells. In addition, in vivo overexpression of lncRNA AFAP1-AS1 triggered subcutaneous tumor growth in nude mice implanted with TSCC cells and upregulated ZIC2 in the tumors. The TCGA database findings revealed that AFAP1-AS1 was significantly upregulated in TSCC specimens and had good clinical diagnostic value. The results of GSEA showed that peroxisome proliferator-activated receptor signaling pathway was significantly correlated with low expression of AFP1-AS1. Finally, the results of drug prediction indicated that the group with high AFAP1-AS1 expression was more sensitive to docetaxel, AZD4547, AZD7762 and nilotinib. CONCLUSIONS: The upregulation of lncRNA AFAP1-AS1, which increases TSCC cell viability, migration, proliferation and invasion via the AFAP1-AS1/miR-133a-5p/ZIC2 axis, aids in the progression of TSCC.

Myosin heavy chain isoform expression and meat quality characteristics of different muscles in yak (Bos grunniens).

Myosin heavy chain (MHC) isoforms and meat quality characteristics of different muscles were investigated to explore their potential relationships in yaks. Results showed that semitendinosus (ST), longissimus thoracis (LT), and infraspinatus (IS) have a greater ratio of MHC IIb (47.84%), MHC IIa (73.27%), and MHC I (24.26%), respectively, than the other two muscles. Compared with LT or ST, IS exhibited more intense color, greater water-holding capacity, and initial tenderness with higher intermuscular fat (IMF) and collagen (of lower cross-linking level), presenting overall better quality. Variations in MHC isoforms accounted for the muscle-specific meat quality. Specifically, MHC I was positively associated with redness, myoglobin, IMF, collagen, pH, and thermal stability and negatively associated with myofibril fragmentation index, fiber thickness, collagen cross-linking, and drip loss. These results provide insights into the relationships between MHC isoforms and meat quality in yaks and the MHC I isoform has an extensive influence on meat quality.

OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records.

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases.

BACKGROUND: As new infectious diseases (ID) emerge and others continue to mutate, there remains an imminent threat, especially for vulnerable individuals. Yet no generalizable framework exists to identify the at-risk group prior to infection. Metabolomics has the advantage of capturing the existing physiologic state, unobserved via current clinical measures. Furthermore, metabolomics profiling during acute disease can be influenced by confounding factors such as indications, medical treatments, and lifestyles. METHODS: We employed metabolomic profiling to cluster infection-free individuals and assessed their relationship with COVID severity and influenza incidence/recurrence. FINDINGS: We identified a metabolomic susceptibility endotype that was strongly associated with both severe COVID (ORICUadmission = 6.7, p-value = 1.2 × 10-08, ORmortality = 4.7, p-value = 1.6 × 10-04) and influenza (ORincidence = 2.9; p-values = 2.2 × 10-4, ßrecurrence = 1.03; p-value = 5.1 × 10-3). We observed similar severity associations when recapitulating this susceptibility endotype using metabolomics from individuals during and after acute COVID infection. We demonstrate the value of using metabolomic endotyping to identify a metabolically susceptible group for two-and potentially more-IDs that are driven by increases in specific amino acids, including microbial-related metabolites such as tryptophan, bile acids, histidine, polyamine, phenylalanine, and tyrosine metabolism, as well as carbohydrates involved in glycolysis. INTERPRETATIONS: These metabolites may be identified prior to infection to enable protective measures for these individuals. FUNDING: The Longitudinal EMR and Omics COVID-19 Cohort (LEOCC) and metabolomic profiling were supported by the National Heart, Lung, and Blood Institute and the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health.

A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes.

BACKGROUND: Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition. METHODS: Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes. RESULTS: Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity. CONCLUSIONS: This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.

Sex-related differences in the prevalence of substance use disorders, treatment, and overdose among parents with young children.

Introduction: Risk factors and treatment rates for substance use disorders (SUDs) differ by sex. Females often have greater childcare and household responsibilities than males, which may inhibit SUD treatment. We examined how SUD, medication for opioid use disorder (MOUD) receipt, and overdose rates differ by sex among parents with young children (<5 years). Methods: Using deidentified national administrative healthcare data from Optum's Clinformatics® Data Mart Database version 8.1 (2007-2021), we identified parents aged 26-64 continuously enrolled in commercial insurance for ≥ 30 days and linked to ≥ 1 dependent child < 5 years from January 1, 2016-February 29, 2020. We used generalized estimating equations to estimate the average predicted prevalence of SUD diagnosis, MOUD receipt after opioid use disorder (OUD) diagnosis, and overdose by parent sex in any month, adjusting for age, race/ethnicity, state of residence, enrollment month, and mental health conditions. Results: From 2016 to 2020, there were 2,241,795 parents with a dependent child < 5 years, including 1,155,252 (51.5%) females and 1,086,543 (48.5%) males. Male parents had a higher average predicted prevalence of an SUD diagnosis (11.1% [11, 11.16]) than female parents (5.5% [5.48, 5.58]). Among parents with OUD, the average predicted prevalence of receiving MOUD was 27.4% [26.1, 28.63] among male and 19.7% [18.34, 21.04] among female parents, with no difference in overdose rates by sex. Conclusion: Female parents are less likely to be diagnosed with an SUD or receive MOUD than male parents. Removing policies that criminalize parental SUD and addressing childcare-related barriers may improve SUD identification and treatment.

Duration of medication for opioid use disorder during pregnancy and postpartum by race/ethnicity: Results from 6 state Medicaid programs.

BACKGROUND: Medication for opioid use disorder (MOUD) is evidence-based treatment during pregnancy and postpartum. Prior studies show racial/ethnic differences in receipt of MOUD during pregnancy. Fewer studies have examined racial/ethnic differences in MOUD receipt and duration during the first year postpartum and in the type of MOUD received during pregnancy and postpartum. METHODS: We used Medicaid administrative data from 6 states to compare the percentage of women with any MOUD and the average proportion of days covered (PDC) with MOUD, overall and by type of MOUD, during pregnancy and four postpartum periods (1-90 days, 91-180 days, 181-270 days, and 271-360 days postpartum) among White non-Hispanic, Black non-Hispanic, and Hispanic women diagnosed with OUD. RESULTS: White non-Hispanic women were more likely to receive any MOUD during pregnancy and all postpartum periods compared to Hispanic and Black non-Hispanic women. For all MOUD types combined and for buprenorphine, White non-Hispanic women had the highest average PDC during pregnancy and each postpartum period, followed by Hispanic women and Black non-Hispanic women (e.g., for all MOUD types, 0.49 vs. 0.41 vs. 0.23 PDC, respectively, during days 1-90 postpartum). For methadone, White non-Hispanic and Hispanic women had similar average PDC during pregnancy and postpartum, and Black non-Hispanic women had substantially lower PDC. CONCLUSIONS: There are stark racial/ethnic differences in MOUD during pregnancy and the first year postpartum. Reducing these inequities is critical to improving health outcomes among pregnant and postpartum women with OUD.

Phage N15-Based Vectors for Gene Cloning and Expression in Bacteria and Mammalian Cells.

Bacteriophage N15 is the first virus known to deliver linear prophage into Escherichia coli. During its lysogenic cycle, N15 protelomerase (TelN) resolves its telomerase occupancy site (tos) into hairpin telomeres. This protects the N15 prophage from bacterial exonuclease degradation, enabling it to stably replicate as a linear plasmid in E. coli. Interestingly, purely proteinaceous TelN can retain phage DNA linearization and hairpin formation without involving host- or phage-derived intermediates or cofactors in the heterologous environment. This unique feature has led to the advent of synthetic linear DNA vector systems derived from the TelN-tos module for the genetic engineering of bacterial and mammalian cells. This review will focus on the development and advantages of N15-based novel cloning and expression vectors in the bacterial and mammalian environments. To date, N15 is the most widely exploited molecular tool for the development of linear vector systems, especially the production of therapeutically useful miniDNA vectors without a bacterial backbone. Compared to typical circular plasmids, linear N15-based plasmids display remarkable cloning fidelity in propagating unstable repetitive DNA sequences and large genomic fragments. Additionally, TelN-linearized vectors with the relevant origin of replication can replicate extrachromosomally and retain transgenes functionality in bacterial and mammalian cells without compromising host cell viability. Currently, this DNA linearization system has shown robust results in the development of gene delivery vehicles, DNA vaccines and engineering mammalian cells against infectious diseases or cancers, highlighting its multifaceted importance in genetic studies and gene medicine.

Effect of slaughter age and postmortem aging time on tenderness and water-holding capacity of yak (Bos grunniens) longissimus thoracis muscle.

The present study investigated the effect of slaughter age (2.43 ± 0.20, 4.15 ± 0.19, 6.62 ± 0.18, 10.59 ± 0.74 years) and postmortem aging time (1, 24, and 72 h) on the tenderness and water-holding capacity (WHC) of yak longissimus thoracis muscles to determine the most suitable age for slaughter to ensure product consistency. Under conventional postmortem aging conditions (4 °C), muscles of each age group exhibited the effect of cold shortening. Once the cold shortening occurred, the age effect on thickening muscle fiber and developing cross-links of collagen, considered to intensify the meat toughness, became less important. Owing to greater carcass weight and intramuscular fat, muscles of the older carcass (over 6-year-old) were less influenced by the cold shortening effect during the chilling process and showed lessened sarcomere contraction, delayed formation of drip loss channels, and increased level of myofibril fragmentation index (MFI) and myofiber structural disintegration, resulting in greater tenderness and WHC, especially 6-7 years group. Aging of 72 h structurally disintegrated the collagen cross-linking and integrity of muscle fibers and elevated the MFI, improving the meat tenderness. Therefore, the suitable slaughter age for yak is 6-7 years old and after 72 h aging, improved quality of yak meat can be obtained.