Michigan United

SummarySecreted mucins are the major component of the mucus layer that protects intestinal epithelial surfaces by blocking excessive interactions with the microbiota. Mucins are complex glycoproteins decorated with over 100 differentO-glycans. Some bacteria can utilize mucins and excessive degradation has been associated with disruption of the mucus barrier and inflammation. Despite the importance of mucins, a detailed enzymatic pathway by which gut bacteria degrade colonic mucinO-glycans and the impact of this process on gut colonization are unknown. Here, we identified >100 genes that are expressed by the symbiontBacteroides thetaiotaomicronduring growth on differentO-glycan substrates, revealing effects of glycan structure on gene expression. The characterization of 33 glycoside hydrolase enzymes revealed the pathway for colonicO-glycan degradation by this bacterium.In vivocompetition experiments show that multiple exo-acting enzymes targeting mucin capping structures are central to gut colonization and may provide targets to inhibit bacterial mucin degradation.

We aimed to examine the individual and combined associations of e-cigarette policies with e-cigarette use among U.S. adolescents and young adults aged 12-20 years. We used data from Waves 7 (January 2022-April 2023) and 7.5 (April 2023-December 2023, conducted approximately one year after completion of the Wave 7 survey) of the Population Assessment of Tobacco and Health (PATH) study (N=11,418 U.S. adolescents and adults aged 12-20 years) and state-level e-cigarette policy data on flavor bans, e-cigarette-inclusive smoke-free policies, excise tax, product packaging, and retail licensing. We conducted multivariable logistic regression analyses to examine the individual and combined associations between e-cigarette policies and lifetime, past 30-day, and frequent e-cigarette use at Wave 7, and initiation of e-cigarette use at Wave 7.5 among those who reported no lifetime e-cigarette use at Wave 7. Flavor bans were associated with lower odds of lifetime e-cigarette use (AOR=0.69, 95% CI=0.55, 0.85). E-cigarette-inclusive smoke-free policies had significant associations with lifetime and frequent e-cigarette use (AOR range=0.56-0.78, ps<.05). The individual associations between e-cigarette excise taxes, product packaging, and retail licensing policies and underage e-cigarette use were not statistically significant. The combined e-cigarette policies scale was linked to reduced odds of lifetime e-cigarette use (AOR=0.91, 95% CI=0.87, 0.96). Comprehensive state-level e-cigarette policies, including but not limited to flavor bans and e-cigarette-inclusive smoke-free policies, may be crucial in mitigating e-cigarette use among adolescents and young adults, thereby providing critical evidence to inform future policy initiatives in the regulatory landscape of e-cigarettes.

We present a compact and generative machine-learning framework that predicts oil contamination based on microbial community compositions from experimental samples. Our method combines dimensionality reduction with data augmentation and generative modeling to address high-dimensional, non-linear, and sparse microbial data. To reduce the 503-dimensional bacterial composition dataset, we compared three dimensionality reduction techniques: feature importance from random forest, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE). Feature importance outperformed PCA and t-SNE, improving predictive performance and identifying microbial species most strongly correlated with oil contamination. To mitigate data scarcity, we augmented the training data using an augmented data neural network (ADNN) with noise injection. Samples generated by a variational autoencoder (VAE) were used as controlled perturbations to probe model robustness during stress testing. Using the top 3-10 bacterial features, our model achieved an R² value of up to 0.99 in both training and stress testing for predicting oil contamination from microbial data. In a bottle-level hold-out evaluation (22 splits at an 80/20 bottle ratio), performance on held-out bottles was lower and variable (mean test R² = -0.150), indicating limited generalization within this cohort. These results should be interpreted as a feasibility demonstration requiring validation on larger independent datasets.

Little is known about whether childhood exposure to parental mental health problems, a significant stressor in early life, influences an individual’s memory trajectories in mid- and later life. Drawing on data from four waves (2011–2018) of the China Health and Retirement Longitudinal Study (CHARLS) and its supplement, the 2014 Life History Survey, we used the latent growth curve modeling technique to investigate whether exposure to parental depression in childhood is associated with memory trajectories of Chinese older adults. Our analytic sample included 7,097 respondents aged 50 and above who were raised by both parents. Results show that individuals who recalled having both parents depressed during their childhood had lower memory scores at baseline compared to their non-exposed counterparts, even after controlling for childhood socioeconomic status and health. These differences remained stable over the 7-year follow-up. Educational attainment and adult health—particularly depressive symptoms—explained the lower episodic memory scores observed in individuals who experienced both parents’ depression during childhood. Surprisingly, individuals who reported having only one parent (either mother or father) depressed during their childhood did not show significantly different memory trajectories compared to their non-exposed counterparts. The findings underscore the long arm of parental mental health on cognitive function in later life and highlight the importance of preventing and treating parental depression through a child’s formative years.

The COVID-19 pandemic contributed to greater day-to-day time spent together for many families. Some research in Euro-American settings indicated that fathers spent more time caring for their children during the pandemic than previously, with the potential for lasting effects on fathers’ caregiving. However, there are few longitudinal studies with post-pandemic paternal care data and analyses from non-Euro-American contexts. We drew on a large sample of men (N = 649; Obs. = 1286) enrolled in a longitudinal study in the Philippines with waves of data collection prior to the pandemic in 2009 (wave 1) and 2014 (wave 2) and a third wave post-pandemic in 2022−23 (wave 3). Our main analyses focus on within-individual change in paternal caregiving for men residing with young children (N = 307) from the pre-pandemic (wave 2) to post-pandemic period (wave 3). Fathers showed meaningful within-individual declines in routine (intensive) caregiving time from the pre-pandemic (wave 2) to the post-pandemic (wave 3). However, they reported comparable engagement in overall, recreational, and educational care post-pandemic relative to their pre-pandemic levels at wave 2. Men’s shifts in pre-to-post-pandemic employment status predicted their changes in caregiving time, particularly for educational care. The post-pandemic patterns we observed for educational care are potentially consistent with shifting dynamics for fathers’ caregiving in this domain following the pandemic and complement results elsewhere connecting fathers’ employment characteristics to their caregiving during and after the pandemic.

During Juno’s extended mission, the spacecraft’s periapsis migrated toward Jupiter’s north pole, enabling high-resolution observations of auroral regions. At microwave wavelengths, these auroral features appear as localized reductions in brightness temperature (“cold spots”). Here we present observations from Juno Perijoves 56–72 using the Microwave Radiometer (MWR). MWR measures thermal emission from Jupiter’s deep atmosphere, which is partially absorbed by ionization produced by precipitating energetic electrons in the ionosphere. By exploiting MWR’s multi-frequency observations, we use the frequency dependence of electron–neutral collisional absorption to probe the vertical extent of auroral ionization at depths well below those accessible to ultraviolet measurements.We find systematic differences among auroral regions. The deepest ionization occurs at the Io footprint, is moderate along the main auroral oval, and is shallowest in the polar cap. Modeling of the multi-frequency absorption indicates that the Io footprint requires a substantial population of precipitating electrons with energies in the tens-of-MeV range, whereas the main oval can be explained without invoking such high-energy electrons. These results place new constraints on the energy and depth of electron precipitation in Jupiter’s aurora and demonstrate the unique capability of MWR multi-frequency measurements to diagnose deep ionospheric structure, complementing ultraviolet, infrared, and radio occultation observations.

Results from the Juno investigation of Jupiter have challenged our understanding of Jupiter origin and evolution. As the archetype of giant planets, the study of Jupiter provides knowledge needed to understand the origin of our own solar system and the planetary systems being discovered around other stars. Jupiter uniquely informs us about the origin of our own planetary system. The mass of Jupiter’s heavy element core and the abundance of heavy elements in the atmosphere discriminate among models for giant planet formation. Measurements by Juno of Jupiter’s gravity field suggest Jupiter’s core is diffuse, extended and contains compositional gradients. These new results require new models of Jupiter’s formation and evolution. The gravity science results on the measurement of J4 coupled to current estimates on the hydrogen and helium equation of state suggests Jupiter’s interior composition has low metallicity, potentially solar or even sub-solar. This is inconsistent with measurements of the atmosphere by both Juno and the Galileo probe which indicate the atmospheric composition is of higher metallicity (2-4x solar).The combined results from Juno provide new constraints on theories of Jupiter’s formation and evolution and giant planets in general. A summary of Juno’s results relevant to Jupiter’s formation and evolution will be presented along with a discussion of theoretical implications on Jupiter, and giant planets both within our solar system and beyond.