Association of breastfeeding practices during the first 12 months and subsequent infant respiratory tract infections: a prospective cohort study
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Analysis of microbial composition and sharing in low-biomass human milk samples: a comparison of DNA isolation and sequencing techniques
Human milk microbiome studies are currently hindered by low milk bacterial/human cell ratios and often rely on 16S rRNA gene sequencing, which limits downstream analyses. Here, we aimed to find a method to study milk bacteria and assess bacterial sharing between maternal and infant microbiota. We tested four DNA isolation methods, two bacterial enrichment methods and three sequencing methods on mock communities, milk samples and negative controls. Of the four DNA isolation kits, the DNeasy PowerSoil Pro (PS) and MagMAX Total Nucleic Acid Isolation (MX) kits provided consistent 16S rRNA gene sequencing results with low contamination. Neither enrichment method substantially decreased the human metagenomic sequencing read-depth. Long-read 16S-ITS-23S rRNA gene sequencing biased the mock community composition but provided consistent results for milk samples, with little contamination. In contrast to 16S rRNA gene sequencing, 16S-ITS-23S rRNA gene sequencing of milk, infant oral, infant faecal and maternal faecal DNA from 14 mother-infant pairs provided sufficient resolution to detect significantly more frequent sharing of bacteria between related pairs compared to unrelated pairs. In conclusion, PS or MX kit-DNA isolation followed by 16S rRNA gene sequencing reliably characterises human milk microbiota, and 16S-ITS-23S rRNA gene sequencing enables studies of bacterial transmission in low-biomass samples.
A network analysis of postpartum depression and mother-to-infant bonding shows common and unique symptom-level connections across three postpartum periods
Postpartum depression and mother-to-infant bonding difficulties (MIBD), two issues crucial to maternal and infant mental health, often coexist and affect each other. Our study aims to dissect their complex relationship through a graphical LASSO network analysis of individual symptoms in 5594 Japanese postpartum women, whose geographical distribution was nationally representative. We identified ‘fear’, ‘enjoyment’, ‘overwhelm’, and ‘insomnia’ as common bridge symptoms linking postpartum depression and MIBD across three distinct postpartum periods. Moreover, ‘self-harm’ emerged as a bridge symptom in the first 6 months and the 7–12 month period, while ‘laugh’ was a bridge symptom in the first 6 months and the 13–24 month period. Notably, ‘self-blame’ was identified as a unique bridge symptom specific to the 13–24 month period. Our analysis highlights the complexities of symptom connectivity across postpartum stages and underscores the critical need for interventions that address both common and stage-specific bridge symptoms to effectively support maternal mental health and strengthen mother-to-infant bonding.
Moving beyond descriptive studies: harnessing metabolomics to elucidate the molecular mechanisms underpinning host-microbiome phenotypes
Advances in technology and software have radically expanded the scope of metabolomics studies and allow us to monitor a broad transect of central carbon metabolism in routine studies. These increasingly sophisticated tools have shown that many human diseases are modulated by microbial metabolism. Despite this, it remains surprisingly difficult to move beyond these statistical associations and identify the specific molecular mechanisms that link dysbiosis to the progression of human disease. This difficulty stems from both the biological intricacies of host-microbiome dynamics as well as the analytical complexities inherent to microbiome metabolism research. The primary objective of this review is to examine the experimental and computational tools that can provide insights into the molecular mechanisms at work in host–microbiome interactions and to highlight the undeveloped frontiers that are currently holding back microbiome research from fully leveraging the benefits of modern metabolomics.
Young infants’ exposure to parabens: lotion use as a potential source of exposure
Parabens are widely used as antimicrobials in personal care products and pharmaceuticals. While previous studies demonstrate paraben exposure is ubiquitous, data investigating infants’ exposure is limited.
Management practices and manufacturing firm responses to a randomized energy audit
Increasing the efficiency of industrial energy use is widely considered important for mitigating climate change. We randomize assignment of an energy audit intervention aimed at improving energy efficiency and reducing energy expenditures of small- and medium-sized metal processing firms in Shandong Province, China, and examine impacts on energy outcomes and interactions with firms’ management practices. We find that the intervention reduced firms’ unit cost of electricity by 8% on average. Firms with more developed structured management practices showed higher rates of recommendation adoption. However, the post-intervention electricity unit cost reduction is larger in firms with less developed practices, primarily driven by a single recommendation that corrected managers’ inaccurate reporting of transformer usage at baseline, lowering their electricity costs. By closing management-associated gaps in awareness of energy expenditures, energy audit programmes may reduce a firm’s unit cost of energy but have an ambiguous impact on energy use and climate change.
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