Limited data exist related to low birth weight (LBW) incidence and risk factors in Western China. This paper aims to assess LBW and its relationship with antenatal care (ANC) in the poor counties of Western China. A community-based study in rural Western China was conducted in 2011. A kernel distribution was used to estimate the adjusted LBW incidence, and associations between LBW and socio-demographic or maternal factors were examined using multilevel logistic regression. Among 8,964 participants, 65.7% were weighed at birth. Crude LBW incidence was 6.6% and the adjusted rate was 9.3%. The study revealed that risk factors of LBW are being female, raised within a minority group, and with a family income below the national poverty line. For maternal risk factors, LBW was positively associated with not attending at least five or eight ANC visits, not receiving any ANC during the first trimester, and not having access to assess certain ANC content (weight, blood pressure, blood test, urine test, B-scan ultrasound, and folic acid supplement). There is urgent need to promote quality ANC in poor and rural areas of Western China and to prioritize vulnerable women and children who will benefit from quality ANC.

Urinary tract infections (UTIs) are frequent in humans, affecting the upper and lower urinary tract. Present diagnosis relies on the positive culture of uropathogenic bacteria from urine and clinical markers of inflammation of the urinary tract. The bladder is constantly challenged by adverse environmental stimuli which influence urinary tract physiology, contributing to a dysbiotic environment. Simultaneously, pathogens are primed by environmental stressors such as antibiotics, favoring recurrent UTIs (rUTIs), resulting in chronic illness. Due to different confounders for UTI onset, a greater understanding of the fundamental environmental mechanisms and microbial ecology of the human urinary tract is required. Such advancements could promote the tandem translation of bench and computational studies for precision treatments and clinical management of UTIs. Therefore, there is an urgent need to understand the ecological interactions of the human urogenital microbial communities which precede rUTIs. This review aims to outline the mechanistic aspects of rUTI ecology underlying dysbiosis between both the human microbiome and host physiology which predisposes humans to rUTIs. By assessing the applications of next generation and systems level methods, we also recommend novel approaches to elucidate the systemic consequences of rUTIs which requires an integrated approach for successful treatment. To this end, we will provide an outlook towards the so-called ‘uncomplicated environment of UTIs’, a holistic and systems view that applies ecological principles to define patient-specific UTIs. This perspective illustrates the need to withdraw from traditional reductionist perspectives in infection biology and instead, a move towards a systems-view revolving around patient-specific pathophysiology during UTIs.

As a key indicator of childhood malnutrition, few studies have focused on stunting in relation to various socio-economic factors in which disadvantaged groups face in China. We conducted a community-based cross-sectional study incorporating forty-two rural counties in seven western provinces of China in 2011. In total, 5196 children aged 6–23 months were included. We used Poisson regression to examine risk factors for inadequate minimum dietary diversity (MDD) and stunting status, respectively. Overall, the proportion of children not meeting MDD was 44·5 %. Children aged 6–11 months (adjusted risk ratio (ARR)=1·39; 95 % CI 1·31, 1·49), with two siblings (ARR=1·09; 95 % CI 1·02, 1·17), delivered at home (ARR=1·30; 95 % CI 1·20, 1·41), within Yi (ARR=1·15; 95 % CI 1·04, 1·28) or Uighur groups (ARR=1·52; 95 % CI 1·36, 1·71), with an illiterate caregiver (ARR=2·12; 95 % CI 1·52, 2·96), receiving lowest income (ARR=1·32; 95 % CI 1·17, 1·50), and with breast-feeding in the last day (ARR=1·55; 95 % CI 1·44, 1·66) were more likely to have inadequate MDD. Moreover, inadequate MDD was positively associated with stunting (ARR=1·15; 95 % CI 1·01, 1·31). Other determinants for stunting were age, sex, place of delivery, minority group and income. The stunting prevalence and proportion of inadequate MDD remained high in Western China; to reduce stunting rates of ethnic minorities, further efforts addressing appropriate dietary feeding practices are needed, especially within these groups.

Limosilactobacillus reuteri , a probiotic microbe instrumental to human health and sustainable food production, adapts to diverse environmental shifts via dynamic gene expression. We applied the independent component analysis (ICA) to 117 RNA-seq data sets to decode its transcriptional regulatory network (TRN), identifying 35 distinct signals that modulate specific gene sets. Our findings indicate that the ICA provides a qualitative advancement and captures nuanced relationships within gene clusters that other methods may miss. This study uncovers the fundamental properties of L. reuteri ’s TRN and deepens our understanding of its arginine metabolism and the co-regulation of riboflavin metabolism and fatty acid conversion. It also sheds light on conditions that regulate genes within a specific biosynthetic gene cluster and allows for the speculation of the potential role of isoprenoid biosynthesis in L. reuteri ’s adaptive response to environmental changes. By integrating transcriptomics and machine learning, we provide a system-level understanding of L. reuteri ’s response mechanism to environmental fluctuations, thus setting the stage for modeling the probiotic transcriptome for applications in microbial food production. IMPORTANCE: We have studied Limosilactobacillus reuteri , a beneficial probiotic microbe that plays a significant role in our health and production of sustainable foods, a type of foods that are nutritionally dense and healthier and have low-carbon emissions compared to traditional foods. Similar to how humans adapt their lifestyles to different environments, this microbe adjusts its behavior by modulating the expression of genes. We applied machine learning to analyze large-scale data sets on how these genes behave across diverse conditions. From this, we identified 35 unique patterns demonstrating how L. reuteri adjusts its genes based on 50 unique environmental conditions (such as various sugars, salts, microbial cocultures, human milk, and fruit juice). This research helps us understand better how L. reuteri functions, especially in processes like breaking down certain nutrients and adapting to stressful changes. More importantly, with our findings, we become closer to using this knowledge to improve how we produce more sustainable and healthier foods with the help of microbes.

Parkinson’s Disease (PD) is a neurodegenerative disease, leading to motor and non-motor complications. Autonomic alterations, including gastrointestinal symptoms, precede motor defects and act as early warning signs. Chronic exposure to dietary, environmental heavy metals impacts the gastrointestinal system and host-associated microbiome, eventually affecting the central nervous system. The correlation between dysbiosis and PD suggests a functional and bidirectional communication between the gut and the brain. The bioaccumulation of metals promotes stress mechanisms by increasing reactive oxygen species, likely altering the bidirectional gut–brain link. To better understand the differing molecular mechanisms underlying PD, integrative modeling approaches are necessary to connect multifactorial perturbations in this heterogeneous disorder. By exploring the effects of gut microbiota modulation on dietary heavy metal exposure in relation to PD onset, the modification of the host-associated microbiome to mitigate neurological stress may be a future treatment option against neurodegeneration through bioremediation. The progressive movement towards a systems toxicology framework for precision medicine can uncover molecular mechanisms underlying PD onset such as metal regulation and microbial community interactions by developing predictive models to better understand PD etiology to identify options for novel treatments and beyond. Several methodologies recently addressed the complexity of this interaction from different perspectives; however, to date, a comprehensive review of these approaches is still lacking. Therefore, our main aim through this manuscript is to fill this gap in the scientific literature by reviewing recently published papers to address the surrounding questions regarding the underlying molecular mechanisms between metals, microbiota, and the gut–brain-axis, as well as the regulation of this system to prevent neurodegeneration.