Characteristics of the gut microbiome in women with gestational diabetes mellitus: A systematic review

Background The incidence of women developing gestational diabetes mellitus (GDM) is increasing, which is associated with an increased risk of type 2 diabetes mellitus (T2DM) for both mother and child. Gut microbiota dysbiosis may contribute to the pathogenesis of both GDM and the accompanying risk of T2DM. Thus, a better understanding of the microbial communities associated with GDM could offer a potential target for intervention and treatment in the future. Therefore, we performed a systematic review to investigate if the GDM women have a distinct gut microbiota composition compared to non-GDM women. Methods We identified 21 studies in a systematic literature search of Embase and PubMed up to February 24, 2021. Data on demographics, methodology and identified microbial metrics were extracted. The quality of each study was assessed according to the Newcastle-Ottawa Scale. Results Sixteen of the studies did find a GDM-associated gut microbiota, although no consistency could be seen. Only Collinsella and Blautia showed a tendency to be increased in GDM women, whereas the remaining genera were significantly different in opposing directions. Conclusion Although most of the studies found an association between GDM and gut microbiota dysbiosis, no overall GDM-specific gut microbiota could be identified. All studies in the second trimester found a difference between GDM and non-GDM women, indicating that dysbiosis is present at the time of diagnosis. Nevertheless, it is still unclear when the dysbiosis develops, as no consensus could be seen between the studies investigating the gut microbiota in the first trimester of pregnancy. However, studies varied widely concerning methodology and study design, which might explain the highly heterogeneous gut microbiota compositions between studies. Therefore, future studies need to include multiple time points and consider possible confounding factors such as ethnicity, pre-pregnancy body mass index, and GDM treatment.

Usefulness of circulating tumor DNA by targeting human papilloma virus-derived sequences as a biomarker in p16-positive oropharyngeal cancer

In head and neck cancer, early detection of recurrence after treatment is important. The contemporary development of therapeutic agents have improved the prognosis after recurrence; however, no biomarker has been established for evaluating therapeutic effects or detecting recurrence. Recently, circulating tumor DNA (ctDNA), which comprises DNA derived from tumor cells and exists in the form of cell-free DNA in the blood, has attracted attention as a minimally invasive and repeatable biomarker for detecting cancer. We validated the usefulness of ctDNA of human papilloma virus (HPV)-derived sequences as a biomarker in HPV-related p16-positive oropharyngeal cancer by assessing 25 patients with p16-positive oropharyngeal cancer. Blood samples were collected from each patient at multiple time points during the treatment, and the plasma was preserved. The ctDNA was extracted from the plasma and analyzed using digital polymerase chain reaction. HPV-derived ctDNA was detected in 14 (56%) of the 25 patients. In all the patients, the samples were found to be ctDNA-negative after initial treatment. Cancer recurrence was observed in 2 of the 14 patients; HPV-derived ctDNA was detected at the time of recurrence. Our results indicate that HPV-derived ctDNA can be a prospective biomarker for predicting the recurrence of p16-positive oropharyngeal cancer.

Design and Development of AI based Approach for Histopathology Cancer Screening and Identification

Cancer is a heterogeneous disorder comprising various types and sub-types. Early detection, screening, and diagnosis of cancer types are necessary for facilitating cancer research in early diagnosis, management, and the evolution of successful therapies. Existing methodologies were only able to classify and diagnose a single variety of cancer based on a homogeneous dataset but more focused on predicting patient survivability then cure. This research defines a machine learning-based methodology to develop an universal approach in diagnosis, detection, symptoms-based prediction, and screening of histopathology cancer, their types, and sub types using a heterogeneous dataset based on images and scans. In this architecture, we use VGG-19 based 3D-Convolutional Neural Network for deep feature extraction and later perform regression using a random forest algorithm. We create a heterogeneous dataset consisting of results from laboratory tests, imaging tests and biopsy reports, not only relying on clinical images. Initially, we categorize tumors and lesions as benign or malignant and classify the malignant lesions into their sub-types, detecting their severity and growth rate. Our system is designed to predict risk at multiple time-points, leverage optional risk factors if they are available and produce predictions that are consistent across mammography machines. We found the classification accuracy for categorizing tumors as cancerous to be 95% whereas the accuracy for classification of malignant lesions into their sub-types to be 94%..

Advanced understanding of prokaryotic biofilm formation using a cost-effective and versatile multi-panel adhesion (mPAD) mount

Most microorganisms exist in biofilms, which comprise aggregates of cells surrounded by an extracellular matrix that provides protection from external stresses. Based on the conditions under which they form, biofilm structures vary in significant ways. For instance, biofilms that develop when microbes are incubated under static conditions differ from those formed when microbes encounter the shear forces of a flowing liquid. Moreover, biofilms develop dynamically over time. Here, we describe a cost-effective, 3D-printed coverslip holder that facilitates surface adhesion assays under a broad range of standing and shaking culture conditions. This multi-panel adhesion (mPAD) mount further allows cultures to be sampled at multiple time points, ensuring consistency and comparability between samples and enabling analyses of the dynamics of biofilm formation. As a proof of principle, using the mPAD mount for shaking, oxic cultures, we confirm previous flow chamber experiments showing that Pseudomonas aeruginosa wild type and a phenazine deletion mutant (Δ phz ) form biofilms with similar structure but reduced density in the mutant strain. Extending this analysis to anoxic conditions, we reveal that microcolony and biofilm formation can only be observed under shaking conditions and are decreased in the Δ phz mutant compared to wild-type cultures, indicating that phenazines are crucial for the formation of biofilms if oxygen as an electron acceptor is unavailable. Furthermore, while the model archaeon Haloferax volcanii does not require archaella for surface attachment under static conditions, we demonstrate that H. volcanii mutants that lack archaella are impaired in early stages of biofilm formation under shaking conditions. Importance: Due to the versatility of the mPAD mount, we anticipate that it will aid the analysis of biofilm formation in a broad range of bacteria and archaea. Thereby, it contributes to answering critical biological questions about the regulatory and structural components of biofilm formation and understanding this process in a wide array of environmental, biotechnological, and medical contexts.

Estimation of causal effects of a time-varying exposure at multiple time points through Multivariable Mendelian randomization

Mendelian Randomisation (MR) is a powerful tool in epidemiology to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilising genetic variants as instrumental variables (IVs) for the exposure. The effects obtained from MR studies are often interpreted as the lifetime effect of the exposure in question. However, the causal effects of many exposures are thought to vary throughout an individual's lifetime and there may be periods during which an exposure has more of an effect on a particular outcome. Multivariable MR (MVMR) is an extension of MR that allows for multiple, potentially highly related, exposures to be included in an MR estimation. MVMR estimates the direct effect of each exposure on the outcome conditional on all of the other exposures included in the estimation. We explore the use of MVMR to estimate the direct effect of a single exposure at different time points in an individual's lifetime on an outcome. We use simulations to illustrate the interpretation of the results from such analyses and the key assumptions required. We show that causal effects at different time periods can be estimated through MVMR when the association between the genetic variants used as instruments and the exposure measured at those time periods varies, however this estimation will not necessarily identify exact time periods over which an exposure has the most effect on the outcome. We illustrate the method through estimation of the causal effects of childhood and adult BMI on smoking behaviour.

Effect of Sodium Selenite on the Metabolite Profile of Epichloë sp. Mycelia from Festuca sinensis in Solid Culture

Selenium (Se) is an essential micronutrient with many beneficial effects for humans and other living organisms. Numerous microorganisms in culture systems enrich and convert inorganic selenium to organic selenium. In this study, Epichloë sp. from Festuca sinensis was exposed to increasing Na2SeO3 concentrations (0, 0.1, 0.2, 0.3, and 0.4 mmol/L) in Petri dishes with potato dextrose agar (PDA) for 8 weeks. Epichloë sp. mycelia were immediately collected after mycelial diameters were measured at 4, 5, 6, 7, and 8 weeks of cultivation, respectively. Gas chromatography-mass spectrometer (GC-MS) analysis was performed on different groups of Epichloë sp. mycelia. Different changes were observed as Epichloë sp. was exposed to different selenite conditions and cultivation time. The colony diameter of Epichloë sp. decreased in response to increased selenite concentrations, whereas the inhibitory effects diminished over time. Seventy-two of the 203 identified metabolites did not differ significantly across selenite treatments within the same time point, while 82 compounds did not differ significantly between multiple time points of the same Se concentration. However, the relative levels of 122 metabolites increased the most under selenite conditions. Specifically, between the 4th and 8th weeks, there were increases in 2-keto-isovaleric acid, uridine, and maltose in selenite treatments compared to controls. Selenium increased glutathione levels and exhibited antioxidant properties in weeks 4, 5, and 7. Additionally, we observed that different doses of selenite could promote the production of carbohydrates such as isomaltose, cellobiose, and sucrose; fatty acids such as palmitoleic acid, palmitic acid, and stearic acid; and amino acids such as lysine and tyrosine in Epichloë sp. mycelia. Therefore, Epichloë sp. exposed to selenite stress may benefit from increased levels of some metabolite compounds.

Immunological and Genetic Investigation of SARS-CoV-2 Reinfection in an Otherwise Healthy, Young Marine Recruit

We used epidemiologic and viral genetic information to identify a case of likely reinfection in an otherwise healthy, young Marine recruit enrolled in the prospective, longitudinal COVID-19 Health Action Response for Marines (CHARM) study, and we paired these findings with serological studies. This participant had a positive RT-PCR to SARS-CoV-2 upon routine sampling on study day 7, although he was asymptomatic at that time. He cleared the infection within seven days. On study day 46, he had developed symptoms consistent with COVID-19 and tested positive by RT-PCR for SARS-CoV-2 again. Viral whole genome sequencing was conducted from nares swabs at multiple time points. The day 7 sample was determined to be lineage B.1.340, whereas both the day 46 and day 49 samples were B.1.1. The first positive result for anti-SARS-CoV-2 IgM serology was collected on day 49 and for IgG on day 91. This case appears most consistent with a reinfection event. Our investigation into this case is unique in that we compared sequence data from more than just paired specimens, and we also assayed for immune response after both the initial infection and the later reinfection. These data demonstrate that individuals who have experienced an infection with SARS-CoV-2 may fail to generate effective or long-lasting immunity, similar to endemic human beta coronaviruses.

Rethinking the Rule of 10s: Early Cleft Lip Repair Improves Weight Gain

Objective This study compares patients undergoing early cleft lip repair (ECLR) (<3-months) and traditional lip repair (TLR) (3-6 months) with/without nasoalveolar molding (NAM) to evaluate the effects of surgical timing on weight gain in hopes of guiding future treatment paradigms. Design Retrospective review. Setting Children's Hospital of Los Angeles, California. Patient, Participants A retrospective chart review evaluated patients who underwent ECLR or TLR ± NAM from November 2009 through January 2020. Interventions No intervention was performed. Main Outcome Measure(s) Patient demographics, birth and medical history, perioperative variables, and complications were collected. Infant weights and age-based percentiles were recorded at birth, surgery, 8-weeks, 6-months, 12-months, and 24-months postoperatively. The main outcomes were weight change and weight percentile amongst ECLR and TLR ± NAM groups. Results 107 patients met inclusion criteria: ECLR, n = 51 (47.6%); TLR + NAM, n = 35 (32.7%); and TLR-NAM, n = 21 (19.6%). ECLR patients had significantly greater changes in weight from surgery to 8-weeks and from surgery to 24-months postoperatively compared with both TLR ± NAM ( P < .05). Age-matched weights in the ECLR group were significantly greater than TLR ± NAM at multiple time points postoperatively ( P < .05). Conclusions ECLR significantly increased patient weights 24-months postoperatively when compared to TLR ± NAM. Specifically compared to TLR-NAM, ECLR weights were significantly greater at all time points past 6-months postoperatively. The results of this study demonstrate that ECLR can mitigate feeding difficulties and malnutrition traditionally seen in patients with cleft lip.

Determining and quantifying the historical traces of spatial land arrangements in rural landscapes of Central and Eastern Europe

The article attempts to define and determine the intangible components of cultural heritage related to the spatial structure of land in a comprehensive way using computational methods. The components were quantified and a method of empirical evaluation of landscape durability was proposed for agricultural areas of significant cultural and historical value with an evident mosaic structure of fields, baulks, ponds, meadows, and forests. This method allows us to identify places more resistant to political transformation and those with greater cultural potential. The paper proposed an integrated approach to the measuring of the degree of preservation of spatial arrangements in the landscape based on a set of objects that describe the spatial land structure. The article classifies areas by the degree of preservation of rural spatial arrangements of land. The spatial analysis employed facilitated a synthetic quantification of the multi-criteria process. Three groups of factors were used: spatial assessment of land-cover type persistence (u), agricultural land structure persistence (w), and persistence of settlement buildings (z). The final results pinpointed areas in need of strategic intervention to sufficiently protect the rural cultural heritage, properly consider them in zoning planning, and ensure their sustainable development. The proposed tool can be used to monitor the degree of changes in the landscape layout structure when multiple time points are analysed as well.