Metabolic Glycoengineering in hMSC-TERT as a Model for Skeletal Precursors by Using Modified Azide/Alkyne Monosaccharides

Metabolic glycoengineering enables a directed modification of cell surfaces by introducing target molecules to surface proteins displaying new features. Biochemical pathways involving glycans differ in dependence on the cell type; therefore, this technique should be tailored for the best results. We characterized metabolic glycoengineering in telomerase-immortalized human mesenchymal stromal cells (hMSC-TERT) as a model for primary hMSC, to investigate its applicability in TERT-modified cell lines. The metabolic incorporation of N-azidoacetylmannosamine (Ac₄ManNAz) and N-alkyneacetylmannosamine (Ac₄ManNAl) into the glycocalyx as a first step in the glycoengineering process revealed no adverse effects on cell viability or gene expression, and the in vitro multipotency (osteogenic and adipogenic differentiation potential) was maintained under these adapted culture conditions. In the second step, glycoengineered cells were modified with fluorescent dyes using Cu-mediated click chemistry. In these analyses, the two mannose derivatives showed superior incorporation efficiencies compared to glucose and galactose isomers. In time-dependent experiments, the incorporation of Ac₄ManNAz was detectable for up to six days while Ac₄ManNAl-derived metabolites were absent after two days. Taken together, these findings demonstrate the successful metabolic glycoengineering of immortalized hMSC resulting in transient cell surface modifications, and thus present a useful model to address different scientific questions regarding glycosylation processes in skeletal precursors.     

On Two‐Stage Estimation of the Spectral Density with Assigned Risk in Presence of Missing Data

Estimation with assigned risk is a classical statistical problem, and the theory is well developed for the case of directly observed (no missing) data. In this article a more complicated problem of estimation of the spectral density in presence of missing data is considered. First, the corresponding theory of sequential estimation with minimal expected stopping time is developed. Then it is shown that a two‐stage estimator may be used and it yields the minimal stopping time. Sample size of the first stage may be deterministic and in order smaller than a minimal stopping time, and then the first stage defines the size of the second stage. Furthermore, the estimator adapts to unknown smoothness of an underlying spectral density and to an underlying missing mechanism.     

Reusable and durable electrostatic air filter based on hybrid metallized microfibers decorated with metal-organic-framework nanocrystals

As global air pollution becomes increasingly severe,various types of fibrous filters have been devel-oped to improve air filter performance.However,fibrous filters have limitations such as high packing density that generally causes high-pressure drop and ultimately deterioration in the filtration effi-ciency.High-pressure particulate matter precipitators are limited in terms of scope for commercialization because they require high voltage supplies and ozone generators.In this study,we develop fibrous fil-ters with enhanced durability and improved performance using metallized microfibers decorated with metal-organic-framework(MOF)nanocrystals.Not only does the efficiency of the developed filters remain at or above 97％for 0.50-1.5 μm PMs but the durability also significantly increases.In addi-tion,using the water purification ability of the MOF,we explore the dye degradation effect of the hybrid microfibers by immersing them into Rhodamine B aqueous solution.In such an experiment the Rho-damine B aqueous solution is completely purified by the presence of the hybrid microfibers under the UV irradiation.     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Hydrodynamic drag constrains head enlargement for mouthbrooding in cichlids

Presumably as an adaptation for mouthbrooding, many cichlid fish species have evolved a prominent sexual dimorphism in the adult head. Since the head of fishes serves as a bow during locomotion, an evolutionary increase in head volume to brood more eggs can trade-off with the hydrodynamic efficiency of swimming. Here, the differences between males and females in three-dimensional shape and size of the external head surfaces and the effect thereof on drag force during locomotion was analysed for the Nile tilapia (Oreochromis niloticus), a maternal mouthbrooder. To do so, three-dimensional body surface reconstructions from laser scans and computational fluid dynamics simulations were performed. After scaling the scanned specimens to post-cranial body volume, in order to theoretically equalize propulsive power, the external volume of the head of females was 27% larger than that of males (head length + 14%; head width + 9%). These differences resulted in an approximate 15% increase in drag force. Yet, hydrodynamics imposed important constraints on the adaptation for mouthbrooding as a much more drastic drop in swimming efficiency seems avoided by mainly enlarging the head along the swimming direction.     

COVID-19 hospitalization rates rise exponentially with age,inversely proportional to thymic T-cell production

Here, we report that COVID-19 hospitalization rates follow an exponential relationship with age, doubling for every 16 years of age or equivalently increasing by 4.5% per year of life (R² = 0.98). This mirrors the well-studied exponential decline of both thymus volume and T-cell production, which halve every 16 years. COVID-19 can therefore be added to the list of other diseases with this property, including those caused by methicillin-resistant Staphylococcus aureus, MERS-CoV, West Nile virus, Streptococcus pneumoniae and certain cancers, such as chronic myeloid leukaemia and brain cancers. In addition, the incidence of severe disease and mortality due to COVID-19 are both higher in men, consistent with the degree to which thymic involution (and the decrease in T-cell production with age) is more severe in men compared to women. Since these properties are shared with some non-contagious diseases, we hypothesized that the age dependence does not come from social-mixing patterns, i.e. that the probability of hospitalization given infection rises exponentially, doubling every 16 years. A Bayesian analysis of daily hospitalizations, incorporating contact matrices, found that this relationship holds for every age group except for the under 20s. While older adults have fewer contacts than young adults, our analysis suggests that there is an approximate cancellation between the effects of fewer contacts for the elderly and higher infectiousness due to a higher probability of developing severe disease. Our model fitting suggests under 20s have 49–75% additional immune protection beyond that predicted by strong thymus function alone, consistent with increased juvenile cross-immunity from other viruses. We found no evidence for differences between age groups in susceptibility to infection or infectiousness to others (given disease state), i.e. the only important factor in the age dependence of hospitalization rates is the probability of hospitalization given infection. These findings suggest the existence of a T-cell exhaustion threshold, proportional to thymic output and that clonal expansion of peripheral T-cells does not affect disease risk. The strikingly simple inverse relationship between risk and thymic T-cell output adds to the evidence that thymic involution is an important factor in the decline of the immune system with age and may also be an important clue in understanding disease progression, not just for COVID-19 but other diseases as well.     

Regulatory RNAs: A Universal Language for Inter-Domain Communication

In eukaryotes, microRNAs (miRNAs) have roles in development, homeostasis, disease and the immune response. Recent work has shown that plant and mammalian miRNAs also mediate cross-kingdom and cross-domain communications. However, these studies remain controversial and are lacking critical mechanistic explanations. Bacteria do not produce miRNAs themselves, and therefore it is unclear how these eukaryotic RNA molecules could function in the bacterial recipient. In this review, we compare and contrast the biogenesis and functions of regulatory RNAs in eukaryotes and bacteria. As a result, we discovered several conserved features and homologous components in these distinct pathways. These findings enabled us to propose novel mechanisms to explain how eukaryotic miRNAs could function in bacteria. Further understanding in this area is necessary to validate the findings of existing studies and could facilitate the use of miRNAs as novel tools for the directed remodelling of the human microbiota.