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Optomagnetic Coordination Helical Robot with Shape Transformation and Multimodal Motion Capabilities
No full textSoft robots with magnetic responsiveness exhibit diverse
motion
modes and programmable shape transformations. While the fixed magnetization
configuration facilitates coupling control of robot posture and motion,
it limits individual posture control to some extent. This poses a
challenge in independently controlling the robot’s transformation
and motion, restricting its versatile applications. This research
introduces a multifunctional helical robot responsive to both light
and magnetism, segregating posture control from movements. Light fields
assist in robot shaping, achieving a 78% maximum diameter shift. Magnetic
fields guide helical robots in multimodal motions, encompassing rotation,
flipping, rolling, and spinning-induced propulsion. By controlling
multimodal locomotion and shape transformation on demand, helical
robots gain enhanced flexibility. This innovation allows them to tightly
grip and wirelessly transport designated payloads, showcasing potential
applications in drug delivery, soft grippers, and chemical reaction
platforms. The unique combination of structural design and control
methods holds promise for intelligent robots in the future
Machine Learning Models and Dimensionality Reduction for Prediction of Polymer Properties
No full textAccurate prediction of block polymer properties as a
function of
monomer sequence is necessary for better material development. The
number of permutations of chemistry and sequence is nearly infinite,
and new methods are needed to predict and engineer properties as a
function of molecular structure. In this work, we present a machine
learning approach to determine polymer properties where a feed-forward
neural network is trained to predict the period length of a diblock
lamellar system as a function of block sequence and interaction parameters.
These sequenced polymers are similar to experimentally explored polypeptoid
systems. Additionally, we report on our efforts to explore dimensionality
reduction as a method for gaining physical insights into these polymeric
materials
Characterization of the complete chloroplast genome of <i>Barbella flagellifera</i> (Cardot) Nog. 1938 (Bryidae, Meteoriaceae)
No full textWhether Barbella flagellifera (Cardot) Nog. belongs to Neodicladiella has not yet been determined, and a study of the complete chloroplast (cp) genome of B. flagellifera would aid in determining its evolutionary position. In this study, we aimed to sequence the complete cp genome of B. flagellifera, an epiphytic species found in tropical and subtropical forests. The complete cp genome is 125,025 base pairs (bp) long and appears as a typical quadrilateral structure with a large single-copy (86,854 bp), a small single-copy (18,473 bp), and a pair of inverted repeats (19,698 bp). The overall GC content of the sequence is 41.0% and the genome encodes 127 genes, including 82 protein-coding genes, 37 tRNAs, and eight rRNAs. Phylogenetic analysis reveals that B. flagellifera clustered into a clade with other Hypnales groups with high bootstrap support. The complete cp genome presented here will provide helpful information for species identification of Barbella genus and Neodicladiella genus in Meteoriaceae.</p
Upper airway epithelial tissue transcriptome analysis reveals immune signatures associated with COVID-19 severity in Ghanaians.
No full textThe immunological signatures driving the severity of coronavirus disease 19 (COVID-19) in Ghanaians remain poorly understood. We performed bulk transcriptome sequencing of nasopharyngeal samples from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected Ghanaians with mild and severe COVID-19, as well as healthy controls to characterize immune signatures at the primary SARS-CoV-2 infection site and identify drivers of disease severity. Generally, a heightened antiviral response was observed in SARS-CoV-2-infected Ghanaians compared with uninfected controls. COVID-19 severity was associated with immune suppression, overexpression of proinflammatory cytokines, including CRNN, IL1A, S100A7, and IL23A, and activation of pathways involved in keratinocyte proliferation. SAMD9L was among the differentially regulated interferon-stimulated genes in our mild and severe disease cohorts, suggesting that it may play a critical role in SARS-CoV-2 pathogenesis. By comparing our data with a publicly available dataset from a non-African (Indians) (GSE166530), an elevated expression of antiviral response-related genes was noted in COVID-19-infected Ghanaians. Overall, the study describes immune signatures driving COVID-19 severity in Ghanaians and identifies immune drivers that could serve as potential prognostic markers for future outbreaks or pandemics. It further provides important preliminary evidence suggesting differences in antiviral response at the upper respiratory interface in sub-Saharan Africans (Ghanaians) and non-Africans, which could be contributing to the differences in disease outcomes. Further studies using larger datasets from different populations will expand on these findings
Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees
No full textWe present a new methodology for handling AIerrors by introducing weakly supervised AI error correctors witha prioriperformance guarantees. These AI correctors are auxiliarymaps whose role is to moderate the decisions of some previouslyconstructed underlying classifier by either approving or rejectingits decisions. The rejection of a decision can be used as a signalto suggest abstaining from making a decision. A key technicalfocus of the work is in providing performance guarantees forthese new AI correctors through bounds on the probabilities ofincorrect decisions. These bounds are distribution agnostic anddo not rely on assumptions on the data dimension. Our empiricalexample illustrates how the framework can be applied to improvethe performance of an image classifier in a challenging real-worldtask where training data are scarce.</p
Table2_Processing of Reynoutria multiflora: transformation of catechin and gallic acid derivatives and their identification.DOCX
No full textIntroduction: The root of Reynoutria multiflora (Thunb.) Moldenke (RM) has been used widely in formulations of herbal medicines in China for centuries. Raw R. multiflora (RRM) should be processed before use to reduce toxicity and increase efficacy. However, detailed regulation of the processing endpoint is lacking, and the duration of processing can vary considerably. We conducted in-depth research on stilbene glycosides in RM at different processing times. Previously, we discovered that 219 stilbene glycosides changed markedly in quantity and content. Therefore, we proposed that processing causes changes in various chemical groups.Methods: To better explain the mechanism of RM processing for toxicity reduction and efficacy enhancement, we used a method of tandem mass spectrometry described previously to research gallic acid based and catechin based metabolites.Results: A total of 259 metabolites based on gallic acid and 112 metabolites based on catechins were identified. Among these, the peak areas of 157 gallic acid and 81 catechins gradually decreased, those of another 71 gallic acid and 30 catechins first increased and then decreased, those of 14 gallic acid and 1 catechin gradually increased. However, 17 of the gallic acids showed no significant changes. We speculate that many gallic acid metabolites hydrolyze to produce gallic acid; moreover, the dimers/trimers of catechins, after being cleaved into catechins, epicatechin, gallic acid catechins, and epicatechin monomers, are cleaved into gallic acid and protocatechualdehyde under high temperature and high humidity, subsequently participating in the Maillard reaction and browning reactions.Discussion: We showed that processing led to changes in chemical groups, clarification of the groups of secondary metabolites could provide a basis for research on the pharmacological and toxic mechanisms of RM, as well as the screening of related markers.</p
Data, machine learning models weights, and results used for the analyses in the paper entitled "Predicting microbial community structure and temporal dynamics by using graph neural network models".
No full textAbstract from the manuscript:Modeling or even predicting the dynamics of complex microbial communities comprising thousands of individual species has been a long-standing challenge within microbial ecology. In biological wastewater treatment plants (WWTPs) an optimal microbial community composition is critical to effectively remove or recycle resources from human activities that would otherwise pollute the environment. Both the presence and abundance of process-critical microorganisms are important for the overall performance, and the relative abundance of the individual species can vary greatly over time without any recurring abundance dynamics. Being able to predict the future abundance dynamics can therefore be a great help for WWTP operators to prevent problems in time and optimize operation and performance. Here we used a graph neural network based model design that, for the first time, enables accurate prediction of the future abundance dynamics of the majority of bacteria in the microbial communities of activated sludge several months ahead. We trained and tested models on time series datasets from 24 different Danish full-scale WWTPs sampled 2-5 times a month over a period of 3-8 years totalling 4709 environmental samples. We were able to predict the dynamics 10 time points into the future (2-4 months) with high accuracy for most of the abundant bacteria, especially process-critical bacteria, and some even 20 time points ahead (up to 8 months). The approach was implemented as a workflow suitable for any longitudinal community dataset, and is not limited to the AS ecosystem alone.</p
Table3_Quantitative proteomics reveals the protective effects of Yinchenzhufu decoction against cholestatic liver fibrosis in mice by inhibiting the PDGFRβ/PI3K/AKT pathway.XLSX
No full textIntroduction: Yinchenzhufu decoction (YCZFD) is a traditional Chinese medicine formula with hepatoprotective effects. In this study, the protective effects of YCZFD against cholestatic liver fibrosis (CLF) and its underlying mechanisms were evaluated.Methods: A 3, 5-diethoxycarbonyl-1, 4-dihydro-collidine (DDC)-induced cholestatic mouse model was used to investigate the amelioration of YCZFD on CLF. Data-independent acquisition-based mass spectrometry was performed to investigate proteomic changes in the livers of mice in three groups: control, model, and model treated with high-dose YCZFD. The effects of YCZFD on the expression of key proteins were confirmed in mice and cell models.Results: YCZFD significantly decreased the levels of serum biochemical, liver injury, and fibrosis indicators of cholestatic mice. The proteomics indicated that 460 differentially expressed proteins (DEPs) were identified among control, model, and model treated with high-dose YCZFD groups. Enrichment analyses of these DEPs revealed that YCZFD influenced multiple pathways, including PI3K-Akt, focal adhesion, ECM–receptor interaction, glutathione metabolism, and steroid biosynthesis pathways. The expression of platelet derived growth factor receptor beta (PDGFRβ), a receptor associated with the PI3K/AKT and focal adhesion pathways, was upregulated in the livers of cholestatic mice but downregulated by YCZFD. The effects of YCZFD on the expression of key proteins in the PDGFRβ/PI3K/AKT pathway were further confirmed in mice and transforming growth factor-β-induced hepatic stellate cells. We uncovered seven plant metabolites (chlorogenic acid, scoparone, isoliquiritigenin, glycyrrhetinic acid, formononetin, atractylenolide I, and benzoylaconitine) of YCZFD that may regulate PDGFRβ expression.Conclusion: YCZFD substantially protects against DDC-induced CLF mainly through regulating the PDGFRβ/PI3K/AKT signaling pathway.</p
Effects of long-term application of inorganic fertilizers and organic amendments on the turnover rates of fractionated soil organic carbon and their determining factors in paddy fields
No full textTo investigate how the long-term application of inorganic fertilizer and organic amendments affects the turnover rates of organic matter in physico-chemically fractionated components in paddy soils and how their rates are related to their amounts, we studied the effect of variable management of inorganic fertilizer and organic amendments for > 50 years on the ∆14C values of accumulated soil organic carbon (SOC) in fractionated components of 5 soil samples from three paddy fields. SOC was fractionated into four components based on their physico-chemical properties: (1) light fraction (LF) derived from plant residues, (2) heavy fraction (HF) containing stable aggregates, (3) oxidizable fraction (OxF) and (4) non-oxidizable fraction (NOxF) forming organo-mineral complexes with fine-textured minerals. The ∆14C values were determined by accelerator mass spectrometry using graphitized samples. The ∆14C values of SOC in NOxF (from −305‰ to − 90.5‰) were much lower than those of HF (from −123‰ to − 3.7‰) and OxF (from −215‰ to 21.0‰). Lowest values for NOxF suggested slowest turnover rates as expected, and higher and comparable values for OxF and HF implied much faster turnover rates of SOC in OxF compared with upland soils. This could be one of the characteristics of SOC dynamics in paddy soils, probably reflecting repeated puddling of plow layer soils. ∆14C values in all the fractions increased in response to the application of inorganic fertilizer and organic amendments, suggesting faster turnover rate. Soils with clayey and weathered characteristics had the lowest ∆14C values, or slowest turnover rates among the study fields. The relationship between the ∆14C value and the amount of accumulated C for HF, OxF and NOxF indicated that the more the SOC accumulated, the faster the turnover rate of the SOC was, regardless of the fractions, and the relationship of the HF was considerably different from those of OxF and NOxF. In conclusion, these results can be the basis for understanding the C dynamics and for improving soil fertility status and soil C sequestration in paddy soils.</p