Type I hypersensitivity, also known as classical allergy, is mediated via allergen-specific IgE antibodies bound to type I FcR (FcεRI) on the surface of mast cells and basophils upon cross-linking by allergens. This IgE-mediated cellular activation may be blocked by allergen-specific IgG through multiple mechanisms, including direct neutralization of the allergen or engagement of the inhibitory receptor FcγRIIb which blocks IgE signal transduction. In addition, co-engagement of FceRI and FcγRIIb by IgE-IgG-allergen immune-complexes causes down-regulation of receptor bound IgE, resulting in desensitization of the cells. Both, activation of FceRI by allergen-specific IgE and engagement of FcγRIIb by allergen-specific IgG are driven by allergen-binding. Here we delineate the distinct roles of antibody affinity versus avidity in driving these processes and discuss the role of IgG subclasses in inhibiting basophil and mast cell activation.

Zymomonas mobilis is an emerging chassis for being engineered to produce bulk products due to its glycolysis through the Entner-Doudoroff pathway with less ATP produced for lower biomass accumulation and higher yields with targeted products. When self-flocculated, the bacterial cells are more productive and tolerant to stresses for high product titers, but this morphology needs to be controlled properly to avoid internal mass transfer limitation associated with strong flocculation. Herewith we explored the regulation of cyclic diguanosine monophosphate (c-di-GMP) on self-flocculation of the bacterial cells through cellulose biosynthesis. While ZMO1365 and ZMO0919 with GGDEF domains for diguanylate cyclase activities catalyze c-di-GMP biosynthesis, ZMO1487 with an EAL domain for phosphodiesterase activities catalyzes c-di-GMP degradation, but ZMO1055 and ZMO0401 contain the dual domains with phosphodiesterase activities predominated. Since c-di-GMP is synthesized from GTP, the intracellular accumulation of this signal molecule through deactivating the activity of phosphodiesterase is preferred for activating cellulose biosynthesis to flocculate the bacterial cells, since such a strategy exerts less perturbance on intracellular processes regulated by GTP. These discoveries are significant not only for engineering unicellular Z. mobilis strains with the self-flocculating morphology to boost production, but also for understanding mechanism underlying c-di-GMP biosynthesis and degradation in the bacterium.

The practice of documenting pharmacists’ interventions (PIs) has been endorsed by many hospital pharmacists’ societies and organizations worldwide. Current systems for recording PIs have been developed to generate data on better patient and healthcare outcomes, but harmonization and transferability are apparently minimal. The present work aims to provide a descriptive and comprehensive overview of the currently utilized PIs documentation and classification (D/C) tools contributing to increased evidence systematization. A systematic literature search was conducted in PUBMED, Scopus, Web of Science and CINAHL. Studies from 2008, after the release of the Basel Statements, were included if interventions were made by the hospital or clinical pharmacists in a global hospital setting. Publications quality assessment was accomplished using the Mixed Methods Appraisal Tool (MMAT). A total of 26 studies were included. Three studies did not refer to the D/C method, 10 used an in-house developed D/C method, seven used externally developed D/C tools and six studies described method validation or translation. Evidence confirmed that most of the D/C systems are designed in-house, but external development and validation of PI systems to be used in hospital practice is gradually increasing. Reports on validated PIs D/C tools that are being used in hospital clinical practice are limited, including countries with advanced hospital pharmacy practice. Unmet needs and gaps in practice were identified. Further research should be conducted to understand why using validated D/C methods is not a disseminated practice, knowing patients’ and organizational advantages.

We describe methods and software resources for a bioimpedance measurement technique, “trans-radial electrical bioimpedance velocimetry” that allows for the non-invasive monitoring of relative cardiac contractility and stroke volume, proxies of sympathetic cardiac tone. In addition to describing the general recording methodology, which requires impedance measurements of the forearm, we provide open source Jupyter based software (operable on most computers) for deriving cardiac contractility from the impedance measurements. We demonstrate the ability of this bioimpedance measurement for tracking event related contractility in a maximal grip force production task. Critically, the results demonstrate both a reactive increase in cardiosympathetic drive with force production as well as a learned increase in drive prior to grip onset, consistent with allostatic autonomic regulation. The method and software should be of broad utility for investigations of event related cardio-sympathetic regulation in psychophysical studies.

The current strategy for biodiversity conservation is doomed. Based on a study of evidence-based summaries known as environmental impact assessment reports produced over the past 44 years, we suggest that biodiversity loss has not been halted because of a failure to accurately identify and assess the ecological effects of the drivers of change linked to land use planning. This failure is due to the poor representativeness of biological diversity in the practices of planners and the inadequate involvement of the ecologist community. Researchers in ecology could play a key role in improving the environmental considerations in project designs by focusing on preventive assessments instead of curative solutions.

Human activities have increased the intensity and frequency of natural stressors and created novel stressors, altering host-pathogen interactions, and changing the risk of emerging infectious diseases. Despite the ubiquity of such anthropogenic impacts, predicting the directionality of outcomes has proven challenging. Here, we conduct a systematic review and meta-analysis to determine the primary mechanisms through which stressors affect host-pathogen interactions and to evaluate the impacts stress has on host fitness (survival and fecundity) and pathogen infectivity (prevalence and intensity). We assessed 893 effect sizes from 71 host species (representing seven taxonomic groups) and 78 parasite taxa from 98 studies. We found that infected and uninfected hosts had similar sensitivity to stressors and that responses varied according to stressor type. Specifically, limited resources compromised host fecundity and decreased pathogen intensity, while abiotic environmental stressors (e.g., temperature and salinity) decreased host survivorship and increased pathogen intensity, and pollution increased mortality but decreased pathogen prevalence. We then used our meta-analysis results to develop Susceptible-Infected theoretical models to illustrate scenarios where infection rates are expected to increase or decrease in response to resource limitation or environmental stress gradients. Our results carry implications for conservation and disease emergence and reveal areas for future work.

Osteoarthritis (OA) , known as an inflammatory disease, affects the quality of life of countless people all around the world. In this ex vivo study, the anti-inflammatory effects of alcoholic extract S. lavandulifolia Vahl were investigated. Anti-inflammatory effects S. lavandulifolia Vahl. was evaluated based on measuring the levels of mRNA expression of pro-inflammatory genes including TNF-α , iL-1β , COX-2, and iNOS in bovine fibroblast-like synoviocytes and the levels of NO and PGE2 in Human THP-1 cells. Cells were treated with 100 ng/ml LPS in both the absence and presence of Alcoholic Extract S. lavandulifolia Vahl (AESL) (7.5µg/ml) that had no cytotoxic effects, as measured with MTT and trypan blue assays. Results showed that S. lavandulifolia Vahl. downregulated TNF-α (41.24%), iL-1β (47.12%), COX-2 (44.92%), and iNOS (45.34%) expression in BFLS, downregulated TNF-α (56.8%), iL-6 (58.04%) and iL-18 (52.59%) in THP-1 activated cells and this suppression was paralleled by a significant reduction in PGE2 (52.12%) and NO (51.06%) in cellular supernatant of THP-1. For the first time, our results suggested that S. lavandulifolia Vahl exerts has anti-inflammatory effects through the suppression of TNF-α, IL-1β, COX-2, and iNOS in bovine fibroblast synoviocytes along with the reduction in NO and PGE2 production in THP-1 cells.

TITLE : Embedding communication concepts in forecasting training increases students’ understanding of ecological uncertainty Submitted as an Article to Ecosphere , Eco-Education TrackAUTHOR LIST: Whitney M. Woelmera*, Tadhg N. Moorea,b11Present address: School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland, Mary E. Loftona, R. Quinn Thomasa,b, and Cayelan C. CareyaaDepartment of Biological Sciences, Virginia Tech, Blacksburg, VA, USAbDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, USA*Corresponding author: wwoelmer@vt.eduOPEN RESEARCH STATEMENT : This study collected and analyzed human subject data and was approved by the Virginia Tech Institutional Review Board (19-669) and the Carleton College Institutional Review Board (19-20 065). Data for this study have been anonymized and aggregated and can be found at Woelmer (2023) along with all code to reproduce the analysis and figures within this study.Woelmer, W. 2023. Wwoelmer/module8_public_ecosphere: Ecosphere submission March 2023 (v1.0). Zenodo. https://doi.org/10.5281/zenodo.7733965KEYWORDS : active learning, ecology education, ecological forecast, Macrosystems EDDIE, R Shiny, teaching modules, translational ecology, undergraduate curricula, visualization literacyABSTRACT : Communicating and interpreting uncertainty in ecological model predictions is notoriously challenging, motivating the need for new educational tools which introduce ecology students to core concepts in uncertainty communication. Ecological forecasting, an emerging approach to estimate future states of ecological systems with uncertainty, provides a relevant and engaging framework for introducing uncertainty communication to undergraduate students, as forecasts can be used as decision support tools for addressing real-world ecological problems and are inherently uncertain. To provide critical training on uncertainty communication and introduce undergraduate students to the use of ecological forecasts for guiding decision-making, we developed a hands-on teaching module within the Macrosystems EDDIE (Environmental Data-Driven Inquiry and Exploration; MacrosystemsEDDIE.org) educational program. Our module used an active learning approach by embedding forecasting activities in an R Shiny application to engage introductory students in data science, ecological modeling, and forecasting without needing advanced computational or programming skills. Pre- and post-module assessment data from >250 undergraduate ecology students indicate that the module significantly increased students’ ability to interpret forecast visualizations with uncertainty, identify different ways to communicate forecast uncertainty for diverse users, and correctly define ecological forecasting terms. Specifically, students were more likely to describe visual, numeric, and probabilistic methods of uncertainty communication following module completion. Students were also able to identify more benefits of ecological forecasting following module completion, with the key benefits of using forecasts for prediction and decision-making most commonly described. These results show promise for introducing ecological model uncertainty, data visualizations, and forecasting into undergraduate ecology curricula via software-based learning, which can increase students’ ability to engage and understand complex ecological concepts.

The occurrence of random mutations can increase the diversity of the genome and promote the evolutionary process of organisms. High efficiency mutagenesis techniques significantly accelerate the evolutionary process. In this work, we describe a targeted in vivo mutagenesis system to significantly increase mutation frequency and generate mutations across all four nucleotides. We constructed different DNA-modifying enzyme-PmCDA1-T7 RNA polymerase fusion proteins, achieved targeted mutagenesis by flanking the target gene with T7 promoters, and tuned the mutation spectra by introducing different DNA-modifying enzymes. With the mutagenesis fusion proteins, the mutation frequency of the target gene could reach 5.13x10-3, and the proportion of non-C→T mutations is 10~11-fold higher than the cytidine-based evolutionary tools. We also demonstrated that our mutagenesis tools could be used to evolve the essential enzyme in the β-carotene biosynthesis process and generate mutations with different types.

In order to meet the growing demand for productivity and cost effectiveness, the manufacturing setup needs to run the operation with minimal failures, yielding higher availability. This makes it challenging for the manufacturing companies to run their operations economically ensuring the availability and reliability by adopting a full proof maintenance management system. Though reliability-centered maintenance (RCM) is adopted across industries to improve availability and reliability, there is still a lot of scope for improvement. To monitor machinery performance parameters and health conditions on a real-time basis, digitalization is required in the field of maintenance management systems. Industry 4.0 can be used as a tool in RCM, which will strengthen the maintenance management system. It will help to fetch enormous data and perform subsequent analysis for improved availability and reliability. A smart RCM model is proposed in this paper for implementation in the maintenance management system to make it more effective. It describes how manufacturing and other industries can benefit from deploying Industry 4.0, which comprises IOT (the Internet of Things), CPS (the Cyber Physical System), cloud computing, and cognitive computing, converting conventional RCM (reliability-centered maintenance) into smart RCM.

Compressed sensing (CS) techniques have enabled efficient acquisition and recovery of sparse high-dimensional data via succinct low-dimensional projections, which usually consist of an encoder and a decoder. Unlike conventional CS techniques with the encoding-decoding architecture, the uncertainty autoencoder (UAE) can sample from the learned input data distribution without an explicit likelihood function, hence avoids potential uninformative latent representations. However, existing works on UAE mainly focus on the encoders and maximize the lower bound of the mutual information between input and measurements, rather than the decoders, which brings the shortcoming that the two may not cope well. In this letter, we propose a novel training scheme for UAE that blurs the measurements to learn the encoder and decoder simultaneously. Experimental results show that the proposed method improves the reconstruction performances when applied to UAE.

Blockchain technology is a promising technology that attracts popularity among researchers. However, it was first introduced with digital currencies in particular Bitcoin, but nowadays it is also known as one of the most frequently used techniques for securing networks. This systematic review research identifies studies that use blockchain for their security challenges. In addition, different fields in blockchain usage, blockchain categorization type, consensus mechanism, smart contract usage, and integration with other software-based algorithm is also investigated. Our results maintain that the internet of things (IoT) is the main field that blockchain is used to provide security.

The paper proposes an alternative approach to improve the performance of image retrieval. In this work, a framework for image retrieval based on machine learning and semantic retrieval is proposed. In the preprocessing phase, the image is segmented objects by using Graph-cut, and the feature vectors of objects presented in the image and their visual relationships are extracted using R-CNN. The feature vectors, visual relationships, and their symbolic labels are stored in KD-Tree data structures which can be used to predict the label of objects and visual relationships later. To facilitate semantic query, the images use the RDF data model and create an ontology for the symbolic labels annotated. For each query image, after extracting their feature vectors, the KD-Tree is used to classify the objects and predict their relationship. After that, a SPARQL query is built to extract a set of similar images. The SPARQL query consists of triple statements describing the objects and their relationship which were previously predicted. The evaluation of the framework with the MS-COCO dataset and Flickr showed that the precision achieved scores of 0.9218 and 0.9370 respectively.

Negative plant-soil feedbacks can be viewed as Janzen-Connell effects and influence plant population dynamics in grasslands. However, even though plant-soil feedbacks are often referred to as a mechanism for Janzen-Connell effects, for grassland species this is based on pot experiments and these effects have rarely been examined in the field. We examined the spatial distribution of a monocarpic perennial Jacobaea vulgaris to infer whether there is a distance- and/or density dependent effect and if the pattern is soil-mediated. Replicated plots were constructed to investigate J. vulgaris populations at two sites. Rosettes and flowering plants were marked, and their coordinates were recorded within each plot. For three plots, plants were tracked repeatedly during a single season to examine temporal distribution patterns. We then examined distance- and density dependent effects with spatial point pattern analysis. We also collected soil underneath flowering plants and 0.5-meter away from each plant. Seed germination, survival and growth of seedlings were traced in these soils with bioassays. Further, we measured biomass of J. vulgaris grown in soil from patches with high densities of J. vulgaris and in soil from outside of these patches. The density of rosettes was generally lower than expected from null models at close distances from flowering plants. The degree of clustering decreased from rosettes to flowering plants indicating density dependent self-thinning. Both the distance-based decay in rosette density and life-stage-dependent spacing became stronger over time in the plots where repeated measures were taken. Seed germination was higher in soil further away than in soil underneath flowering plants. However, seedling mortality and biomass did not differ in soils from different distances, and plants produced similar biomass in soil from pairwise patches. Our study provides spatial-based evidence for Janzen-Connell effects of J. vulgaris, and suggests plant-soil feedbacks play a minor role in mediating Janzen-Connell effects.

Introduction: In this paper we examine the relationship between vaccination against COVID-19 and both the death rate from COVID-19 and the rate of COVID-19 spread. Our goal is determine if vaccination is associated with reduced death and/or spread of disease at the local level. Methods: This analysis was conducted at the county level in the state of Pennsylvania, United States of America, with data that were collected during the first half of 2022 from the state of Pennsylvania’s Covid Dashboard ([COVID-19 Data for Pennsylvania (pa.gov)](https://www.health.pa.gov/topics/disease/coronavirus/pages/cases.aspx) . Result s: Given that, during this time period, the vaccines being used were not geared specifically toward the common variants at that time, we found no statistically significant relationship between disease spread and vaccination rate at the county level. That said, we did find a highly statistically significant relationship between death rate and vaccination rate (p-value = 0.006). Specifically, a 1% increase in vaccination rate was found to correspond to a 0.751% decrease in death rate (95% confidence interval (0.236%, 1.266%)). Conclusions: These results support previous findings from across the world that Covid vaccination is highly efficacious in preventing death from the disease. Even during a time when vaccine design was not optimally matched with the prevailing strains, vaccination was found to reduce death rate. Hence, improving global vaccine availability is vitally important, in order to achieve necessary outcomes.

Transfusion-related acute lung injury under general anesthesia successfully treated with extracorporeal membrane oxygenation: A case report

INTRODUCTION: Tourette’s syndrome is a neurodevelopmental disorder commonly presenting in young males below 18 years of age and persisting for more than one year with multiple motor and vocal tics [1]. Tics are sudden, rapid, recurrent, and non-rhythmic motor movements or vocalizations commonly preceded by an urge [2]. Most cases of Tourette syndrome show significant improvement or resolve entirely by adulthood [3]. Patients whose tics persist into adulthood suffer from higher anxiety, low self-esteem, socioeconomic status, and poor quality of life [4]. Tourette syndrome is frequently associated with other common childhood disorders such as attention deficit hyperactivity disorder (ADHD) (60-80%), obsessive compulsive disorder (OCD) (11-80%), anxiety, depression (13-76%), migraine (25%) and self-injurious behaviour [5,6].According to the American Academy of Neurology’s practice guidelines, Tourette syndrome can be managed with behavioural, pharmacological, and surgical modalities [7]. Behavioural therapy includes exposure and response prevention therapy (ERP), habit reversal therapy (HRT), and comprehensive behavioural intervention for tics (CBiT), which is considered the safest and first line of treatment [4,7].CBiT is typically a behavioural intervention that includes psycho-education, HRT, functional analysis, and relaxation training and improves the patient’s recognition of the initial urge by providing a competing response or motor movement incompatible with the corresponding tic [8,9].

A document by Adam Kisling. Click on the document to view its contents.

Timing and magnitude of potassium supply determines the location of potassium deficiency symptoms

Ubiquitin proteasome system (UPS) is the major avenues approach of protein degradation, which is responsible for 80% protein degradation in eukaryotic cells. Recently, UPS is involved in a variety of disease processes and plays a significant role in DNA repair, transcription regulation, autophagy and protein transport. Pulmonary arterial hypertension (PAH) is a disease mainly caused by pulmonary artery endothelial cell (PAEC) dysfunction and pulmonary artery smooth muscle cell (PASMC) excessive proliferation and abnormal apoptosis. These increased pulmonary vascular resistance, vascular remodeling, and finally leading to the failure of right heart. The alteration of pulmonary artery protein ubiquitination occurs at the initial stage of PAH and participates in several cell pathways, such as vasoconstriction, tissue remodeling/angiogenesis, cell migration and calcium signaling. In this review, we mainly introduce the functional changes of UPS in PAH, especially specific E3 ubiquitin ligases with related endoplasmic reticulum stress (ERS), proteolysis-targeting chimeras (PROTACs) and proteasome inhibitors mediated degradation mechanism, providing new ideas for the precise diagnosis and treatment of PAH.

Background: The purpose of this article is armed to provide some experience and insight for the clinical treatment of primary mediastinal yolk sac tumor (PMYST) basing on our case report and relevant literature review. Case report and literature review: A 15-year-old boy was diagnosed as PMYST with the volume about 13*12*8cm. The

Postpartum anestrus (PPA) condition or long PPA interval (PPAI) (>90 days) is a reproductive problem in buffaloes. Both genetic and non-genetic factors contribute to the variation in PPAI. Identifying the genetic markers associated with PPA will help in the marker-based selection of buffaloes against PPA, thereby PPA incidence can be reduced. However, such genetic markers associated with PPA are scanty. Therefore, the present study was targeted to identify the association of SNPs in the gonadotropin inhibitory hormone (GnIH/NPVF) gene with PPAI in Indian Murrah buffaloes. GnIH/NPVF is a neuropeptide that inhibits gonadotropin-releasing hormone (GnRH) and gonadotropin secretion. Sequencing of the GnIH/NPVF gene amplified from a pooled DNA sample of 10 PPA and 10 healthy postpartum cyclic controls revealed 8 SNPs in the putative promoter and 5’-UTR regions. Transcription factor binding analysis identified that the allele A of the SNP (c.-1001A>G) at the 5’UTR region could promote the binding of FoxO_CS transcription factor, an inhibitor of gonadotropin release. Association analysis between the genotypes of this SNP and PPAI of 66 extreme PPA buffaloes and 83 extreme controls (PPA< 90 days) identified its significant (P<0.0093) association with PPAI in this selected buffalo population sample. Particularly, the G-allele of this SNP appeared to reduce 30.33±11.51 PPAI days in Murrah buffaloes. In conclusion, the SNP c.-1001A>G in the GnIH/NPVF gene could be a potential genetic marker associated with PPA in Murrah buffaloes, and this association needs further validation in large population samples before its consideration for marker-assisted selection programs against PPA in buffaloes.

Afforestation is the primary ecosystem measure to address the issue of ecosystem degradation in in the Horqin sandy region of northern China. However , It is yet unclear how afforestation may affect the recovery of sandy grassland. This study took the ecological stoichiometry as indicators, and conducted a field investigation and indoor analysis to assess the afforestation strategies of three indigenous tree species for the restoration of sandy grassland , three restoration strategies were: (1) grasslands were enclosed via a Populus × beijingensis shelterbelt (FG); (2) Pinussylvestris var. mongolica was used for the afforestation of small, well-distributed grassland patches (MG); (3) Ulmus pumila was used for the afforestation of small, well-distributed patches (UG). Our result showed that the C, N, and P contents as well as the C: N: P ratio in plants, litters, and soils varied significantly between FG, MG, and UG. All three treatments were found to significantly impact the soil ratios of C:N, N:P, and C:P relative to CK treatment after more than 20 years of recovery. The results of N : P in different tissues showed that FG , MG and UG vegetation restorations were N-limited. N and P homeostasis was present in trees, especially Ulmus pumila, while the degree of homeostasis was significantly impacted by afforestation species and plant tissues. The N:P results suggested that lower N deficiency stress may have been experienced by three experimental plants. We concluded that UG was better suited to the dry climate in Horqin Sandy Land.

This paper studies the problem of optimal control with state constraints for mean-field type stochastic systems, which is governed by fully coupled forward-backward stochastic differential equations(FBSDE) with Teugels martingales. In this system, the coefficients contain not only the state processes but also its marginal distribution, and the cost function is of mean-field type as well. We use an equivalent backward formulation to deal with the terminal state constraint, and then we obtain a stochastic maximum principle by Ekeland’s variational principle. In addition, we discuss a stochastic LQ control problem with state constraints.