Preservice teachers’ digital literacy in educator preparation programs : a literature review

As technology’s potential to transform teaching and learning became clear, shared standards and expectations emerged for teachers to integrate in K-12 classrooms. However, despite the massive influx of classroom technology, there were few noticeable changes to the pedagogical development or curricular sequences. The purpose of this report is to provide a review of literature that explores how preservice teachers learn to conceptualize their own digital literacy during their teacher preparation. More specifically, this review investigates preservice teachers’ learning about digital literacy conceptions in relation to how their learning experiences are embedded in and situated as part of learning activities and teaching practices with technology in teacher education coursework. The results of the literature review provide insight as to what learning opportunities teacher educators can provide when preservice teachers need to be prepared to understand and practice with technology for specific purposes and contexts in classrooms.Curriculum and Instructio

Investigation of Antimony in Natural Water and Leaching from Polyethylene Terephthalate (PET) Bottled Water

Abstract -Antimony (Sb) is one of the trace hazardous compounds in drinking water. Recent studies demonstrated that polyethylene terephthalate (PET) bottles can release antimony into water. It is also found on natural environment such as groundwater and crustal rocks. The natural content of Sb in northern Gyeonggi province in South Korea was very low range from 0.02~0.32 μg/L. The source water and tap water for 15 water supply plants from river or reservoir showed 0.13 μg/L on average. The groundwater concentration from 50 mineral springs indicated significantly low at 0.02 μg/L. The concentration of antimony was investigated in 47 bottled water brands on market. The average of Sb in bottled water brands was 0.57 μg/L. The detection rate was 100% in these products. Otherwise, raw water for bottled water contained 0.32 μg/L of antimony and detection rate was 90.7%. As a results of leaching experiment, antimony content in PET bottled water was increased from 1.04 to 9.84 μg/L under 60℃ after 12weeks. In case, the bottled water was stored in over 35℃, antimony leached into water. UV-ray irradiation to bottled water not induced increasing antimony release into water following 14days

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Digital PCR Discriminates between SARS-CoV-2 Omicron Variants and Immune Escape Mutations

ABSTRACT As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve, mutations arise that will allow the virus to evade immune defenses and therapeutics. Assays that can identify these mutations can be used to guide personalized patient treatment plans. Digital PCR (dPCR) is a fast and reliable complement to whole-genome sequencing that can be used to discriminate single nucleotide polymorphisms (SNPs) in template molecules. Here, we developed a panel of SARS-CoV-2 dPCR assays and demonstrate its applications for typing variant lineages and therapeutic monoclonal antibody resistance. We first designed multiplexed dPCR assays for SNPs located at residue 3395 in the orf1ab gene that differentiate the Delta, Omicron BA.1, and Omicron BA.2 lineages. We demonstrate their effectiveness on 596 clinical saliva specimens that were sequence verified using Illumina whole-genome sequencing. Next, we developed dPCR assays for spike mutations R346T, K444T, N460K, F486V, and F486S, which are associated with host immune evasion and reduced therapeutic monoclonal antibody efficacy. We demonstrate that these assays can be run individually or multiplexed to detect the presence of up to 4 SNPs in a single assay. We perform these dPCR assays on 81 clinical saliva SARS-CoV-2-positive specimens and properly identify mutations in Omicron subvariants BA.2.75.2, BM.1.1, BN.1, BF.7, BQ.1, BQ.1.1, and XBB. Thus, dPCR could serve as a useful tool to determine if clinical specimens contain therapeutically relevant mutations and inform patient treatment. IMPORTANCE Spike mutations in the SARS-CoV-2 genome confer resistance to therapeutic monoclonal antibodies. Authorization for treatment options is typically guided by general trends of variant prevalence. For example, bebtelovimab is no longer authorized for emergency use in the United States due to the increased prevalence of antibody-resistant BQ.1, BQ.1.1, and XBB Omicron subvariants. However, this blanket approach limits access to life-saving treatment options to patients who are otherwise infected with susceptible variants. Digital PCR assays targeting specific mutations can complement whole-genome sequencing approaches to genotype the virus. In this study, we demonstrate the proof of concept that dPCR can be used to type lineage defining and monoclonal antibody resistance-associated mutations in saliva specimens. These findings show that digital PCR could be used as a personalized diagnostic tool to guide individual patient treatment

Prediction of Pelvic Organ Prolapse Postsurgical Outcome Using Biomaterial-Induced Blood Cytokine Levels: Machine Learning Approach

BackgroundPelvic organ prolapse (POP) refers to symptomatic descent of the vaginal wall. To reduce surgical failure rates, surgical correction can be augmented with the insertion of polypropylene mesh. This benefit is offset by the risk of mesh complication, predominantly mesh exposure through the vaginal wall. If mesh placement is under consideration as part of prolapse repair, patient selection and counseling would benefit from the prediction of mesh exposure; yet, no such reliable preoperative method currently exists. Past studies indicate that inflammation and associated cytokine release is correlated with mesh complication. While some degree of mesh-induced cytokine response accompanies implantation, excessive or persistent cytokine responses may elicit inflammation and implant rejection. ObjectiveHere, we explore the levels of biomaterial-induced blood cytokines from patients who have undergone POP repair surgery to (1) identify correlations among cytokine expression and (2) predict postsurgical mesh exposure through the vaginal wall. MethodsBlood samples from 20 female patients who previously underwent surgical intervention with transvaginal placement of polypropylene mesh to correct POP were collected for the study. These included 10 who experienced postsurgical mesh exposure through the vaginal wall and 10 who did not. Blood samples incubated with inflammatory agent lipopolysaccharide, with sterile polypropylene mesh, or alone were analyzed for plasma levels of 13 proinflammatory and anti-inflammatory cytokines using multiplex assay. Data were analyzed by principal component analysis (PCA) to uncover associations among cytokines and identify cytokine patterns that correlate with postsurgical mesh exposure through the vaginal wall. Supervised machine learning models were created to predict the presence or absence of mesh exposure and probe the number of cytokine measurements required for effective predictions. ResultsPCA revealed that proinflammatory cytokines interferon gamma, interleukin 12p70, and interleukin 2 are the largest contributors to the variance explained in PC 1, while anti-inflammatory cytokines interleukins 10, 4, and 6 are the largest contributors to the variance explained in PC 2. Additionally, PCA distinguished cytokine correlations that implicate prospective therapies to improve postsurgical outcomes. Among machine learning models trained with all 13 cytokines, the artificial neural network, the highest performing model, predicted POP surgical outcomes with 83% (15/18) accuracy; the same model predicted POP surgical outcomes with 78% (14/18) accuracy when trained with just 7 cytokines, demonstrating retention of predictive capability using a smaller cytokine group. ConclusionsThis preliminary study, incorporating a sample size of just 20 participants, identified correlations among cytokines and demonstrated the potential of this novel approach to predict mesh exposure through the vaginal wall following transvaginal POP repair surgery. Further study with a larger sample size will be pursued to confirm these results. If corroborated, this method could provide a personalized medicine approach to assist surgeons in their recommendation of POP repair surgeries with minimal potential for adverse outcomes

Electrochemical Generation of Mesopores and Residual Oxygen for the Enhanced Activity of Silver Electrocatalysts

The development of stable and efficient electrocatalysts is of key importance for the establishment of a sustainable society. The activity of a metal electrocatalyst is determined by its electrochemically active surface area and intrinsic activity, which can be increased using highly porous structures and heteroatomic doping, respectively. Herein, we propose a general strategy of generating mesopores and residual oxygen in metal electrocatalysts by reduction of metastable metal oxides using Ag2O3 electrodeposited onto carbon paper as a model system and demonstrating that the obtained multipurpose porous Ag electrocatalyst has high activity for the electroreduction of O-2 and CO2. The presence of mesopores and residual oxygen is confirmed by electrochemical and spectroscopic techniques, and quantum mechanical simulations prove the importance of residual oxygen for electrocatalytic activity enhancement. Thus, the adopted strategy is concluded to allow the synthesis of highly active metal catalysts with controlled mesoporosity and residual oxygen content