Nanostructured Chitosan Membranes for Filtration

Chitosan is a non-toxic and biodegradable biopolymer derived from naturally occurring chitin. It has excellent metal binding and anti-microbial properties which could be beneficial in air and water filtration applications. Nanofibers have distinctly high surface area to volume ratio. Electrospinning is a process by which nano-sized polymer fibers can be produced using an electrostatically driven jet of polymer solution. The fibers are collected as a non-woven mat and offer a high surface area to volume ratio. Electrospinning of pure chitosan is hindered by its limited solubility in aqueous acids and high molecular weight with high degree of inter and intra chain hydrogen bonding. We have been able to form nanometer sized fibers without bead defects by electrospinning Chitosan blends with different polymers like poly (ethylene oxide) and poly (acrylamide) with up to 95% chitosan in blend fibers. The electrospinning apparatus was modified so at to be able heat solutions during electrospinning which helps in expanding the processing window. Fiber formation is controlled by polymer molecular weight, blend ratios, polymer concentration and spinning solution temperature. Surface chemistry of these blend fibers was characterized using XPS. XPS data validated that chitosan content on fiber surface was a function of % chitosan in blend, degree of deacetylation of chitosan, and fiber diameter. A theoretical model was developed which predicted the binding properties of chitosan fibers with known fiber diameter, % chitosan in blend and degree of deacetylation. Surface properties of blend fibers showed a strong correlation with the structure and morphology of the fibers and higher chromium binding capacities compared to similar blend ratio chitosan films were observed. A nanofibrous filter media has been fabricated by electrospinning a layer of chitosan nanofibers onto a non-woven spun bonded poly propylene fabric. These coated filter media have been tested for their metal binding and anti-microbial properties and results showed applicability towards effectively filtering heavy metals and bacteria from waste media. The filtration performance of these nanofibrous filter media have been tested against latex polystyrene beads and aerosol particles and filtration efficiencies of these media were a function of pore size, fiber diameter and size of filtrate

Tellipsoid: Exploiting inter-gene correlation for improved detection of differential gene expression

Motivation: Algorithms for differential analysis of microarray data are vital to modern biomedical research. Their accuracy strongly depends on effective treatment of inter-gene correlation. Correlation is ordinarily accounted for in terms of its effect on significance cut-offs. In this paper it is shown that correlation can, in fact, be exploited {to share information across tests}, which, in turn, can increase statistical power. Results: Vastly and demonstrably improved differential analysis approaches are the result of combining identifiability (the fact that in most microarray data sets, a large proportion of genes can be identified a priori as non-differential) with optimization criteria that incorporate correlation. As a special case, we develop a method which builds upon the widely used two-sample t-statistic based approach and uses the Mahalanobis distance as an optimality criterion. Results on the prostate cancer data of Singh et al. (2002) suggest that the proposed method outperforms all published approaches in terms of statistical power. Availability: The proposed algorithm is implemented in MATLAB and in R. The software, called Tellipsoid, and relevant data sets are available at http://www.egr.msu.edu/~desaikeyComment: 19 pages, Submitted to Bioinformatic

Developing a Cement Formulation for Gas Migration Control During Cementing for High-Pressure/High-Temperature Wells

Cementing high-pressure/high-temperature (HP/HT) gas wells is a challenging and expensive job in the oil and gas industry. Gas migration through the cement column has major safety, environmental, and economic concerns. Problems such as weighting material segregation, excessive fluid loss, and shortages of water available for cement hydration can produce high-porosity cement structures that are prone to progressive gas migration. This work aims to increase hydration efficiency, develop sufficient gel strength, reduce fluid loss, and enhance mechanical properties to produce gas-migration-resistant HP/HT cement slurries. This work developed an HP/HT cement slurry with high resistance to gas migration by optimizing a new additive, Maxcrete, which replaces multiple common gas-migration-control additives. The experimental slurry was prepared and evaluated following the API RP 10B-2 procedures. Fluid loss was optimized through various iterations of additive combinations at different concentrations. The cement hydration process was monitored over 24 hours using computed tomography (CT) scans and compressive-strength analysis. The optimized cement slurry with the new additive showed superior enhancement in the main properties that control the gas migration process. A class G cement slurry with 2.5 lb/100 lb by weight of cement (BWOC) of the new additive showed an enhancement in the cement hydration capacity, fluid loss control, and compressive strength compared to a slurry without the additive. These improvements resulted from coating the cement particles with a layer that is capable of attracting more water molecules, which prevented quick free-water separation and provided for better and faster hydration. The suggested mechanism was supported by gas migration evaluation and rheology assessment. The results of these tests showed rapid development of an initially low gel strength that mitigated the initial induction of gas channels in the cement body during the setting time. The CT-scans showed that the cement blocks were more hydrated and, with time, demonstrated a reduction in the cube porosity. This work introduces and evaluates a new additive with the capability to replace multiple additives in cement slurries for better gas-migration control. The suggested chemistry has the potential to work synergistically with fewer additives and deliver superior cement properties for HP/HT wells

Explainable AI Using Knowledge Graphs

During the last decade, traditional data-driven deep learning (DL) has shown remarkable success in essential natural language processing tasks, such as relation extraction. Yet, challenges remain in developing artificial intelligence (AI) methods in real-world cases that require explainability through human interpretable and traceable outcomes. The scarcity of labeled data for downstream supervised tasks and entangled embeddings produced as an outcome of self-supervised pre-training objectives also hinders interpretability and explainability. Additionally, data labeling in multiple unstructured domains, particularly healthcare and education, is computationally expensive as it requires a pool of human expertise. Consider Education Technology, where AI systems fall along a “capability spectrum” depending on how extensively they exploit various resources, such as academic content, granularity in student engagement, academic domain experts, and knowledge bases to identify concepts that would help achieve knowledge mastery for student goals. Likewise, the task of assessing human health using online conversations raises challenges for current statistical DL methods through evolving cultural and context-specific discussions. Hence, developing strategies that merge AI with stratified knowledge to identify concepts that would delineate healthcare conversation patterns and help healthcare professionals decide. Such technological innovations are imperative as they provide consistency and explainability in outcomes. This tutorial discusses the notion of explainability and interpretability through the use of knowledge graphs in (1) Healthcare on the Web, (2) Education Technology. This tutorial will provide details of knowledge-infused learning algorithms and its contribution to explainability for the above two applications that can be applied to any other domain using knowledge graphs

Unusual case of acute coronary syndrome: inferior wall myocardial infarction 19 years young male presented with fever and right ankle cellulites treated with tissue plasminogen activator and its out come

Unusual case of acute coronary syndrome: inferior wall myocardial infarction in 19yrs young male patient presented with fever and right ankle cellulites with fungal infection, thrombolysis was done with injection tenectaplase a newer tissue plasminogen activator with Troponin-T positive. Tenectaplase drug showed ECG changes within 30 minutes of thrombolysis with normal coronary during the angiography and preserved the left ventricular ejection function making it a successful thrombolysis by the tissue plasminogen activator (TPA) in young patient with myocardial infarction

Excess PLAC8 promotes an unconventional ERK2-dependent EMT in colon cancer

The epithelial-to-mesenchymal transition (EMT) transcriptional program is characterized by repression of E-cadherin (CDH1) and induction of N-cadherin (CDH2), and mesenchymal genes like vimentin (VIM). Placenta-specific 8 (PLAC8) has been implicated in colon cancer; however, how PLAC8 contributes to disease is unknown, and endogenous PLAC8 protein has not been studied. We analyzed zebrafish and human tissues and found that endogenous PLAC8 localizes to the apical domain of differentiated intestinal epithelium. Colon cancer cells with elevated PLAC8 levels exhibited EMT features, including increased expression of VIM and zinc finger E-box binding homeobox 1 (ZEB1), aberrant cell motility, and increased invasiveness. In contrast to classical EMT, PLAC8 overexpression reduced cell surface CDH1 and upregulated P-cadherin (CDH3) without affecting CDH2 expression. PLAC8-induced EMT was linked to increased phosphorylated ERK2 (p-ERK2), and ERK2 knockdown restored cell surface CDH1 and suppressed CDH3, VIM, and ZEB1 upregulation. In vitro, PLAC8 directly bound and inactivated the ERK2 phosphatase DUSP6, thereby increasing p-ERK2. In a murine xenograft model, knockdown of endogenous PLAC8 in colon cancer cells resulted in smaller tumors, reduced local invasion, and decreased p-ERK2. Using MultiOmyx, a multiplex immunofluorescence-based methodology, we observed coexpression of cytosolic PLAC8, CDH3, and VIM at the leading edge of a human colorectal tumor, supporting a role for PLAC8 in cancer invasion in vivo

Dissecting Inflammatory Complications in Critically Injured Patients by Within-Patient Gene Expression Changes: A Longitudinal Clinical Genomics Study

By studying gene expression changes over time in a cohort of trauma patients, Keyur Desai and colleagues identify genes and pathways strongly associated with longer-term complications, which could lead to improved outcome prediction in the first 80 hours after injury

Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [18F]-Flutemetamol PET Scan Result

Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) A\u3b2 and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/A\u3b242 (n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures (n = 100), MCI participants enrolled in the GE067-005 study with [18F]-Flutemetamol PET amyloid measures (n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF A\u3b242 measurements (n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/A\u3b242 (P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen \u3b2 chain confirmed by immunoassay (P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid (P < 0.05) replicating the association with CSF Tau/A\u3b242. There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF A\u3b242 (P 48 0.05), while both A1AT and clusterin were nominally significantly associated with CSF A\u3b242 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important