Pharmacogenomics Cascade Testing (PhaCT): A Novel Approach for Preemptive Pharmacogenomics Testing to Optimize Medication Therapy

The implementation of pharmacogenomics (PGx) has come a long way since the dawn of utilizing pharmacogenomic data in clinical patient care. However, the potential benefits of sharing PGx results have yet to be explored. In this paper, we explore the willingness of patients to share PGx results, as well as the inclusion of family medication history in identifying potential family members for pharmacogenomics cascade testing (PhaCT). The genetic similarities in families allow for identifying potential gene variants prior to official preemptive testing. Once a candidate patient is determined, PhaCT can be initiated. PhaCT recognizes that further cascade testing throughout a family can serve to improve precision medicine. In order to make PhaCT feasible, we propose a novel shareable HIPAA-compliant informatics platform that will enable patients to manage not only their own test results and medications but also those of their family members. The informatics platform will be an external genomics system with capabilities to integrate with patients’ electronic health records. Patients will be given the tools to provide information to and work with clinicians in identifying family members for PhaCT through this platform. Offering patients the tools to share PGx results with their family members for preemptive testing could be the key to empowering patients. Clinicians can utilize PhaCT to potentially improve medication adherence, which may consequently help to distribute the burden of health management between patients, family members, providers, and payers

Nanoengineered drug-releasing Ti wires as an alternative for local delivery of chemotherapeutics in the brain

The blood–brain barrier (BBB) blocks the passage of active molecules from the blood which makes drug delivery to the brain a challenging problem. Oral drug delivery using chemically modified drugs to enhance their transport properties or remove the blocking of drug transport across the BBB is explored as a common approach to address these problems, but with limited success. Local delivery of drugs directly to the brain interstitium using implants such as polymeric wafers, gels, and catheters has been recognized as a promising alternative particularly for the treatment of brain cancer (glioma) and neurodegenerative disorders. The aim of this study was to introduce a new solution by engineering a drug-releasing implant for local drug delivery in the brain, based on titanium (Ti) wires with titania nanotube (TNT) arrays on their surfaces. Drug loading and drug release characteristics of this system were explored using two drugs commonly used in oral brain therapy: dopamine (DOPA), a neurotransmitter agent; and doxorubicin (DOXO), an anticancer drug. Results showed that TNT/Ti wires could provide a considerable amount of drugs (>170 μg to 1000 μg) with desirable release kinetics and controllable release time (1 to several weeks) and proved their feasibility for use as drug-releasing implants for local drug delivery in the brain

KEANEKARAGAMAN TERIPANG (Holothuroidae) DI ZONA INTERTIDAL PADA AREA KONSERVASI “SASI” KAMPUNG FOLLEY DISTRIK MISOOL TIMUR KABUPATEN RAJA AMPAT - PAPUA BARAT

Sasi adalah kearifan lokal dari masyarakat di Papua untuk menjaga kelestarian sumberdaya termasuk biota perairan.  Penelitian ini bertujuan untuk mengkaji keanekaragaman teripang (Holothuroidae) di perairan Kampung Folley Distrik Misool Timur kabupaten Raja Ampat. Lokasi penelitian yang terdiri dari 2 lokasi konservasi sasi teripang yaitu perairan Tanjung Vageta dan Tanjung Waponta, serta 1 lokasi di luar area konservasi yaitu Perairan Dermaga Kampung Folley. Pengambilan data pada bulan Juni-Juli 2019 dilakukan menggunakan kuadran 5x5m2 diletakkan zigzag dengan transek garis 100m sejajar garis pantai.  Terdapat 7 spesies teripang di lokasi konservasi sasi yakni Holothuria scabra1, H. scabra2, H. atra, H. leucuspilota, H. impatiens,  Stichopus hermanii, Synaptidae. H. scabra adalah yang terbanyak di area konservasi sasi dan merupakan komoditas penting bagi masyarakat lokal

Drug-eluting Ti wires with titania nanotube arrays for bone fixation and reduced bone infection

Current bone fixation technology which uses stainless steel wires known as Kirschner wires for fracture fixing often causes infection and reduced skeletal load resulting in implant failure. Creating new wires with drug-eluting properties to locally deliver drugs is an appealing approach to address some of these problems. This study presents the use of titanium [Ti] wires with titania nanotube [TNT] arrays formed with a drug delivery capability to design alternative bone fixation tools for orthopaedic applications. A titania layer with an array of nanotube structures was synthesised on the surface of a Ti wire by electrochemical anodisation and loaded with antibiotic (gentamicin) used as a model of bone anti-bacterial drug. Successful fabrication of TNT structures with pore diameters of approximately 170 nm and length of 70 μm is demonstrated for the first time in the form of wires. The drug release characteristics of TNT-Ti wires were evaluated, showing a two-phase release, with a burst release (37%) and a slow release with zero-order kinetics over 11 days. These results confirmed our system's ability to be applied as a drug-eluting tool for orthopaedic applications. The established biocompatibility of TNT structures, closer modulus of elasticity to natural bones and possible inclusion of desired drugs, proteins or growth factors make this system a promising alternative to replace conventional bone implants to prevent bone infection and to be used for targeted treatment of bone cancer, osteomyelitis and other orthopaedic diseases

Operationalizing Healthcare Big Data in the Electronic Health Records using a Heatmap Visualization Technique

Background: The majority of the electronic health record (EHR) contains a wealth of information, including unstructured notes. Healthcare professionals may be missing substantial portions of essential diagnostic and treatment information by not focusing on unstructured texts. The objective of this study is to present progress notes data using heatmap visualization. Methods: In this study, the research team used the unstructured text from the progress notes of deidentified patient data. The research team conducted qualitative content-coding based on the clinical complexity model and developed a heatmap based on the processed frequency data. Result: The researchers developed a color-coded heatmap focusing on the severity and acuity of patients’ status accumulated through multiple previous patient’s visits. Conclusions: Future research into creating an automated process to generate the heatmap from an unstructured dataset can open up opportunities to operationalize big data in healthcare

Real quadratic fields admitting universal lattices of rank7

In this paper, we will prove that if $d$ is sufficiently large square-free positive rational integer, then there is no integral septenary universal quadratic lattice over $\mathcal{O}_F$ where $F=\mathbb Q(\sqrt{d})$

Isolasi dan skrining Bakteri Endofit dari Tanaman Endemik Papua Labu Koteka Langenaria siceraria (Molina) Standl sebagai agen Antijamur terhadap Candida albicans

Labu Koteka Langenaria siceraria (Molina) Standl adalah tanaman endemik Papua yang digunakan pada masyarakat suku Dani sebagai pakaian tradisional kaum pria. Selain itu, labu koteka dimanfaatkan sebagai bahan pengobatan demam tipoid. Bakteri endofit merupakan bakteri yang hidup pada jaringan tumbuhan tanpa menyebabkan penyakit dan mengandung senyawa metabolit sekunder yang sama dengan tanaman inangnya. Tujuan dari penelitian ini yaitu untuk memperoleh isolat bakteri endofit yang berpotensial sebagai antijamur terhadap Candida albicans dan mengetahui komponen senyawa metabolit sekunder. Tahapan dari penelitian terdiri atas eksplorasi bakteri endofit dari labu koteka, skrining isolat bakteri endofit, fermentasi bakteri endofit dengan menggunakan molase sebagai sumber karbon dengan konsentrasi 1%, 5%, dan 10%, uji aktivitas antijamur terhadap C. albicans secara difusi cakram, dan identifikasi senyawa metabolit sekunder dari bakteri potensial. Berdasarkan hasil penelitian diperoleh dua isolat bakteri endofit yang berpotensial sebagai antijamur yaitu isolat bakteri-1 dan isolat bakteri-4 dengan diameter zona hambat rata-rata 14 mm dan 12,89 mm. Komponen senyawa metabolit sekunder pada isolat bakteri-1 yaitu alkaloid, saponin, dan antraquinon. Sedangkan isolat bakteri-4 mengandung alkaloid, terpenoid dan antraquinon

Single-cell Transcriptomics of Murine Mural Cells Reveals Cellular Heterogeneity

Mural cells (MCs) wrap around the endothelium, and participate in the development and homeostasis of vasculature. MCs have been reported as heterogeneous population morphologically and functionally. However, the transcriptional heterogeneity of MCs was rarely studied. In this study, we illustrated the transcriptional heterogeneity of MCs with different perspectives by using publicly available single-cell dataset GSE109774. Specifically, MCs are transcriptionally different from other cell types, and ligand-receptor interactions of different cells with MCs vary. Re-clustering of MCs identified five distinct subclusters. The heterogeneity of MCs in tissues was reflected by MC coverage, various distribution of MC subclusters, and ligand-receptor interactions of MCs and parenchymal cells. The transcriptomic diversity of MCs revealed in this article will help facilitate further research into MCs

Pharmacogenomic Considerations in Opioid Therapy

Opioids are among the most common medications used in the treatment of pain, and they carry many serious risks if used inappropriately. Pharmacogenomic considerations can impact a patient’s treatment plan for chronic pain, as CYP polymorphisms may interfere with nonsteroidal anti-inflammatory drugs, tricyclic antidepressants, and opioids. In particular, CYP2D6 polymorphisms may play a considerable part in the safety and efficacy of codeine, hydrocodone, and tramadol, as outlined in the Clinical Pharmacogenetic Implementation Consortium (CPIC) guideline on opioids. Based on current research, the CPIC recently updated its guidance on opioid use and interactions with CYP2D6, OPRM1, and COMT polymorphisms. Greater pharmacist understanding of CYP polymorphisms can lead to safer opioid prescribing and better outcomes for patients receiving pain management

Artificial Intelligent Context-Aware Machine-Learning Tool to Detect Adverse Drug Events from Social Media Platforms

Introduction Pharmacovigilance (PV) has proven to detect post-marketing adverse drug events (ADE). Previous research used the natural language processing (NLP) tool to extract unstructured texts relevant to ADEs. However, texts without context reduce the efficiency of such algorithms. Our objective was to develop and validate an innovative NLP tool, aTarantula, using a context-aware machine-learning algorithm to detect existing ADEs from social media using an aggregated lexicon. Method aTarantula utilized FastText embeddings and an aggregated lexicon to extract contextual data from three patient forums (i.e., MedHelp, MedsChat, and PatientInfo) taking warfarin. The lexicon used warfarin package inserts and synonyms of warfarin ADEs from UMLS and FAERS databases. Data was stored on SQLite and then refined and manually checked by three clinical pharmacists for validation. Results Multiple organ systems where the most frequent ADE were reported at 1.50%, followed by CNS side effects at 1.19%. Lymphatic system ADEs were the least common side effect reported at 0.09%. The overall Spearman rank correlation coefficient between patient-reported data from the forums and FAERS was 0.19. As determined by pharmacist validation, aTarantula had a sensitivity of 84.2% and a specificity of 98%. Three clinical pharmacists manually validated our results. Finally, we created an aggregated lexicon for mining ADEs from social media. Conclusion We successfully developed aTarantula, a machine-learning algorithmn based on artificial intelligence to extract warfarin-related ADEs from online social discussion forums automatically. Our study shows that it is feasible to use aTarantula to detect ADEs. Future researchers can validate aTarantula on the diverse dataset