ABSTRACT
Qualitative methods are used to capture stakeholder perspectives within learning healthcare systems (LHS), but there is a need to specify methods that balance rigour and pragmatic approaches to inform quality improvement (QI). Utilizing examples from two QI projects within the OTNY LHS, we illustrate methods and strategies that build team capacity and flexibility to respond to an evolving LHS. Method(s): Qualitative methods were tailored to fit each project's timelines and goals, to inform both practice and research. Tools to facilitate rapid cycle feedback included interview/focus group summary templates, aggregate summaries that synthesize findings by stakeholder group, case matrix templates for rapid extraction and systematic categorization of data along topic areas, and dissemination materials adapted for stakeholder audience and project phases. Strategies to maintain rigour included processes for data reduction and interpretation, a multi-disciplinary approach for analysis, frequent consensus-based meetings, data triangulation, and member checks. Result(s): Rapid cycle approaches yielded interim results that reshaped research questions or identified critical gaps. Case summary analysis exploring the impact of COVID-19 revealed limited information on telehealth challenges amongst OTNY participants, necessitating a shift in recruitment and interview focus. For another project, analytic methods were sequenced to rapidly inventory suggestions from interview summaries on how to enhance OTNY practice to better address racism, while subsequent thematic analysis of transcripts captured participants' experiences of racism for context. Challenges included concurrent alignment of data collection and analysis, tailoring summary templates to maximize utility for rapid analysis, and maintaining flexibility to respond to evolving findings and LHS stakeholder input. Conclusion(s): The diverse methods and strategies illustrated by these projects offer guidance for balancing.
ABSTRACT
Genotypic definition of monogenic inborn errors of immunity (IEIs) continues to accelerate with broader access to next generation sequencing, underscoring this aggregated group of disorders as a major health burden impacting both civilian and military populations. At an estimated prevalence of 1 in 1200 individuals, IEIs affect ~8,000 patients within the Military Health System (MHS). Despite access to targeted gene/exome panels at military treatment facilities, most affected patients never receive a definitive genetic diagnosis that would significantly improve clinical care. To address this gap, we established the first registry of IEI patients within the MHS with the goal of identifying known and novel pathogenic genetic defects to increase diagnosis rates and enhance clinical care. Using the registry, a research protocol was opened in July 2022. Since July we have enrolled 75 IEI patients encompassing a breadth of phenotypes including severe and recurrent infections, bone marrow failure, autoimmunity/autoinflammation, atopic disease, and malignancy. Enrolled patients provide blood and bone marrow samples for whole genome, ultra-deep targeted panel and comprehensive transcriptome sequencing, plus cryopreservation of peripheral blood mononuclear cells for future functional studies. We are also implementing and developing analytical methods for identifying and interrogating non-coding and structural variants. Suspected pathogenic variants are adjudicated by a clinical molecular geneticist using state-of-the-art analysis pipelines. These analyses subsequently inform in vitro experiments to validate causative mutations using cell reporter systems and primary patient cells. Clinical variant validation and return of genetic results are planned with genetic counseling provided. As a proof of principle, this integrated genetic evaluation pipeline revealed a novel, candidate TLR7 nonsense variant in two adolescent brothers who both endured critical COVID-19 pneumonia, requiring mechanical ventilation and extracorporeal membrane oxygenation. Our protocol is therefore poised to greatly enrich clinical genetics resources available in the MHS for IEI patients, contributing to better diagnosis rates, informed family counseling, and targeted treatments that collectively improve the health and readiness of the military community. Moreover, our efforts should yield new mechanistic insights on immune pathogenesis for a broad variety of known and novel IEIs.Copyright © 2023 Elsevier Inc.
ABSTRACT
Recent advancements in nanotechnology have resulted in improved medicine delivery to the target site. Nanosponges are three-dimensional drug delivery systems that are nanoscale in size and created by cross-linking polymers. The introduction of Nanosponges has been a significant step toward overcoming issues such as drug toxicity, low bioavailability, and predictable medication release. Using a new way of nanotechnology, nanosponges, which are porous with small sponges (below one microm) flowing throughout the body, have demonstrated excellent results in delivering drugs. As a result, they reach the target place, attach to the skin's surface, and slowly release the medicine. Nanosponges can be used to encapsulate a wide range of medicines, including both hydrophilic and lipophilic pharmaceuticals. The medication delivery method using nanosponges is one of the most promising fields in pharmacy. It can be used as a biocatalyst carrier for vaccines, antibodies, enzymes, and proteins to be released. The existing study enlightens on the preparation method, evaluation, and prospective application in a medication delivery system and also focuses on patents filed in the field of nanosponges.Copyright © 2023 The Authors.
ABSTRACT
In order to comprehensively understand the research hotspots and development trends of Lonicera Japonica Flos in the past 20 years, and to provide intuitive data reference and objective opinions and suggestions for subsequent related research in this field, this study collected 8 871 Chinese literature and 311 English literature related to Lonicera Japonica Flos research in the core collection databases of Wanfang Data), CNKI and Web of Science (WOS) from 2002 to 2021, and conducted bibliometric and visual analysis using vosviewer. The results showed that the research on the active components of Lonicera Japonica Flos based on phenolic acid components, the research on the mechanism of novel coronavirus pneumonia based on data mining and molecular docking technology, and the pharmacological research on the anti-inflammatory and antiviral properties of Lonicera Japonica Flos are the three hot research directions in the may become the future research direction. In this paper, we analyze the research on Lonicera Japonica Flos from five aspects: active ingredients, research methods, formulation and preparation, pharmacological effects and clinical applications, aiming to reveal the research hotspots, frontiers and development trends in this field and provide predictions and references for future research.Copyright © Drug Evaluation Research 2022.
ABSTRACT
The COVID19 pandemic accelerated opportunities for innovation within the decentralization process of clinical trials with opportunities for implementation of patient-centric workflows for efficiency and cost-reduction. Decentralized sample collection, particularly whole blood using dried blood spots (DBS) provides the ideal mechanism for patient driven sample collection with ease of access to sample generation, drug level assessments and metabolomic prMegofiling, providing longitudinal real-time measure of drug specific pharmacodynamic readout for safety and efficacy. In this study, we report the development of a protocol for the capture and comprehensive profiling of metabolomics using dried blood spots from a cohort of 49 healthy volunteer donors. Using liquid chromatography combined with mass spectrometric (UPLC-MS/MS) methods an untargeted metabolomic approach resulted in the identification of >800 biochemicals of which a significant subset was found to be presented in corresponding matched plasma (from whole blood) samples. The biochemicals identified from the DBS samples included metabolites that were part of the lipid, amino acid, nucleotide, peptide, cofactors, carbohydrate and energy super pathways. A significant number of metabolites identified in the DBS samples were xenobiotics including those representing the biotransformation products of drugs. The overall metabolite profiles were analyzed for precision and accuracy of measure, variability in performance and dynamic range to establish benchmarks for evaluation. An additional cohort with a longitudinal sampling as part of the protocol provided the reproducibility of the analytic method for inter-day variability of metabolite performance over time. Although metabolomic profiles varied between individuals from a population perspective, there was minimal variation observed within individuals when samples were profiled longitudinally over several weeks. Thus, the protocols for DBS collection and the corresponding capture of a large set of metabolites with reproducible performance provides an opportunity for its implementation in oncological clinical trials as part of a de-centralized clinical trial solution.
ABSTRACT
Introduction: Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States (US) and disproportionately impacts Black individuals. The US Preventive Services Taskforce began recommending CRC screening for individuals aged 45-49 in 2021, however effective strategies to increase screening participation in Black individuals in this age group are unknown. Thus, the National Colorectal RoundTable (NCCRT) used a mixed methods approach to identify barriers and facilitators to CRC screening in Black individuals, with specific focus on those age 45-49. Results informed the development of the 2022 NCCRT Messaging Guidebook for Black & African American People. Method(s): We conducted a mixed-methods study in a large, nationally representative sample of unscreened Black individuals. We first conducted semi-structured qualitative interviews with Black individuals over age 45, recruited from the Schlesinger Group qualitative research platform. Findings informed content for a subsequent survey to understand barriers and facilitators, administered broadly via the Prodege online research platform. Messages to encourage screening participation were developed based on learnings from prior ACS and NCCRT work. Message were tested using MaxDiff analytic methods and reviewed by a multidisciplinary advisory committee for inclusion in the Guidebook. Result(s): There were 10 qualitative interview and 490 survey participants. The average age of participants was 52.7 (s.d.56.1) for interviews and 55.3 (s.d.57.3) for surveys. 40.0% were female and 38.2% lived in the Southeast US (Table). The most frequently reported barrier to screening was procrastination (40.0% in age 45-49;42.8% in age 50-65;34.2% in age .55). Procrastination was often attributed to financial concerns (20.8% in age 45-49) and COVID-19 (27.0% in age 50-54;21.8% in age .55) (Figure). Of those age 45-49, the majority preferred to receive screening information from a health care provider (57.5%), however only 31.7% reported that a provider had initiated a screening conversation. Several messages rated as highly effective in encouraging screening were included in the NCCRT Guidebook. Conclusion(s): We identified several age-specific barriers to CRC screening and developed unique messaging to motivate screening among unscreened Black individuals age 45 and over. Messages that tested positively are publicly available as a resource for organizations and institutions that aim to increase screening rates.
ABSTRACT
Naringin is a flavonoid isolated from different citrus fruits like Grapefruit, Orange, Pomelo, Lemon, etc, which are commonly called local fruit. Naringin is found in the white spongy portion of citrus peel. Its content varies from 0.65 mg/gm in the mandarin peel to 14.40mg/gm in the grapefruit peel. Naringin is metabolized to the flavanone naringenin by the enzyme Naringinase present in the liver. It can be analyzed by using various analytical techniques such as HPLC, TLC, UV, HPTLC, mass spectroscopy, Liquid chromatography, chiral chromatography and LC/Mass spectroscopy. Naringin can act as an antioxidant and scavenge free radicals. Naringin mainly focuses on in-vitro and in-vivo animal studies showing its beneficial effects on cardioprotective, antioxidant, anti-inflammatory, antimicrobial, hypolipemiant, neurological, thermogenic, pulmonary disorders and antidiabetic. Naringin is also treated as a most promising treatment strategy against Covid-19 due to its antiviral and anti-inflammatory effects. Recently, Naringin has proven its activity in various molecular docking studies. Naringin keeps the body healthy against various illnesses and major lifestyle disorders.Copyright All © 2023 are reserved by International Journal of Pharmaceutical Sciences and Research.
ABSTRACT
Low Back Pain (LBP) is a health problem that affects performance in working. Indonesia is a country affected by the COVID-19 pandemic, so a study from the home policy has been issued. This study aimed to determine the association between the factors that affect LBP in Medical Students at the Faculty of Medicine, University of Mataram during the study from home. This study is an observational analytic study design with the cross-sectional approach. The population of this study is Medical Students, Faculty of Medicine, University of Mataram with total sample of 185 people. Collecting data using questionnaires and analyzed using univariate, bivariate, and multivariate analysis. According to univariate analysis, amount of LBP complaints (53 people). Based on bivariate analysis, the p-value of gender factor (0.000);body mass index factor (0.840);social-economy status factor (0.499);sitting position factors (sitting position while studying factor (0.008), sitting location while studying factor (0.046), chair shape while studying factor (0.286), body position while studying factor (0.037), legs position while studying factor (0.339), back support use while studying factor (0.455), table use while studying factor (0.010), elbows position while studying factor (0.627), stretching between study time factor (0.372), duration in each stretch factor (0.389), time range between stretch factor (0.311)), and sitting duration factor (0.011). Based on multivariate analysis, the strength of the association (OR) to LBP are sitting position factor (sitting position while studying factor) (8.232), sitting duration factor (1.956), and gender factor (0.187). The dominant factors to LBP are gender factor, sitting position factor (sitting position while studying factor), and sitting duration factor. The factor that has the strongest association with LBP is sitting position factor (sitting position while studying factor).Copyright Published by Oriental Scientific Publishing Company © 2023.
ABSTRACT
The COVID-19 pandemic has presented a global challenge to the health system. More than 200 years of world epidemiological experience since the first mass use of vaccines have convincingly shown that effective vaccines are the key tools in the fight against dangerous infectious diseases, especially epidemic and pandemic ones. In the context of a rapidly spreading pandemic of a new infectious agent, it is crucial not only to develop fundamentally new vaccines, but also to be able to quickly organise their large-scale production. In the Russian Federation, in 2020, a team of the National Research Centre for Epidemiology and Microbiology named after Honorary Academician N.F. Gamaleya developed an innovative vector vaccine, Gam-COVID-Vac, for the prevention of coronavirus disease caused by the SARS-CoV-2 virus. A number of pharmaceutical companies faced the challenge of producing the vaccine. The aim of the study was to optimise the production technology of Gam-COVID-Vac for scaling and increasing the production capacity. In the course of the work, the authors established critical quality attributes of the product, optimised analytical methods for their control, identified poorly scalable technological stages, streamlined the technological process before its transfer to production, and modified non-scalable and technologically unfeasible stages. The work resulted in the launch of industrial-scale production of active pharmaceutical ingredients for both components of Gam-COVID-Vac, which made it possible not only to meet the critical need for COVID-19 immunoprophylaxis in the Russian Federation, but also to supply this vaccine to a number of foreign countries.Copyright © 2023 Safety and Risk of Pharmacotherapy. All rights reserved.
ABSTRACT
To treat mild to moderate COVID-19, an investigational drug called nirmatrelvir in combination with ritonavir is being researched for which the potential hazards with this are still unknown. Nirmatrelvir has been approved for immediate use by the US Food and drug intake in conjunction with the drug ritonavir for the treatment of mild to medium COVID-19 in grown ups and individuals of more than 12 years who test positive for the virus and are at a high risk to develop severe COVID-19.To quantify the drugs simultaneously in tablet dosage forms, a novel, sensitive and reproducible reverse phase liquid chromatography method has been developed. Thechromatographic separation was performed using Phenomenex (250x4.6mm,5micro particle size) column. The separation and elution were carried out at an ambient temperature using a mobile phase consisting of 0.1% trifluoro acetic acid &acetonitrile in the ratio of 50:50%v/v. The maximum absorbance by UV spectrophotometer shown at wavelength 258.3nm& 271.4nm for nirmatrelvir and ritonavir. Also, 266nm was selected as detector wavelength by a photodiode array detector for the HPLC chromatrographic method.Beer lambert's law obeyed in the linear range of 37.5-225microg/mL(R2=0.9998) for nirmatrelvir and 25-150 microg/mL(R2=0.9994) for ritonavir. The method shows method and system precision with % RSD less than 1%.The percentage mean recovery was found to be 99.9-100.2%& 100.0-100.2%. The LOD 1.5 microg/mL &1 microg/mL values indicates the method sensitivity. The proposed stability indicating method was validated for precision,accuracy, specificity, selectivity, robustness and stability studies according to ICH guidelines.Copyright © 2022, Anka Publishers. All rights reserved.
ABSTRACT
Organ-on-a-chip is a three-dimensional microfluidic system that simulates the cellular structure and biological milieu of an organ, that seemed to be constructed and studied substantially in the last decade. Microchips can be configured to suit disease states in a variety of organs, including the lung. When contrasted to traditional in vitro models like monolayer cell lineages, lung-on-a-chip models lays out a pragmatic portrayal of disease pathophysiology and pharmaceuticals' mode of action, and this is especially more prevailing in connection with the COVID-19 pandemic. Animal models have typically been used in pharmaceutical drug screening to assess pharmacological and toxicological reactions to a new entity. These adaptations, on the other hand, do not precisely represent biological reactions in humans. Present and prospective uses of the lung-on-a-chip model in the pulmonary system are highlighted in this overview. In addition, the constraints of existing in vitro systems for respiratory disease simulation and therapeutic discovery would be emphasized. Attributes of lung-on-a-chip transformative features in biomedical applications will be addressed to illustrate the relevance of this lung-on-chip model for medical science.Copyright © 2022
ABSTRACT
A fast procedure obtained by the combination of fabric phase extraction (FPSE) with high performance liquid chromatography (HPLC) has been developed and validated for the quantification of favipiravir (FVP) in human plasma and breast milk. A sol-gel polycaprolactone-block-polydimethylsiloxane-block-polycaprolactone (sol-gel PCAP-PDMS-PCAP) coated on 100% cellose cotton fabric was selected as the most efficient membrane for FPSE in human plasma and breast milk samples. HPLC-UV analysis were performed using a RP C18 column under isocratic conditions. Under these optimezed settings, the overall chromatographic analysis time was limited to only 5 min without encountering any observable matrix interferences. Following the method validation procedure, the herein assay shows a linear calibration curve over the range of 0.2–50 µg/mL and 0.5–25 µg/mL for plasma and breast milk, respectively. The method sensitivities in terms of limit of detection (LOD) and limit of quantification (LOQ), validated in both the matrices, have been found to be 0.06 and 0.2 µg/mL for plasma and 0.15 and 0.5 µg/mL for milk, respectively. Intraday and interday precision and trueness, accordingly to the International Guidelines, were validated and were below 3.61% for both the matrices. The herein method was further tested on real samples in order to highlight the applicability and the advantage for therapeutic drug monitoring (TDM) applications. To the best of our knowledge, this is the first validated FPSE-HPLC-UV method in human plasma and breast milk for TDM purposes applied on real samples. The validated method provides fast, simple, cost reduced, and sensitive assay for the direct quantification of favipiravir in real biological matrices, also appliyng a well-known rugged and cheap instrument configuration. © 2022 Elsevier B.V.
ABSTRACT
The COVID-19 pandemic has presented a global challenge to the health system. More than 200 years of world epidemiological experience since the first mass use of vaccines have convincingly shown that effective vaccines are the key tools in the fight against dangerous infectious diseases, especially epidemic and pandemic ones. In the context of a rapidly spreading pandemic of a new infectious agent, it is crucial not only to develop fundamentally new vaccines, but also to be able to quickly organise their large-scale production. In the Russian Federation, in 2020, a team of the National Research Centre for Epidemiology and Microbiology named after Honorary Academician N.F. Gamaleya developed an innovative vector vaccine, Gam-COVID-Vaс, for the prevention of coronavirus disease caused by the SARS-CoV-2 virus. A number of pharmaceutical companies faced the challenge of producing the vaccine. The aim of the study was to optimise the production technology of Gam-COVID-Vac for scaling and increasing the production capacity. In the course of the work, the authors established critical quality attributes of the product, optimised analytical methods for their control, identified poorly scalable technological stages, streamlined the technological process before its transfer to production, and modified non-scalable and technologically unfeasible stages. The work resulted in the launch of industrial-scale production of active pharmaceutical ingredients for both components of Gam-COVID-Vac, which made it possible not only to meet the critical need for COVID-19 immunoprophylaxis in the Russian Federation, but also to supply this vaccine to a number of foreign countries.
ABSTRACT
Food adulteration is an enduring concern to date, and its detection and food authentication are some of the major approaches which can eradicate adulteration. This article reviews modern analytical techniques which are currently used for optimization and identification of adulterants. The Analytical techniques reviewed are distributed in three sections- Computer vision, Spectral and spectral Imaging techniques, and Electrical Techniques. Computer vision is a very advanced technique, allowing the analysis of several parameters with accurate and precise results. The hazardous effect of adulteration and future challenges and impacts are briefly discussed. The Previous decade is considered to be a massive success for food adulterant detection as it involved a chemometrics study. The use of chemometrics with analytical techniques is briefly discussed. Chemometrics is the science of extracting information from the chemical system by data-driven means. The inevitability of food in perspective to the current COVID-19 pandemic is very strong and authenticated food is a prior requirement. Copyright © 2022 Society of Pharmaceutical Sciences and Research. All rights reserved.
ABSTRACT
Favipiravir is a pyrazine carboxamide derivative discovered by Toyama chemical of Japan to act against many RNA viruses (potent broad spectrum inhibitor of Influenza & other RNA viruses). The present study gives the development of the RP HPLC method by using Quality by Design followed by validation of developed method for estimation co Favipiravir in bulk and tablet dosage form. The central composite method was applied on organic Phase concentration & buffer PH for initial Screening studies. The selection of optimum chromatographic condition was carried out by design space numerical, graphical optimization on retention time, Peak asymmetry & Theoretical Plates. Optimized analytical method consisted Acetonitrile: water (80:20%v/v) as mobile phase, pH 5, flow rate 1ml/min, a wavelength 323 nm. Favipiravir was eluted with retention time 2.7 min & peak area 51248, Favipiravir showed good linear relationship in range of 10-90 microg/ml with a correlation coefficient of 0.9985. The % RSD for intraday, inter day precision & Repeatability was found to be 0.88, 0.65 & 0.97 respectively. Limit of detection & quantification was found to be 104.44 microg/ml &. 316.5 microg/ml. The method validation parameters were in the prescribed limit as per ICH guidelines. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
ABSTRACT
Covid-19 has now spread to almost all parts of the world which has caused changes in the social order of life for humans. The spread of Covid-19 in Indonesia is relatively high, so the Indonesian government has adopted a policy using social distancing (large-scale social restrictions). Various pressures experienced by residents tend to result in exces-sive stress and emotions. This can have an impact on the occurrence of violence in families and generally the victims are ado-lescents. Physical abuse is an act that can cause physical pain such as slapping, stran-gling, hitting, kicking, stabbing, twisting the arm, threats with sharp weapons or weapons, and murder. The method used in this research is descriptive analytical method. The research sample was 192 people from various provinces in Indonesia aged 10-24 years. The results of this study revealed that some of the physical abuse behaviors were obtained by adolescents at elementary school age, namely in the age range of 10 years or more with details, including hard encouragement by others with a total of 48 (25.0%), getting hit with a hand with a total of 38 (52.8%), getting slapped by other people with a total of 43 (22.4%), getting hit with a hard object from another person with a total of 22 (11.5%), having been pushed and also being arrested with a total of 16 (8.4%), having been pelt-ed with something painfully from others with a total of 24 (12.5%), and had received treatment in the form of being bitten, punched, and kicked by another person with a total of 26 (13.5%). Physical abuse can have long-term effects, such as physical and psychological disturbances from the teenag-er, which can even lead to death. In addition, physical abuse can also cause adolescents to experience mental disorders such as depression and show traumatic symptoms. Copyright © the Author(s),2022 Licensee PAGEPress, Italy.
ABSTRACT
In recent months, the fight against COVID-19 has grown into one of the most actively pursued anti-toxin treatment strategies worldwide. Correct medical reasoning and a swift response are essential to preventing the COVID-19 epidemic from taking an unexpected turn. Corona virus can be detected via RT-PCR, although chest X-ray techniques have been more effective and helpful in detecting the virus's effects. With an increasing number of people being detected with COVID and a larger number of X-rays being taken, it is now viable to use transfer learning to categorise the X-ray results. Covid19, bacterial pneumonia, and normal incident X-ray datasets have been combined to develop an automatic method for detecting the disease. Specifically, the objective of this study is to achieve better image classification results over state-of-the-art models like the Convolutional Neural Network (CNN) that were developed recently. The data sets were collected from freely accessible online medical sources. The results shows that significant biomarkers associated with Covid-19 illness can be identified using a combination of Transfer Learning and X-ray imaging. In our experiments, we found that the best accuracy was achieved using a combination of VGG16, Resnet50, and a Convolutional Layer, with respective values of 96.78, 98.66%, and 96.46 %. X-rays' potential for utility in diagnosis has grown as the failure rates of older, more established analytical methods have grown alarmingly high. Copyright © 2022, Anka Publishers. All rights reserved.