Research Tool Research Articles

Empowering geological data analysis with specialized software GIS modules

This research is devoted to the development of a geographic information system (GIS) for the analysis of geological data. It presents two specialized software modules designed to solve complex geological problems related to potential progress to disturbed masses and magnetotelluric sounding. These modules are integrated into the QGIS environment, offering efficient data processing and analysis capabilities, contributing to a deeper understanding of geological structures. The study presents a mathematical model for the problem of magnetotelluric sounding (MTS) and the continuation of potentials towards the perturbed masses, demonstrating numerical results using the developed algorithm. To confirm the accuracy of the model, a comparative analysis was carried out with empirical data for various chemical elements, which showed high accuracy, especially at shallow depths, with an error rate of less than 2%. In addition, the study highlights the importance of powerful GIS for the analysis and interpretation of geological data, including geochemical, geophysical and remote sensing information. The advanced functionality of QGIS simplifies data processing and visualization, which makes it an invaluable tool for geologists and researchers.

Animal models for partial heart transplantation.

Partial heart transplantation delivers growing heart valve implants by transplanting the part of the heart containing the necessary heart valve only. In contrast to heart transplantation, partial heart transplantation spares the native ventricles. This has important implications for partial heart transplant biology, including the allowable ischemia time, optimal graft preservation, primary graft dysfunction, immune rejection, and optimal immunosuppression. Exploration of partial heart transplant biology will depend on suitable animal models. Here we review our experience with partial heart transplantation in rodents, piglets, and non-human primates. This review is based on our experience with partial heart transplantation using over 100 rodents, over 50 piglets and one baboon. Suitable animal models for partial heart transplantation include rodent heterotopic partial heart transplantation, piglet orthotopic partial heart transplantation, and non-human primate partial heart xenotransplantation. Rodent models are relatively cheap and offer extensive availability of research tools. However, rodent open-heart surgery is technically not feasible. This limits rodents to heterotopic partial heart transplant models. Piglets are comparable in size to children. This allows for open-heart surgery using clinical grade equipment for orthoptic partial heart transplantation. Piglets also grow rapidly, which is useful for studying partial heart transplant growth. Finally, nonhuman primates are immunologically most closely related to humans. Therefore, nonhuman primates are most suitable for studying partial heart transplant immunobiology and xenotransplantation. Animal research is a privilege that is contingent on utilitarian ethics and the 3R principles of replacement, reduction and refinement. This privilege allows the research community to seek fundamental knowledge about partial heart transplantation, and to apply this knowledge to enhance the health of children who require partial heart transplants.

Analytical Method Development and Optimization on High Performance Liquid Chromatography for Related Substances Test of Gliclazide Drug as Active Pharmaceutical Ingredient

Diabetes mellitus, particularly Type 2 Diabetes Mellitus (T2DM), presents a significant global health challenge, necessitating continuous advancements in therapeutic strategies. Gliclazide, an oral selective inhibitor of sodium glucose co-transporter-2 (SGLT2), has emerged as a promising agent for managing T2DM by facilitating urinary glucose excretion and reducing plasma glucose levels. However, ensuring the quality and efficacy of pharmaceutical formulations remains crucial for regulatory approval and clinical effectiveness. In this study, we present the development of an improved stability-indicating Reverse Phase-High Performance Liquid Chromatography (RP-HPLC) method for the precise quantification of Gliclazide. The novel analytical method employs 0.1% Potassium Phosphate in water 0.1% Potassium Phosphate in methanol (MeOH) as the mobile phase, demonstrating enhanced sensitivity, cost-effectiveness, and reduced reliance on organic chemicals. Through rigorous validation following International Conference on Harmonisation (ICH) guidelines, the developed method exhibited superior performance in terms of retention times compared to existing methodologies. The proposed analytical approach holds promise for routine analysis of Gliclazide in both bulk and tablet formulations, offering a valuable tool for pharmaceutical quality control and clinical research in the management of T2DM.

Development and characterization of phospho-ubiquitin antibodies to monitor PINK1-PRKN signaling in cells and tissue

ABSTRACT The selective removal of dysfunctional mitochondria, a process termed mitophagy, is critical for cellular health and impairments have been linked to aging, Parkinson disease, and other neurodegenerative conditions. A central mitophagy pathway is orchestrated by the ubiquitin (Ub) kinase PINK1 together with the E3 Ub ligase PRKN/Parkin. The decoration of damaged mitochondrial domains with phosphorylated Ub (p-S65-Ub) mediates their elimination though the autophagy system. As such p-S65-Ub has emerged as a highly specific and quantitative marker of mitochondrial damage with significant disease relevance. Existing p-S65-Ub antibodies have been successfully employed as research tools in a range of applications including western blot, immunocytochemistry, immunohistochemistry, and enzyme-linked immunosorbent assay. However, physiological levels of p-S65-Ub in the absence of exogenous stress are very low, therefore difficult to detect and require reliable and ultrasensitive methods. Here we generated and characterized a collection of novel recombinant, rabbit monoclonal p-S65-Ub antibodies with high specificity and affinity in certain applications that allow the field to better understand the molecular mechanisms and disease relevance of PINK1-PRKN signaling. These antibodies may also serve as novel diagnostic or prognostic tools to monitor mitochondrial damage in various clinical and pathological specimens. Abbreviations: AD: Alzheimer disease; CCCP: carbonyl cyanide 3-chlorophenylhydrazone; ELISA: enzyme-linked immunosorbent assay; HEK293E cell: human embryonic kidney E cell; ICC: immunocytochemistry; IHC: immunohistochemistry: KO: knockout; LoB: limit of blank; LoD: limit of detection; LoQ: limit of quantification; MEF: mouse embryonic fibroblast; MSD: Meso Scale Discovery; n.s.: non-significant; nonTg: non-transgenic; PBMC: peripheral blood mononuclear cell; PD: Parkinson disease; p-S65-PRKN: phosphorylated PRKN at serine 65; p-S65-Ub: phosphorylated Ub at serine 65; Ub: ubiquitin; WT: wild-type.

Smartphone-based optical sectioning (SOS) microscopy with a telecentric design for fluorescence imaging.

We propose a smartphone-based optical sectioning (SOS) microscope based on the HiLo technique, with a single smartphone replacing a high-cost illumination source and a camera sensor. We built our SOS with off-the-shelf optical, mechanical cage systems with 3D-printed adapters to seamlessly integrate the smartphone with the SOS main body. The liquid light guide can be integrated with the adapter, guiding the smartphone's LED light to the digital mirror device (DMD) with neglectable loss. We used an electrically tuneable lens (ETL) instead of a mechanical translation stage to realise low-cost axial scanning. The ETL was conjugated to the objective lens's back pupil plane (BPP) to construct a telecentric design by a 4f configuration to maintain the lateral magnification for different axial positions. SOS has a 571.5µm telecentric scanning range and an 11.7µm axial resolution. The broadband smartphone LED torch can effectively excite fluorescent polystyrene (PS) beads. We successfully used SOS for high-contrast fluorescent PS beads imaging with different wavelengths and optical sectioning imaging of multilayer fluorescent PS beads. To our knowledge, the proposed SOS is the first smartphone-based HiLo optical sectioning microscopy (£1965), which can save around £7035 compared with a traditional HiLo system (£9000). It is a powerful tool for biomedical research in resource-limited areas.

Forty Years of HIV Research in French Guiana: Comprehend to Combat

The drivers of the HIV epidemic, the viruses, the opportunistic infections, the attitudes and the resources allocated to the fight against HIV/AIDS, vary substantially across countries. French Guiana, at the crossroads between Amazonian South America and the Caribbean, constitutes a singular context with poor populations and rich country health funding, which has allowed researchers to gather lots of information on the particulars of our epidemic. We aimed to focus on the little known story of forty years of HIV research in French Guiana and emphasize how local research intertwined with public health action has yielded continuous progress, despite the difficult social conditions of the affected population. We searched Web of Science and associated local experts who worked through much of the epidemic in selecting the most meaningful products of local research for clinical and public health outcomes in French Guiana. Research tools and facilities included, from 1991 onwards, the HIV hospital cohort and the HIV-histoplasmosis cohort. Ad hoc studies funded by the ANRS or the European Regional Development fund shed light on vulnerable groups. The cumulative impact of prospective routine collection and focused efforts has yielded a breadth of knowledge, allowing for informed decisions and the adaptation of prevention, testing and care in French Guiana. After this overview, we emphasize that the close integration of research and public health was crucial in adapting interventions to the singular context of French Guiana.

First draft reference genome and annotation of the alternative oil species Physaria fendleri.

In the wake of increasing demand for renewable energy sources, plant-based sources including alternative oilseeds have come to the forefront of interest. Hydroxy fatty acids (HFAs), produced in a few oilseed species, are important chemical feedstocks for industrial applications. An integrated approach was taken to assemble the first draft genome of the alternative HFA producer Physaria fendleri (n = 6), an outcrossing species with high heterozygosity. Both de novo transcriptome assemblies and genome assemblies were produced with public and generated sequencing reads. Resulting intermediate assemblies were then scaffolded and patched with multiple data sources, followed by super-scaffolding onto a masked genome of Camelina laxa (n = 6). Despite a current lack of available resources for the physical mapping of genomic scaffolds of Physaria fendleri, topography of the genome with respect to repeat and gene content was preserved at the scaffold level and not significantly lost via super-scaffolding. Read representation, gene and genome completion statistics, and annotation results illustrated the creation of a functional draft genome and a tool for future research on alternative oil species.

POxload: Machine Learning Estimates Drug Loadings of Polymeric Micelles.

Block copolymers, composed of poly(2-oxazoline)s and poly(2-oxazine)s, can serve as drug delivery systems; they form micelles that carry poorly water-soluble drugs. Many recent studies have investigated the effects of structural changes of the polymer and the hydrophobic cargo on drug loading. In this work, we combine these data to establish an extended formulation database. Different molecular properties and fingerprints are tested for their applicability to serve as formulation-specific mixture descriptors. A variety of classification and regression models are built for different descriptor subsets and thresholds of loading efficiency and loading capacity, with the best models achieving overall good statistics for both cross- and external validation (balanced accuracies of 0.8). Subsequently, important features are dissected for interpretation, and the DrugBank is screened for potential therapeutic use cases where these polymers could be used to develop novel formulations of hydrophobic drugs. The most promising models are provided as an open-source software tool for other researchers to test the applicability of these delivery systems for potential new drug candidates.

Design of Machine Learning-Based Algorithms for Virtualized Diagnostic on SPARC_LAB Accelerator

Machine learning deals with creating algorithms capable of learning from the provided data. These systems have a wide range of applications and can also be a valuable tool for scientific research, which in recent years has been focused on finding new diagnostic techniques for particle accelerator beams. In this context, SPARC_LAB is a facility located at the Frascati National Laboratories of INFN, where the progress of beam diagnostics is one of the main developments of the entire project. With this in mind, we aim to present the design of two neural networks aimed at predicting the spot size of the electron beam of the plasma-based accelerator at SPARC_LAB, which powers an undulator for the generation of an X-ray free electron laser (XFEL). Data-driven algorithms use two different data preprocessing techniques, namely an autoencoder neural network and PCA. With both approaches, the predicted measurements can be obtained with an acceptable margin of error and most importantly without activating the accelerator, thus saving time, even compared to a simulator that can produce the same result but much more slowly. The goal is to lay the groundwork for creating a digital twin of linac and conducting virtualized diagnostics using an innovative approach.

A Simple, Robust, and Versatile MATLAB Formulation of the Dynamic Memdiode Model for Bipolar-Type Resistive Random Access Memory Devices

Modeling in an emerging technology like RRAM devices is one of the pivotal concerns for its development. In the current bibliography, most of the models face difficulties in implementing or simulating unconventional scenarios, particularly when dealing with complex input signals. In addition, circuit simulators like Spice require long running times for high-resolution results because of their internal mathematical implementation. In this work, a fast, simple, robust, and versatile model for RRAM devices built in MATLAB is presented. The proposed model is a recursive and discretized version of the dynamic memdiode model (DMM) for bipolar-type resistive switching devices originally implemented in LTspice. The DMM model basically consists of two coupled equations: one for the current (non-linear current generator) and a second one for the memory state of the device (time-dependent differential equation). This work presents an easy-to-use tool for researchers to reproduce the experimental behavior of their devices and predict the outcome from non-trivial experiments. Three study cases are reported, aimed at capturing different phenomenologies: a frequency effect study, a cycle-to-cycle variability fit, and a stochastic resonance impact analysis.

Unveiling South African insect diversity: DNA barcoding’s contribution to biodiversity data

Insects are one of the most species-rich groups on Earth. They comprise much of animal diversity and play vital roles in ecosystems, including pollination, pest control, and decomposition. However, only a fraction of this diversity has been formally described. South Africa is recognised as one of the most biologically diverse countries globally, with an estimated 44 000 insect species. Many crops rely on insect pollinators, including canola, apples, oranges, and sunflowers. A shortage of wild pollinators currently threatens crop yields, yet our knowledge of insect diversity within South Africa is sparse. There are few taxonomic specialists relative to South Africa’s biodiversity, and the methods used for insect identification can be time-consuming and expensive. DNA barcoding provides an important research tool to accelerate insect biodiversity research. In this review, we queried the public DNA barcoding BOLD (Barcode of Life Data System) database for records of “Insecta” within South Africa, and 416 211 published records assigned to 28 239 unique BINs (Barcode Index Numbers) were returned. We identified five taxonomic orders with more BINs than known species in southern Africa (Hymenoptera, Diptera, Thysanoptera, Plecoptera, and Strepsiptera). Most of the barcoded records were derived from Malaise trap sampling in Gauteng, Mpumalanga and Limpopo, while the rest of South Africa remains poorly sampled. We suggest that there is a need for a comprehensive national sampling effort alongside increased investment in taxonomic expertise to generate critical baseline data on insect biodiversity before species are lost to extinction.

Current status of electronic health literacy among pregnant women with gestational diabetes mellitus and their perceptions of online health information: a mixed-methods study

BackgroundWomen diagnosed with gestational diabetes mellitus often rely on internet-based health information for managing their condition. This study aims to investigate the present state of electronic health literacy among women with gestational diabetes mellitus, analyze the influencing factors, and explore their experiences regarding accessing, comprehending, evaluating, and applying online health information pertinent to gestational diabetes mellitus.MethodsA sequential explanatory mixed methods research design was adopted in this study. Initially, 235 women with gestational diabetes mellitus participated in a cross-sectional survey. The research tools included general information and the Chinese version of the electronic Health Literacy Scale (eHEALS). Descriptive analyses were conducted to describe the characteristics of the sample, and multiple linear regression analyses were used to explore the factors influencing electronic health literacy among women with gestational diabetes mellitus. Secondly, 11 women with gestational diabetes mellitus joined semi-structured in-depth interviews to obtain their perceptions about online health information. The data were analyzed using inductive content analysis to develop themes.ResultsThe median score of eHEALS in the Chinese version among 235 women diagnosed with gestational diabetes mellitus was 29 (interquartile range [IQR], 26 to 32). Factors influencing electronic health literacy among these women included accessing health information from medical professionals (β = 0.137, p = 0.029) and utilizing health information from applications (β = 0.159, p = 0.013). From the qualitative phase of the study, four thematic categories emerged: reasons and basis for accessing health information from the Internet; address barriers to accessing and applying online health information; desires for a higher level of online health information services; outcomes of accessing and applying online health information.ConclusionThe electronic health literacy of women diagnosed with gestational diabetes mellitus remains suboptimal and warrants improvement. The sources of access to health information affect electronic health literacy in women with gestational diabetes mellitus. Moreover, women facing gestational diabetes encounter numerous impediments when attempting to access health-related information online, underscoring the necessity for enhanced online health information services to meet their needs.

Generation of Alzheimer’s Disease Model Derived from Induced Pluripotent Stem Cells with APP Gene Mutation

Alzheimer’s disease (AD), the most common cause of dementia, is characterized by disruptions in memory, cognition, and personality, significantly impacting morbidity and mortality rates among older adults. However, the exact pathophysiological mechanism of AD remains unknown, and effective treatment options for AD are still lacking. Human induced pluripotent stem cells (iPSC) are emerging as promising platforms for disease research, offering the ability to model the genetic mutations associated with various conditions. Patient-derived iPSCs are useful for modeling neurodegenerative and neurodevelopmental disorders. In this study, we generated AD iPSCs from peripheral blood mononuclear cells obtained from a 65-year-old patient with AD carrying the E682K mutation in the gene encoding the amyloid precursor protein. Cerebral organoids derived from AD iPSCs recapitulated the AD phenotype, exhibiting significantly increased levels of tau protein. Our analysis revealed that an iPSC disease model of AD is a valuable assessment tool for pathophysiological research and drug screening.

Investigating the Application of Regression Discontinuity in the Field of International Health Economics

As one of the most significant quasi-experimental research methods, with over eight decades of development, Regression Discontinuity Design (RDD) has garnered extensive attention within the field of international health economics. It has provided robust methodological support for causal inference in research conducted within this domain. This paper provides a comprehensive review and synthesis of the foundational concepts, origins, and evolutionary trajectory of the RDD. It systematically examines the relevant studies in the domain of international health economics, discusses the strengths and limitations of the RDD, and anticipates its future applications in the same field. The aim is to support the utilization of RDD in international health economic research. On a theoretical level, it has effectively enhanced the flexibility and applicability of research designs within the domain of international health economics, augmenting the economic efficiency and external validity of studies, and offering a versatile tool for related research on a global scale. On a practical level, RD accommodates the diverse policy needs of programs across various countries and regions. It provides a more robust and reliable empirical foundation for the formulation of pertinent health policies, aiming to improve the efficiency of health resource allocation and promote equity in health outcomes.

An Optimized Protocol for the Generation of Alveolospheres from Wild-Type Mice

Organoid models have become an integral part of the research methodology in the lung field. These systems allow for the study of progenitor and stem cell self-renewal, self-organization, and differentiation. Distinct models of lung organoids mimicking various anatomical regions of mature lungs have emerged in parallel to the increased gain of knowledge regarding epithelial stem and progenitor cell populations and the corresponding mesenchymal cells that populate the in vivo niche. In the distal lung, type 2 alveolar epithelial cells (AEC2s) represent a stem cell population that is engaged in regenerative mechanisms in response to various insults. These cells self-renew and give rise to AEC1s that carry out gas exchange. Multiple experimental protocols allowing the generation of alveolar organoids, or alveolospheres, from murine lungs have been described. Among the drawbacks have been the requirement of transgenic mice allowing the isolation of AEC2s with high viability and purity, and the occasional emergence of bronchiolar and bronchioalveolar organoids. Here, we provide a refined gating strategy and an optimized protocol for the generation of alveolospheres from wild-type mice. Our approach not only overcomes the need for transgenic mice to generate such organoids, but also yields a pure culture of alveolospheres that is devoid of bronchiolar and bronchioalveolar organoids. Our protocol contributes to the standardization of this important research tool.

The Meioflume: A new system for observing the interstitial behavior of meiofauna

Abstract Meiofauna (benthic invertebrates < 1 mm in size) facilitate sediment biogeochemical cycling, alter sediment microbial community structure, and serve as an important trophic link between benthic micro- and macrofauna, yet the behaviors that mechanistically link individuals to their ecological effects are largely unknown. Meiofauna are small and sediments are opaque, making observing the in situ activities of these animals challenging. We developed the Meioflume, a small, acrylic flow tunnel filled with grains of cryolite, a transparent sand analog, to simulate the in situ conditions experienced by meiofauna in an observable lab environment. The Meioflume has a working area (28.57×10.16×1 mm) that is small enough to quickly locate fauna and clearly observe behavior but large enough that animals are not tightly confined. When connected to a syringe press, the Meioflume can produce low velocity flows consistently and evenly across the width of its working area, while retaining the contents. To demonstrate its functionality in observing the behavior of meiofauna, we placed individual meiofaunal animals (a protodrilid annelid, a harpacticoid copepod, and a platyhelminth flatworm) in Meioflumes and filmed their behavioral response to a sudden initiation of porewater flow. All animals were clearly visible within the flume and could be observed responding to the onset of flow. The design and construction of the Meioflume make it an accessible, affordable tool for researchers. This experimental system could be modified to address many questions in meiofaunal ecology, such as studying behavior in response to chemical cues, allowing us to observe meiofaunal behaviors to better understand their ecological effects.

Machine-Learning Strategies for the Accurate and Efficient Analysis of X-ray Spectroscopy

Abstract Computational spectroscopy has emerged as a critical tool for researchers looking to achieve both qualitative and quantitative interpretations of experimental spectra. Over the past decade, increased interactions between experiment and theory have created a positive feedback loop that has stimulated developments in both domains. In particular, the increased accuracy of calculations has led to them becoming an indispensable tool for the analysis of spectroscopies across the electromagnetic spectrum. This progress is especially well demonstrated for short-wavelength techniques, e.g. core-hole (X-ray) spectroscopies, whose prevalence has increased following the advent of modern X-ray facilities including third-generation synchrotrons and X-ray free-electron lasers (XFELs). While calculations based on well-established wavefunction or density-functional methods continue to dominate the greater part of spectral analyses in the literature, emerging developments in machine-learning algorithms are beginning to open up new opportunities to complement these traditional techniques with fast, accurate, and affordable 'black-box' approaches. This Topical Review recounts recent progress in data-driven/machine-learning approaches for computational X-ray spectroscopy. We discuss the achievements and limitations of the presently-available approaches and review the potential that these techniques have to expand the scope and reach of computational and experimental X-ray spectroscopic studies.


Application and challenge of pancreatic organoids in therapeutic research

The in-vivo non-human primate animal and in-vitro cell disease models play a crucial part in the study of the mechanisms underlying the occurrence and development of pancreatic diseases, but with increasingly prominent limitations with in-depth research. Organoids derived from human pluripotent and adult stem cells resemble human in-vivo organs in their cellular composition, spatial tissue structure and physiological function, making them as an advantageous research tool. Up until now, numerous human organoids, including pancreas, have been effectively developed, demonstrating significant potential for research in organ development, disease modeling, drug screening, and regenerative medicine. However, different from intestine, liver and other organs, the pancreas is the only special organ in the human body, consisting of an exocrine gland and an endocrine gland. Thus, the development of pancreatic organoid technology faces greater challenges, and how to construct a composite pancreatic organoid with exocrine and endocrine gland is still difficult in current research. By reviewing the fundamental architecture and physiological role of the human pancreas, along with the swiftly developing domain of pancreatic organoids, we summarize the method and characteristics of human pancreatic organoids, and its application in modeling pancreatic diseases, as a platform for individualized drug screening and in regenerative medicine study. As the first comprehensive review that focus on the pharmacological study of human pancreatic organoid, the review hopes to help scholars to have a deeper understanding in the study of pancreatic organoid.

Duet playing in dementia care: a new therapeutic music technology

Purpose Supporting the relational worlds of people living with dementia, especially the spousal dyad, is a growing focus in dementia care as is advancing the therapeutic use of music in dementia care. This paper describes a mixed-methods, multi-phase, iterative research study designed to develop the Music Memory Makers (MMM) Duet System, a novel therapeutic music technology, that allows non-musicians to play a personalized repertoire of songs arranged as duets. Methods Following a pilot phase to iteratively assess and refine the MMM Duet System for recreational and therapeutic purposes, multiple sources of data were used to investigate five older spousal dyads’ experiences with the system, two couples living with dementia and three who were not. We assessed perceptions of task difficulty, joint agency, and enjoyment as well as therapeutic benefits associated with enhancing the spousal relationship and sense of couplehood. Results Findings suggest playing meaningful songs together is an enjoyable interactive activity that prompts musical reminiscence, involves joint agency, and supports relationship continuity within a relational, positive approach to dementia care. All couples mastered the task, none evaluated it as “very challenging,” and positive couple interactions were evoked, commonly before and after playing the duets. Conclusions The MMM Duet System is recommended for further research and development as an innovative way to support couples living with dementia with commercial implications, and as a new music technology suitable for use as a research tool.

Vaccine communication strategies among healthcare workers as a reflection of the Israeli Ministry of Health’s communication strategies before and after the COVID-19 pandemic

BackgroundHealthcare workers play a central role in communicating information to the public regarding vaccines. Most of the literature has focused on healthcare workers’ hesitancy and doubts about getting the flu vaccine themselves. However, few studies have dealt with how they perceive their role in communicating information regarding vaccines, especially following the COVID-19 pandemic.Objectives(1) To identify the communication strategies used by the Israeli Ministry of Health regarding vaccines during epidemic crises (before and after the COVID-19 pandemic); (2) To identify the communication strategies used by healthcare workers regarding vaccines before and after the COVID-19 pandemic.MethodsA qualitative study based on in-depth interviews was conducted among healthcare workers and used a semi-structured protocol as a research tool. A total of 18 healthcare workers were sampled using purposeful and snowball sampling.ResultsDespite healthcare workers’ perception that there has been a decrease in trust in the Israeli Ministry of Health among the public following the COVID-19 outbreak, they still rely on the Israeli Ministry of Health as their primary source of information and use the same communication strategies (such as fear appeals and correcting information) as of the Israeli Ministry of Health to communicate with the public, healthcare providers, and other relevant stakeholders.ConclusionHealthcare workers have been shaped by the professional socialization processes within the health system, leading to a predominant reliance on established communication strategies and informational channels. This reliance underscores the importance of evolving these methods to better engage with the public. To address this, there is a compelling need to innovate and adopt new communication techniques that emphasize effective dialogue and transparent interactions. By doing so, healthcare professionals can ensure that their outreach is not only informative but also responsive to the diverse needs and preferences of the community.