Host autophagy mediates organ wasting and nutrient mobilization for tumor growth.

During tumor growth-when nutrient and anabolic demands are high-autophagy supports tumor metabolism and growth through lysosomal organelle turnover and nutrient recycling. Ras-driven tumors additionally invoke non-autonomous autophagy in the microenvironment to support tumor growth, in part through transfer of amino acids. Here we uncover a third critical role of autophagy in mediating systemic organ wasting and nutrient mobilization for tumor growth using a well-characterized malignant tumor model in Drosophila melanogaster. Micro-computed X-ray tomography and metabolic profiling reveal that RasV12 ; scrib-/- tumors grow 10-fold in volume, while systemic organ wasting unfolds with progressive muscle atrophy, loss of body mass, -motility, -feeding, and eventually death. Tissue wasting is found to be mediated by autophagy and results in host mobilization of amino acids and sugars into circulation. Natural abundance Carbon 13 tracing demonstrates that tumor biomass is increasingly derived from host tissues as a nutrient source as wasting progresses. We conclude that host autophagy mediates organ wasting and nutrient mobilization that is utilized for tumor growth.

Multi-animal pose estimation, identification and tracking with DeepLabCut.

Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having highly similar looking animals that interact more closely than in typical multi-human scenarios. To take up this challenge, we build on DeepLabCut, an open-source pose estimation toolbox, and provide high-performance animal assembly and tracking-features required for multi-animal scenarios. Furthermore, we integrate the ability to predict an animal's identity to assist tracking (in case of occlusions). We illustrate the power of this framework with four datasets varying in complexity, which we release to serve as a benchmark for future algorithm development.

The genetic diversity of Nipah virus across spatial scales.

BACKGROUND: Nipah virus (NiV), a highly lethal virus in humans, circulates in Pteropus bats throughout South and Southeast Asia. Difficulty in obtaining viral genomes from bats means we have a poor understanding of NiV diversity. METHODS: We develop phylogenetic approaches applied to the most comprehensive collection of genomes to date (N=257, 175 from bats, 73 from humans) from six countries over 22 years (1999-2020). We divide the four major NiV sublineages into 15 genetic clusters. Using Approximate Bayesian Computation fit to a spatial signature of viral diversity, we estimate the presence and the average size of genetic clusters per area. RESULTS: We find that, within any bat roost, there are an average of 2.4 co-circulating genetic clusters, rising to 5.5 clusters at areas of 1500-2000km2. We estimate that each genetic cluster occupies an average area of 1.3million km2 (95%CI: 0.6-2.3 million), with 14 clusters in an area of 100,000km2 (95%CI: 6-24). In the few sites in Bangladesh and Cambodia where genomic surveillance has been concentrated, we estimate that most clusters have been identified, but only ∼15% of overall NiV diversity has been uncovered. CONCLUSION: Our findings are consistent with entrenched co-circulation of distinct lineages, even within roosts, coupled with slow migration over larger spatial scales.

Monitoring SARS-CoV-2 variants in wastewater of Dhaka City, Bangladesh: approach to complement public health surveillance systems.

BACKGROUND: Wastewater-based epidemiological surveillance has been considered a powerful tool for early detection and monitoring of the dynamics of SARS-CoV-2 and its lineages circulating in a community. This study is aimed to investigate the complexity of SARS-CoV-2 infection dynamics in Dhaka city by examining its genetic variants in wastewater. Also, the study seeks to determine a connection between the SARS-CoV-2 variations detected in clinical testing and those found in wastewater samples. RESULTS: Out of 504 samples tested in RT-qPCR, 185 (36.7%) tested positive for SARS-CoV-2 viral RNA. The median log10 concentration of SARS-CoV-2 N gene copies/Liter of wastewater (gc/L) was 5.2, and the median log10 concentration of ORF1ab was 4.9. To further reveal the genetic diversity of SARS-CoV-2, ten samples with ORF1ab real-time RT-PCR cycle threshold (Ct) values ranging from 28.78 to 32.13 were subjected to whole genome sequencing using nanopore technology. According to clade classification, sequences from wastewater samples were grouped into 4 clades: 20A, 20B, 21A, 21J, and the Pango lineage, B.1, B.1.1, B.1.1.25, and B.1.617.2, with coverage ranging from 94.2 to 99.8%. Of them, 70% belonged to clade 20B, followed by 10% to clade 20A, 21A, and 21J. Lineage B.1.1.25 was predominant in Bangladesh and phylogenetically related to the sequences from India, the USA, Canada, the UK, and Italy. The Delta variant (B.1.617.2) was first identified in clinical samples at the beginning of May 2021. In contrast, we found that it was circulating in the community and was detected in wastewater in September 2020. CONCLUSION: Environmental surveillance is useful for monitoring temporal and spatial trends of existing and emerging infectious diseases and supports evidence-based public health measures. The findings of this study supported the use of wastewater-based epidemiology and provided the baseline data for the dynamics of SARS-CoV-2 variants in the wastewater environment in Dhaka, Bangladesh.

Recent Advances, Challenges, and Future Perspectives of ZnO Nanostructure Materials Towards Energy Applications.

In this approach, zinc oxide (ZnO) is a multipurpose substance with remarkable characteristics such as high sensitivity, a large specific area, non-toxicity, excellent compatibility, and a high isoelectric point, which make it attractive for discussion with some limitations. It is the most favorable possible option for the collection of nanostructures in terms of structure and their characteristics. The development of numerous ZnO nanostructure-based electrochemical sensors and biosensors used in health diagnosis, pharmaceutical evaluation, food hygiene, and contamination of the environment monitoring is described, as well as the production of ZnO nanostructures. Nanostructured ZnO has good chemical and temperature durability as an n-type semiconducting material, making it useful in a wide range of uses, from luminous materials to supercapacitors, batteries, solar cells, photocatalysis, biosensors, medicinal devices, and more. When compared to the bulk materials, the nanosized materials have both a higher rate of disintegration and a higher solubility. Furthermore, ZnO nanoparticles are regarded as top contenders for electrochemical sensors due to their strong electrochemical behaviors and electron transmission characteristics. The impact of many factors, including selectivity, sensitivity, detection limit, strength, and structures, arrangements, and their respective functioning processes, has been investigated. This study concentrated a substantial amount of its attention on the recent advancements that have been made in ZnO-based nanoparticles, composites, and modified materials for use in the application areas of energy storage and conversion devices as well as biological applications. Supercapacitors, Li-ion batteries, dye-sensitized solar cells, photocatalysis, biosensors, medicinal, and biological systems have been studied. ZnO-based materials are constantly analyzed for their advantages in energy and life science applications.

Progress and Perspectives on Promising Covalent-Organic Frameworks (COFs) Materials for Energy Storage Capacity.

In recent years, a new class of highly crystalline advanced permeable materials covalent-organic frameworks (COFs) have garnered a great deal of attention thanks to their remarkable properties, such as their large surface area, highly ordered pores and channels, and controllable crystalline structures. The lower physical stability and electrical conductivity, however, prevent them from being widely used in applications like photocatalytic activities and innovative energy storage and conversion devices. For this reason, many studies have focused on finding ways to improve upon these interesting materials while also minimizing their drawbacks. This review article begins with a brief introduction to the history and major milestones of COFs development before moving on to a comprehensive exploration of the various synthesis methods and recent successes and signposts of their potential applications in carbon dioxide (CO2 ) sequestration, supercapacitors (SCs), lithium-ion batteries (LIBs), and hydrogen production (H2 -energy). In conclusion, the difficulties and potential of future developing with highly efficient COFs ideas for photocatalytic as well as electrochemical energy storage applications are highlighted.

Gold Fluorescence Nanoparticles for Enhanced SERS Detection in Biomedical Sensor Applications: Current Trends and Future Directions.

Nanotechnology has emerged as a pivotal tool in biomedical research, particularly in developing advanced sensing platforms for disease diagnosis and therapeutic monitoring. Since gold nanoparticles are biocompatible and have special optical characteristics, they are excellent choices for surface-enhanced Raman scattering (SERS) sensing devices. Integrating fluorescence characteristics further enhances their utility in real-time imaging and tracking within biological systems. The synergistic combination of SERS and fluorescence enables sensitive and selective detection of biomolecules at trace levels, providing a versatile platform for early cancer diagnosis and drug monitoring. In cancer detection, AuNPs facilitate the specific targeting of cancer biomarkers, allowing for early-stage diagnosis and personalized treatment strategies. The enhanced sensitivity of SERS, coupled with the tunable fluorescence properties of AuNPs, offers a powerful tool for the identification of cancer cells and their microenvironment. This dual-mode detection not only improves diagnostic accuracy but also enables the monitoring of treatment response and disease progression. In drug detection, integrating AuNPs with SERS provides a robust platform for identifying and quantifying pharmaceutical compounds. The unique spectral fingerprints obtained through SERS enable the discrimination of drug molecules even in complex biological matrices. Furthermore, the fluorescence property of AuNPs makes it easier to track medication distribution in real-time, maximizing therapeutic effectiveness and reducing adverse effects. Furthermore, the review explores the role of gold fluorescence nanoparticles in photodynamic therapy (PDT). By using the complementary effects of targeted drug release and light-induced cytotoxicity, SERS-guided drug delivery and photodynamic therapy (PDT) can increase the effectiveness of treatment against cancer cells. In conclusion, the utilization of gold fluorescence nanoparticles in conjunction with SERS holds tremendous potential for revolutionizing cancer detection, drug analysis, and photodynamic therapy. The dual-mode capabilities of these nanomaterials provide a multifaceted approach to address the challenges in early diagnosis, treatment monitoring, and personalized medicine, thereby advancing the landscape of biomedical applications.

Chemistry Aspects and Designing Strategies of Flexible Materials for High-Performance Flexible Lithium-Ion Batteries.

In recent years, flexible and wearable electronics such as smart cards, smart fabrics, bio-sensors, soft robotics, and internet-linked electronics have impacted our lives. In order to meet the requirements of more flexible and adaptable paradigm shifts, wearable products may need to be seamlessly integrated. A great deal of effort has been made in the last two decades to develop flexible lithium-ion batteries (FLIBs). The selection of suitable flexible materials is important for the development of flexible electrolytes self-supported and supported electrodes. This review is focused on the critical discussion of the factors that evaluate the flexibility of the materials and their potential path toward achieving the FLIBs. Following this analysis, we present how to evaluate the flexibility of the battery materials and FLIBs. We describe the chemistry of carbon-based materials, covalent-organic frameworks (COFs), metal-organic frameworks (MOFs), and MXene-based materials and their flexible cell design that represented excellent electrochemical performances during bending. Furthermore, the application of state-of-the-art solid polymer and solid electrolytes to accelerate the development of FLIBs is introduced. Analyzing the contributions and developments of different countries has also been highlighted in the past decade. In addition, the prospects and potential of flexible materials and their engineering are also discussed, providing the roadmap for further developments in this fast-evolving field of FLIB research.

Bioresource Polymer Composite for Energy Generation and Storage: Developments and Trends.

The ever-growing demand of human society for clean and reliable energy sources spurred a substantial academic interest in exploring the potential of biological resources for developing energy generation and storage systems. As a result, alternative energy sources are needed in populous developing countries to compensate for energy deficits in an environmentally sustainable manner. This review aims to evaluate and summarize the recent progress in bio-based polymer composites (PCs) for energy generation and storage. The articulated review provides an overview of energy storage systems, e. g., supercapacitors and batteries, and discusses the future possibilities of various solar cells (SCs), using both past research progress and possible future developments as a basis for discussion. These studies examine systematic and sequential advances in different generations of SCs. Developing novel PCs that are efficient, stable, and cost-effective is of utmost importance. In addition, the current state of high-performance equipment for each of the technologies is evaluated in detail. We also discuss the prospects, future trends, and opportunities regarding using bioresources for energy generation and storage, as well as the development of low-cost and efficient PCs for SCs.

Synthesis of Electrical Conductive Metal-Organic Frameworks for Electrochemical Applications.

Electrical conductivity is very important property of nanomaterials for using wide range of applications especially energy applications. Metal-organic frameworks (MOFs) are notorious for their low electrical conductivity and less considered for usage in pristine forms. However, the advantages of high surface area, porosity and confined catalytic active sites motivated researchers to improve the conductivity of MOFs. Therefore, 2D electrical conductive MOFs (ECMOF) have been widely synthesized by developing the effective synthetic strategies. In this article, we have summarized the recent trends in developing the 2D ECMOFs, following the summary of potential applications in the various fields with future perspectives.

Recent Advances of Transition Metal Dichalcogenides-Based Materials for Energy Storage Devices, in View of Monovalent to Divalent Ions.

The fast growth of electrochemical energy storage (EES) systems necessitates using innovative, high-performance electrode materials. Among the various EES devices, rechargeable batteries (RBs) with potential features like high energy density and extensive lifetime are well suited to meet rapidly increasing energy demands. Layered transition metal dichalcogenides (TMDs), typical two dimensional (2D) nanomaterial, are considered auspicious materials for RBs because of their layered structures and large specific surface areas (SSA) that benefit quick ion transportation. This review summarizes and highlights recent advances in TMDs with improved performance for various RBs. Through novel engineering and functionalization used for high-performance RBs, we briefly discuss the properties, characterizations, and electrochemistry phenomena of TMDs. We summarised that engineering with multiple techniques, like nanocomposites used for TMDs receives special attention. In conclusion, the recent issues and promising upcoming research openings for developing TMDs-based electrodes for RBs are discussed.

2D MXenes Nanosheets for Advanced Energy Conversion and Storage Devices: Recent Advances and Future Prospects.

Since the initial MXenes were discovered in 2011, several MXene compositions constructed using combinations of various transition metals have been developed. MXenes are ideal candidates for different applications in energy conversion and storage, because of their unique and interesting characteristics, which included good electrical conductivity, hydrophilicity, and simplicity of large-scale synthesis. Herein, we study the current developments in two-dimensional (2D) MXene nanosheets for energy storage and conversion technologies. First, we discuss the introduction to energy storage and conversion devices. Later, we emphasized on 2D MXenes and some specific properties of MXenes. Subsequently, research advances in MXene-based electrode materials for energy storage such as supercapacitors and rechargeable batteries is summarized. We provide the relevant energy storage processes, common challenges, and potential approaches to an acceptable solution for 2D MXene-based energy storage. In addition, recent advances for MXenes used in energy conversion devices like solar cells, fuel cells and catalysis is also summarized. Finally, the future prospective of growing MXene-based energy conversion and storage are highlighted.

Polymorph Identification for Flexible Molecules: Linear Regression Analysis of Experimental and Calculated Solution- and Solid-State NMR Data.

The Δδ regression approach of Blade et al. [ J. Phys. Chem. A 2020, 124(43), 8959-8977] for accurately discriminating between solid forms using a combination of experimental solution- and solid-state NMR data with density functional theory (DFT) calculation is here extended to molecules with multiple conformational degrees of freedom, using furosemide polymorphs as an exemplar. As before, the differences in measured 1H and 13C chemical shifts between solution-state NMR and solid-state magic-angle spinning (MAS) NMR (Δδexperimental) are compared to those determined by gauge-including projector augmented wave (GIPAW) calculations (Δδcalculated) by regression analysis and a t-test, allowing the correct furosemide polymorph to be precisely identified. Monte Carlo random sampling is used to calculate solution-state NMR chemical shifts, reducing computation times by avoiding the need to systematically sample the multidimensional conformational landscape that furosemide occupies in solution. The solvent conditions should be chosen to match the molecule's charge state between the solution and solid states. The Δδ regression approach indicates whether or not correlations between Δδexperimental and Δδcalculated are statistically significant; the approach is differently sensitive to the popular root mean squared error (RMSE) method, being shown to exhibit a much greater dynamic range. An alternative method for estimating solution-state NMR chemical shifts by approximating the measured solution-state dynamic 3D behavior with an ensemble of 54 furosemide crystal structures (polymorphs and cocrystals) from the Cambridge Structural Database (CSD) was also successful in this case, suggesting new avenues for this method that may overcome its current dependency on the prior determination of solution dynamic 3D structures.

Recent Advances in Bioactive Carbon Nanotubes Based on Polymer Composites for Biosensor Applications.

Recent breakthroughs in the field of carbon nanotubes (CNTs) have opened up unprecedented opportunities for the development of specialized bioactive CNT-polymers for a variety of biosensor applications. The incorporation of bioactive materials, including DNA, aptamers and antibodies, into CNTs to produce composites of bioactive CNTs has attracted considerable attention. In addition, polymers are essential for the development of biosensors as they provide biocompatible conditions and are the ideal matrix for the immobilization of proteins. The numerous applications of bioactive compounds combined with the excellent chemical and physical properties of CNTs have led to the development of bioactive CNT-polymer composites. This article provides a comprehensive overview of CNT-polymer composites and new approaches to encapsulate bioactive compounds and polymers in CNTs. Finally, biosensor applications of bioactive CNT-polymer for the detection of glucose, H2O2 and cholesterol were investigated. The surface of CNT-polymer facilitates the immobilization of bioactive molecules such as DNA, enzymes or antibodies, which in turn enables the construction of state-of-the-art, future-oriented biosensors.

Assessment of heavy metals accumulation by vegetables irrigated with different stages of textile wastewater for evaluation of food and health risk.

Wastewater irrigation for vegetable cultivation is greatly concerned about the presence of toxic metals in irrigated soil and vegetables which causes possible threats to human health. This study aimed to ascertain the accumulation of heavy metals (HMs) in edible parts of vegetables irrigated with different stages of textile dyeing wastewater (TDW). Bio-concentration factor (BCF), Estimated daily intake (EDI), and target hazard quotient (THQ) were computed to estimate human health risks and speculate the hazard index (HI) of adults and children with the consumption of HMs contaminated vegetables at recommended doses. Five vegetables (red amaranth, Indian spinach, cauliflower, tomato, and radish) in a pot experiment were irrigated with groundwater (T1) and seven stages of TDW (T2∼T8) following a randomized complete block design (RCBD) with three replications. Among the TDW stages, T8, T7, T4, and T5 exhibited elevated BCF, EDI, THQ, and HI due to a rising trend in the accumulation of Pb, Cd, Cr, and Ni heavy metals in the edible portion of the red amaranth, followed by radish, Indian spinach, cauliflower, and tomato. The general patterns of heavy metal (HM) accumulation, regarded as vital nutrients for plants, were detected in the following sequence: Zn > Mn/Cu > Fe. Conversely, toxic metals were found to be Cd/Cr > Ni > Pb, regardless of the type of vegetables. Principal Component Analysis (PCA) identified T8, T7, and T4 of TDW as the primary contributors to the accumulation of heavy metals in the vegetables examined. Furthermore, the analysis of the heavy metals revealed that the BCF, THQ, and HI values for all studied metals were below 1, except for Pb. This suggests that the present consumption rates of different leafy and non-leafy vegetables, whether consumed individually or together, provide a low risk in terms of heavy metal exposure. Nevertheless, the consumption of T8, T7, and T4 irrigated vegetables, specifically Indian spinach alone or in combination with red amaranth and radish, by both adults and children, at the recommended rate, was found to pose potential health risks. On the other hand, T2, T3, and T6 irrigated vegetables were deemed safe for consumption. These findings indicated that the practice of irrigating the vegetables with T8, T7, and T4 stages of TDW has resulted in a significant buildup of heavy metals in the soils and edible parts of vegetables which are posing health risks to adults and children. Hence, it is imperative to discharge the T8, T7, and T4 stages of TDW after ETP to prevent the contamination of vegetables and mitigate potential health risks.

Computer aided design/computer aided manufacturing (CAD/CAM) technology in the undergraduate dental programs in the MENA region.

INTRODUCTION: The aim of this study was to understand the trends of teaching Computer Aided Design/Computer Aided Manufacturing (CAD/CAM) in the undergraduate dental curriculum in the MENA region by conducting an online survey among the undergraduate dental colleges in this region. MATERIALS AND METHODS: An online survey was conducted using Google Forms consisting of 20 questions that could be answered by "yes" or "no" responses, multiple-choice answers or in a descriptive, "open" format. A total of 55 participants from the MENA region representing their dental college were requested to participate in this study. RESULTS: The response rate of the survey was 85.5% following the twofold follow-up reminders method. Although the vast majority of professors demonstrated vital knowledge in the practical use of CAD/CAM, the majority of them did not provide theoretical and practical training on CAD/CAM in their institutions. Among the schools with established levels of teaching CAD/CAM, nearly 50% of them provide both pre-clinical and clinical training on CAD/CAM. Despite the availability of extra-curricular training courses on CAD/CAM outside the university setting, there is a lack of advocating for students to enrol in those courses by the institutions. More than 80% of the participants agreed that CAD/CAM has a strong future in chair-side dental clinics and CAD/CAM needs to be incorporated within undergraduate studies. CONCLUSION: Based on the results of the current study, it is understandable that an intervention is required by the dental education providers to cope with the growing demand for CAD/CAM technology for the current and future dental practitioners of the MENA region.

Nipah Virus Exposure in Domestic and Peridomestic Animals Living in Human Outbreak Sites, Bangladesh, 2013-2015.

Spillovers of Nipah virus (NiV) from Pteropus bats to humans occurs frequently in Bangladesh, but the risk for spillover into other animals is poorly understood. We detected NiV antibodies in cattle, dogs, and cats from 6 sites where spillover human NiV infection cases occurred during 2013-2015.

Development of a novel glycoengineering platform for the rapid production of conjugate vaccines.

Conjugate vaccines produced either by chemical or biologically conjugation have been demonstrated to be safe and efficacious in protection against several deadly bacterial diseases. However, conjugate vaccine assembly and production have several shortcomings which hinders their wider availability. Here, we developed a tool, Mobile-element Assisted Glycoconjugation by Insertion on Chromosome, MAGIC, a novel biotechnological platform that overcomes the limitations of the current conjugate vaccine design method(s). As a model, we focused our design on a leading bioconjugation method using N-oligosaccharyltransferase (OTase), PglB. The installation of MAGIC led to at least twofold increase in glycoconjugate yield via MAGIC when compared to conventional N-OTase based bioconjugation method(s). Then, we improved MAGIC to (a) allow rapid installation of glycoengineering component(s), (b) omit the usage of antibiotics, (c) reduce the dependence on protein induction agents. Furthermore, we show the modularity of the MAGIC platform in performing glycoengineering in bacterial species that are less genetically tractable than the commonly used Escherichia coli. The MAGIC system promises a rapid, robust and versatile method to develop vaccines against serious bacterial pathogens. We anticipate the utility of the MAGIC platform could enhance vaccines production due to its compatibility with virtually any bioconjugation method, thus expanding vaccine biopreparedness toolbox.

Microenvironmental autophagy promotes tumour growth.

As malignant tumours develop, they interact intimately with their microenvironment and can activate autophagy, a catabolic process which provides nutrients during starvation. How tumours regulate autophagy in vivo and whether autophagy affects tumour growth is controversial. Here we demonstrate, using a well characterized Drosophila melanogaster malignant tumour model, that non-cell-autonomous autophagy is induced both in the tumour microenvironment and systemically in distant tissues. Tumour growth can be pharmacologically restrained using autophagy inhibitors, and early-stage tumour growth and invasion are genetically dependent on autophagy within the local tumour microenvironment. Induction of autophagy is mediated by Drosophila tumour necrosis factor and interleukin-6-like signalling from metabolically stressed tumour cells, whereas tumour growth depends on active amino acid transport. We show that dormant growth-impaired tumours from autophagy-deficient animals reactivate tumorous growth when transplanted into autophagy-proficient hosts. We conclude that transformed cells engage surrounding normal cells as active and essential microenvironmental contributors to early tumour growth through nutrient-generating autophagy.

The role of trust and habit in the adoption of mHealth by older adults in Hong Kong: a healthcare technology service acceptance (HTSA) model.

BACKGROUND: Evidence from the literature suggests that mobile health (mHealth) services can potentially improve healthcare outcomes among older adults. Hence, the government of Hong Kong has recently taken several community and information technology (IT) services initiatives to train older adults on how to enhance their abilities and interest in using mHealth technology. Although mHealth services have been widely implemented globally, their adoption and use by older adults are very low, including those in Hong Kong. This study aims to understand key factors influencing mHealth use intention among the older Chinese population in Hong Kong. METHODS: We extended the Unified Theory of Acceptance and Use of Technology (UTAUT2) as the basis of our conceptual framework. We applied Partial Least Squares path modeling method to conduct the Structural Equation Model (SEM) technique that allows measuring the theoretical validity of any conceptual framework. Convenience and snowball sampling methods were used to recruit participants aged 65 or above. In total, 201 valid responses were used for testing the theoretical validity of the proposed conceptual framework. RESULTS: The primary finding shows that the widely used UTAUT2 model falls short in explaining mHealth service acceptance behavior in the Chinese older population in Hong Kong. We further propose a simplified model, the Healthcare Technology Service Acceptance (HTSA) model, to understand the formation of mHealth service acceptance behavior. The findings show that trust is an important component of technology service acceptance intention behavior that was missing in the UTAUT2 model. The results also show that several antecedent factors (i.e., social influence, government policy, and service quality) are critical in forming technology trust beliefs. CONCLUSIONS: The study shows that the HTSA model can better explain mHealth acceptance behavior than the UTAUT2 model. This study advances knowledge in the mHealth technology adoption domain by proposing a simplified new version of the UTAUT2 model for understanding healthcare technology service acceptance and use intention among older adults. The findings of the study provide valuable information to the Hong Kong government and healthcare organizations for wider adoption of mHealth services, especially in older adults.