Evaluating the impact of mesenchymal stem cell therapy on visual acuity and retinal nerve fiber layer thickness in optic neuropathy patients: a comprehensive systematic review and meta-analysis.

BACKGROUND: Stem cell therapy has emerged as a potential therapeutic avenue for optic neuropathy patients. To assess its safety and efficacy, we conducted a systematic review and meta-analysis, focusing on the latest evidence pertaining to the improvement of visual acuity (VA) through stem cell therapy. METHODS: We analyzed Each database from its inception until June 2024. PubMed, Scopus, and Google Scholar were systematically searched to identify the included studies. Data were extracted regarding the year of publication, the name of the first author, sample size, VA (Log Mar), and Retinal Nerve Fiber Layer (RNFL) thickness. PRISMA protocol was used as a guide to perform this meta-analysis. STATA 16 was used for statistical analysis. RESULTS: A total of 66 eyes were examined in seven papers. Based on the meta-analysis, the mean VA (Log MAR) of patients with optic neuropathy improved from 0.90 to 0.65 following stem cell therapy intervention (p-value = 0.001). The thickness of the RNFLs did not demonstrate a significant change (p-value was 0.174). CONCLUSION: According to this systematic review and meta-analysis, stem cell therapy may improve the visual acuity of patients with optic neuropathy. Aside from the traditional therapy that can be provided to patients with optic neuropathy, stem cell therapy may also be beneficial.

Refresh Rate-Based Caching and Prefetching Strategies for Internet of Things Middleware.

One of the research directions in Internet of Things (IoT) is the field of Context Management Platforms (CMPs) which is a specific type of IoT middleware. CMPs provide horizontal connectivity between vertically oriented IoT silos resulting in a noticeable difference in how IoT data streams are processed. As these context data exchanges can be monetised, there is a need to model and predict the context metrics and operational costs of this exchange to provide relevant and timely context in a large-scale IoT ecosystem. In this paper, we argue that caching all transient context information to satisfy this necessity requires large amounts of computational and network resources, resulting in tremendous operational costs. Using Service Level Agreements (SLAs) between the context providers, CMP, and context consumers, where the level of service imperfection is quantified and linked to the associated costs, we show that it is possible to find efficient caching and prefetching strategies to minimize the context management cost. So, this paper proposes a novel method to find the optimal rate of IoT data prefetching and caching. We show the main context caching strategies and the proposed mathematical models, then discuss how a correctly chosen proactive caching strategy and configurations can help to maximise the profit of CMP operation when multiple SLAs are defined. Our model is accurate up to 0.0016 in Root Mean Square Percentage Error against our simulation results when estimating the profits to the system. We also show our model is valid using the t-test value tending to 0 for all the experimental scenarios.

Effectiveness of plant-mediated synthesis of hydroxyapatite nano-particles impregnated in Pistachio oleogum resin on mineral contents of human teeth. An in-situ single-blind controlled study.

OBJECTIVES: This study aimed to synthesize and characterize an environmentally friendly nanohydroxyapatite (n-HA) and evaluate its impact on enamel mineral content when incorporated into a Pistachio oleo gum resin (Saqqez) bio-chewing gum for in-situ models. We compared the effects of this green nano-hydroxyapatite (G n-HA) with those of a commercially available synthetic nano-hydroxyapatite (S n-HA). METHODS: Various analytical techniques were employed including XRD, FESEM, FT-IR, EDX/SEM and TGA/DTA to characterize the crystallinity, size and composition of the G n-HA powder. Three chewing gum groups were formulated: (1) Saqqez gum containing 10% wt G n-HA, (2) Saqqez gum containing 10% wt S n-HA, and (3) pure Saqqez gum. In order to evaluate the impact of these chewing gums on enamel, intraoral appliances were fabricated, each containing six enamel specimens. Participants were instructed to chew the gums while wearing these appliances. The calcium (Ca+2) and phosphorus (P) levels in enamel specimens, both with and without exposure to an acid challenge, were quantified using EDX/SEM. FE-SEM was employed to capture the microstructure of the enamel surface. In terms of the statistical analysis, one-way ANOVA and Tukey's post hoc tests were utilized to compare the data, where the significance level (α) was set at 0.05. RESULTS: The characterization tests confirmed the successful synthesis of G n-HA. Furthermore, EDX/SEM analysis of the enamel specimens from the intraoral appliance revealed significant variations in calcium (Ca+2) content among the enamel specimens (P = 0.000). The S n-HA group, in particular, exhibited the highest Ca+2 content, while the pure Saqqez group displayed the lowest. Nonetheless, there was no statistically significant differences in phosphorus (P) content observed among the three groups (P = 0.27). CONCLUSIONS: Saqqez gum can be considered a wholesome natural chewing gum that serves, as a carrier for delivering remineralization agents to the tooth surfaces. This was evident in the groups containing n-HA, exhibiting elevated Ca+2 levels. It's noteworthy that G n-HA demonstrated less efficacy in enamel remineralization compared to S n-HA.

Adaptive Context Caching for IoT-Based Applications: A Reinforcement Learning Approach.

Making internet-of-things (IoT)-based applications context-aware demands large amounts of raw data to be collected, interpreted, stored, and reused or repurposed if needed from many domains and applications. Context is transient but interpreted data can be distinguished from IoT data in many aspects. Managing context in cache is a novel area of research that has been given very little attention. Performance metric-driven adaptive context caching (ACOCA) can have a profound impact on the performance and cost efficiency of context-management platforms (CMPs) when responding to context queries in realtime. Our paper proposes an ACOCA mechanism to maximize both the cost and performance efficiency of a CMP in near realtime. Our novel mechanism encompasses the entire context-management life cycle. This, in turn, distinctively addresses the problems of efficiently selecting context for caching and managing the additional costs of context management in the cache. We demonstrate that our mechanism results in long-term efficiencies for the CMP that have not been observed in any previous study. The mechanism employs a novel, scalable, and selective context-caching agent implemented using the twin delayed deep deterministic policy gradient method. It further incorporates an adaptive context-refresh switching policy, a time-aware eviction policy, and a latent caching decision management policy. We point out in our findings that the additional complexity of adaptation introduced to the CMP through ACOCA is significantly justified, considering the cost and performance gains achieved. Our algorithm is evaluated using a real-world inspired heterogeneous context-query load and a data set based on parking-related traffic in Melbourne, Australia. This paper presents and benchmarks the proposed scheme against traditional and context-aware caching policies. We demonstrate that ACOCA outperforms the benchmarks in both cost and performance efficiency, i.e., up to 68.6%, 84.7%, and 67% more cost efficient compared to traditional data caching policies to cache context, redirector mode, and context-aware adaptive data caching under real-world-like circumstances.

Classification of skin cancer stages using a AHP fuzzy technique within the context of big data healthcare.

BACKGROUND AND OBJECTIVES: Skin conditions in humans can be challenging to diagnose. Skin cancer manifests itself without warning. In the future, these illnesses, which have been an issue for many, will be identified and treated. With the rapid expansion of big data healthcare framework summarization and precise prediction in early stage skin cancer diagnosis, the fuzzy AHP technique produces the best results in both of these fields. Big data is a potent technology that enhances the standard of research and generates better results more rapidly. This essay gives a way to group the stages of skin cancer treatment based on this information. The combination of support vector machine multi-class classification and fuzzy selector with radial basis function-based binary migration classification of virtual machines is put through a number of experiments. The connections have been categorized. ANALYSIS METHOD: These examinations have determined whether the tumors are malignant or benign and how malignant they are. The images of spots on the skin acquired from laboratory images make up the data set used for processing. We have talked about how to handle and process large datasets in the area of classification using MATLAB, like skin spot images. FINDINGS: Our technique outperforms competing approaches by maintaining stability even as the size of the data set grows rapidly and with little error. In comparison to other methods, the suggested approach meets the accuracy criterion for correct classifications with a score of 90.86%. As a result, the proposed solution is viewed as a potentially useful tool for identifying mass stages and categorizing skin cancer severity.

Automated Adjustment of PPE Masks Using IoT Sensor Fusion.

The COVID-19 pandemic has led to a dramatic increase in the use of PPE by the general public as well as health professionals. Scientists and health organizations have developed measures to protect people and minimize the catastrophic outcomes of COVID, including social distancing, frequent and periodic sanitizing, vaccinations, protective coverings, and face masks. During this time, the usage of protective face masks has increased dramatically. A mask only provides full safety to the user if it is a proper fit on their face. The aim of this paper is to automatically analyze and improve the fit of a face mask using IoT sensors. This paper describes the creation of a 3D-printed smart face mask that uses sensors to determine the current mask fit and then automatically tightens mask straps. This is evaluated using adjustment response time and the quality of fit achieved using the automatic adjustment approach with a range of sensor types.

Integration of IoT Sensors to Determine Life Expectancy of Face Masks.

Personal protective equipment (PPE) is widely used around the world to protect against environmental hazards. With the emergence of the COVID-19 virus, the use of PPE domestically has increased dramatically. People use preventive and protective mechanisms now more than ever, leading to the important question of how protective is the PPE that is being used. Face masks are highly recommended or mandatory during the time of the COVID-19 pandemic due to their protective features against aerosol droplets. However, an issue faced by many users of face masks is that they are entirely manual, with users having to decide for themselves whether their mask is still protective or if they should replace their mask. Due to the difficulty in determining this, people tend to overuse masks beyond their optimal usage. The research presented in this paper is an investigation of the viability of integrating IoT sensors into masks that are capable of collecting data to determine its usage. This paper demonstrates the usage of humidity and temperature sensors for the purpose of determining a mask's usage status based on changes in these variables when a mask is put on and taken off. An evaluation was made on the usage of the two sensors, with the conclusion that a humidity sensor provides more accurate results. From this, we present a framework that takes into consideration the factors that affect a mask's performance, such as time, humidity and temperature, to calculate the life expectancy of a mask.

Recent advances in biopolymer-based hemostatic materials.

Hemorrhage is the leading cause of trauma-related deaths, in hospital and prehospital settings. Hemostasis is a complex mechanism that involves a cascade of clotting factors and proteins that result in the formation of a strong clot. In certain surgical and emergency situations, hemostatic agents are needed to achieve faster blood coagulation to prevent the patient from experiencing a severe hemorrhagic shock. Therefore, it is critical to consider appropriate materials and designs for hemostatic agents. Many materials have been fabricated as hemostatic agents, including synthetic and naturally derived polymers. Compared to synthetic polymers, natural polymers or biopolymers, which include polysaccharides and polypeptides, have greater biocompatibility, biodegradability and processibility. Thus, in this review, we focus on biopolymer-based hemostatic agents of different forms, such as powder, particles, sponges and hydrogels. Finally, we discuss biopolymer-based hemostatic materials currently in clinical trials and offer insight into next-generation hemostats for clinical translation.

Human-induced pluripotent stem cells-derived retinal pigmented epithelium, a new horizon for cells-based therapies for age-related macular degeneration.

Retinal pigment epithelium (RPE) degeneration is the hallmark of age-related macular degeneration (AMD). AMD, as one of the most common causes of irreversible visual impairment worldwide, remains in need of an appropriate approach to restore retinal function. Wet AMD, which is characterized by neovascular formation, can be stabilized by currently available therapies, including laser photocoagulation, photodynamic therapy, and intraocular injections of anti-VEFG (anti-vascular endothelial growth factor) therapy or a combination of these modalities. Unlike wet AMD, there is no effective therapy for progressive dry (non-neovascular) AMD. However, stem cell-based therapies, a part of regenerative medicine, have shown promising results for retinal degenerative diseases such as AMD. The goal of RPE cell therapy is to return the normal structure and function of the retina by re-establishing its interaction with photoreceptors, which is essential to vision. Considering the limited source of naturally occurring RPE cells, recent progress in stem cell research has allowed the generation of RPE cells from human pluripotent cells, both embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSC). Since iPSCs face neither ethical arguments nor significant immunological considerations when compared to ESCs, they open a new horizon for cell therapy of AMD. The current study aims to discuss AMD, review the protocols for making human iPSCs-derived RPEs, and summarize recent developments in the field of iPSC-derived RPEs cell therapy.

Adoptive NK-cell transfer as a potential treatment paradigm for Wilms tumor: A preclinical study.

BACKGROUND: Natural killer (NK) cell therapy has been shown to be effective in the treatment of some cancers. However, the effects of this adoptive immunotherapy have not been investigated for Wilms tumor (WT). In this study, the effects of adoptive NK-cell transfer on a patient-derived xenograft (PDX) model of anaplastic WT were evaluated, and the impacts of cell source and ex vivo activation strategy on the therapeutic efficacy of NK-cell product were appraised. METHODS: NK cells were isolated from human peripheral blood mononuclear cells (NKPB ) and human cord blood (NKCB ), and were expanded and activated using a cytokine cocktail. Another group of NK cells (NKET ) was produced through activation with the exosomes extracted from previously challenged NKPB cells with WT. PDX-bearing mice were treated with clinically relevant doses of NKPB , NKCB , NKET , standard chemotherapy, and placebo (phosphate-buffered saline). RESULTS: PDX models treated with NKCB showed a better survival rate, though the difference among the study groups was not significant. Compared with the placebo control group, NKCB significantly improved the histopathologic response, NKPB significantly inhibited the proliferation of neoplastic cells, and NKET led to a significant decrease in the metastasis score (all p-values <.05). Standard chemotherapy provided the greatest tumor growth inhibition and the lowest mitotic count, though it did not show any significant advantage over NK-cell therapies in any of the outcome parameters in two-by-two comparisons. CONCLUSIONS: This study spotlights the efficacy of adoptive NK-cell transfer as a potential treatment candidate for high-risk WT.

Requirements, Limitations and Recommendations for Enabling End-to-End Quality of Context-Awareness in IoT Middleware.

Satisfying a context consumer's quality of context (QoC) requirements is important to context management platforms (CMPs) in order to have credibility. QoC indicates the contextual information's quality metrics (e.g., accuracy, timeliness, completeness). The outcomes of these metrics depend on the functional and quality characteristics associated with all actors (context consumers (or) context-aware applications, CMPs, and context providers (or) IoT-data providers) in context-aware IoT environments. This survey identifies and studies such characteristics and highlights the limitations in actors' current functionalities and QoC modelling approaches to obtain adequate QoC and improve context consumers' quality of experience (QoE). We propose a novel concept system based on our critical analysis; this system addresses the functional limitations in existing QoC modelling approaches. Moreover, we highlight those QoC metrics affected by quality of service (QoS) metrics in CMPs. These recommendations provide CMP developers with a reference system they could incorporate, functionalities and QoS metrics to maintain in order to deliver an adequate QoC.

An open-label phase 1 clinical trial of the allogeneic side population adipose-derived mesenchymal stem cells in SMA type 1 patients.

INTRODUCTION: Spinal muscular atrophy (SMA), an autosomal recessive neurodegenerative disorder of alpha motor neurons of spinal cord associated with progressive muscle weakness and hypotonia, is the most common genetic cause of infant mortality. Although there is few promising treatment for SMA, but the field of translational research is active in it, and stem cell-based therapy clinical trials or case studies are ongoing. Combination of different therapeutic approaches for noncurative treatments may increase their effectiveness and compliance of patients. We present a phase 1 clinical trial in patients with SMA1 who received side population adipose-derived mesenchymal stem cells (SPADMSCs). METHODS: The intervention group received three intrathecal administrations of escalating doses of SPADMSCs and followed until 24 months or the survival time. The safety analysis was assessed by controlling the side effects and efficacy evaluations performed by the Hammersmith Infant Neurological Examination (HINE), Ballard score, and electrodiagnostic (EDX) evaluation. These evaluations were performed before intervention and at the end of the follow-up. RESULTS: The treatment was safe and well tolerated, without any adverse event related to the stem cell administration. One of the patients in the intervention group was alive after 24 months of study follow-up. He is a non-sitter 62-month-old boy with appropriate weight gain and need for noninvasive ventilation (NIV) for about 8 h per day. Clinical scores, need for supportive ventilation, and number of hospitalizations were not meaningful parameters in the response of patients in the intervention and control groups. All five patients in the intervention group showed significant improvement in the motor amplitude response of the tibial nerve (0.56mV; p: 0.029). CONCLUSION: This study showed that SPADMSCs therapy is tolerable and safe with promising efficacy in SMA I. Probably same as other treatment strategies, early intervention will increase its efficacy and prepare time for more injections. We suggest EDX evaluation for the follow-up of treatment efficacy.

Situation-Aware IoT Data Generation towards Performance Evaluation of IoT Middleware Platforms.

With the increasing growth of IoT applications in various sectors (e.g., manufacturing, healthcare, etc.), we are witnessing a rising demand of IoT middleware platform that host such IoT applications. Hence, there arises a need for new methods to assess the performance of IoT middleware platforms hosting IoT applications. While there are well established methods for performance analysis and testing of databases, and some for the Big data domain, such methods are still lacking support for IoT due to the complexity, heterogeneity of IoT application and their data. To overcome these limitations, in this paper, we present a novel situation-aware IoT data generation framework, namely, SA-IoTDG. Given a majority of IoT applications are event or situation driven, we leverage a situation-based approach in SA-IoTDG for generating situation-specific data relevant to the requirements of the IoT applications. SA-IoTDG includes a situation description system, a SySML model to capture IoT application requirements and a novel Markov chain-based approach that supports transition of IoT data generation based on the corresponding situations. The proposed framework will be beneficial for both researchers and IoT application developers to generate IoT data for their application and enable them to perform initial testing before the actual deployment. We demonstrate the proposed framework using a real-world example from IoT traffic monitoring. We conduct experimental evaluations to validate the ability of SA-IoTDG to generate IoT data similar to real-world data as well as enable conducting performance evaluations of IoT applications deployed on different IoT middleware platforms using the generated data. Experimental results present some promising outcomes that validate the efficacy of SA-IoTDG. Learning and lessons learnt from the results of experiments conclude the paper.

Evaluation of Fibroblast Viability Seeded on Acellular Human Amniotic Membrane.

BACKGROUND: Investigating the viability and proliferative rates of fibroblast cells on human amniotic membrane (HAM) as a scaffold will be an important subject for further research. The aim of this study was to assess the fibroblast viability seeded on acellular HAM, since foreskin neonatal allogenic fibroblasts seeded on HAM accelerate the wound healing process. METHODS: Fibroblasts were retrieved from the foreskin of a genetically healthy male infant, and we exploited AM of healthy term neonates to prepare the amniotic scaffold for fibroblast transfer. After cell culture, preparation of acellular HAM, and seeding of cells on HAM based on the protocol, different methods including 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), 4',6-Diamidino-2-phenylindole dihydrochloride (DAPI), and propidium iodide (PI) staining were employed for assessment of fibroblast viability on HAM. RESULTS: Based on the results obtained from the DAPI and PI staining, the percentage of viable cells in the former staining was clearly higher than that of the dead cells in the latter one. The results of DAPI and PI staining were in accordance with the findings of MTT assay, confirming that fibroblasts were viable and even proliferate on HAM. CONCLUSION: Our findings showed the viability of fibroblasts seeded on the acellular HAM using MTT assay, DAPI, and PI staining; however, this study had some limitations. It would be an interesting subject for future research to compare the viability and proliferation rate of fibroblasts seeded on both cellular and acellular HAM.

Will stem cells from fat and growth factors from blood bring new hope to female patients with reproductive disorders?

Female reproductive system disorders (FRSD) with or without infertility are prevalent women's health problems with a variety of treatment approaches including surgery and hormone therapy. It currently considering to sub-branch of regenerative medicine including stem cells or growth factors injection-based delivery treatment might be improved female reproductive health life. The most common products used for these patients treatment are autologous cell or platelet-based products from patients, including platelet-rich plasma, plasma rich in growth factor, platelet-rich fibrin, and stromal vascular fraction. In this review, we discuss each of the above products used in treatment of FRSD and critically evaluate the clinical outcome.

Efficient Execution of Complex Context Queries to Enable Near Real-Time Smart IoT Applications.

As the Internet of Things (IoT) is evolving at a fast pace, the need for contextual intelligence has become more crucial for delivering IoT intelligence, efficiency, effectiveness, performance, and sustainability. Contextual intelligence enables interactions between IoT devices such as sensors/actuators, smartphones and connected vehicles, to name but a few. Context management platforms (CMP) are emerging as a promising solution to deliver contextual intelligence for IoT. However, the development of a generic solution that allows IoT devices and services to publish, consume, monitor, and share context is still in its infancy. In this paper, we propose, validate and explain the details of a novel mechanism called Context Query Engine (CQE), which is an integral part of a pioneering CMP called Context-as-a-Service (CoaaS). CQE is responsible for efficient execution of context queries in near real-time. We present the architecture of CQE and illuminate its workflows. We also conduct extensive experimental performance and scalability evaluation of the proposed CQE. Results of experimental evaluation convincingly demonstrate that CoaaS outperforms its competitors in executing complex context queries. Moreover, the advanced functionality of the embedded query language makes CoaaS a decent candidate for real-life deployments.

Context Definition and Query Language: Conceptual Specification, Implementation, and Evaluation.

As IoT grows at a staggering pace, the need for contextual intelligence is a fundamental and critical factor for IoT intelligence, efficiency, effectiveness, performance, and sustainability. As the standardisation efforts for IoT are fast progressing, efforts in standardising context management platforms led by the European Telecommunications Standards Institute (ETSI) are gaining more attention from both academic and industrial research organizations. These standardisation endeavours will enable intelligent interactions between 'things', where things could be devices, software components, web-services, or sensing/actuating systems. Therefore, having a generic platform to describe and query context is crucial for the future of IoT applications. In this paper, we propose Context Definition and Query Language (CDQL), an advanced approach that enables things to exchange, reuse and share context between each other. CDQL consists of two main parts, namely: context definition model, which is designed to describe situations and high-level context; and Context Query Language (CQL), which is a powerful and flexible query language to express contextual information requirements without considering details of the underlying data structures. An important feature of the proposed query language is its ability to query entities in IoT environments based on their situation in a fully dynamic manner where users can define situations and context entities as part of the query. We exemplify the usage of CDQL on three different smart city use cases to highlight how CDQL can be utilised to deliver contextual information to IoT applications. Performance evaluation has demonstrated scalability and efficiency of CDQL in handling a fairly large number of concurrent context queries.

Overexpression of SMN2 Gene in Motoneuron-Like Cells Differentiated from Adipose-Derived Mesenchymal Stem Cells by Ponasterone A.

Cell therapy and stem cell transplantation strategies have provided potential therapeutic approaches for the treatment of neurological disorders. Adipose-derived mesenchymal stem cells (ADMSCs) are abundant adult stem cells with low immunogenicity, which can be used for allogeneic cell replacement therapies. Differentiation of ADMSCs into acetylcholine-secreting motoneurons (MNs) is a promising treatment for MN diseases, such as spinal muscular atrophy (SMA), which is associated with the level of SMN1 gene expression. The SMN2 gene plays an important role in MN disorders, as it can somewhat compensate for the lack of SMN1 expression in SMA patients. Although the differentiation potential of ADMSCs into MNs has been previously established, overexpression of SMN2 gene in a shorter period with a longer survival has yet to be elucidated. Ponasterone A (PNA), an ecdysteroid hormone activating the PI3K/Akt pathway, was studied as a new steroid to promote SMN2 overexpression in MNs differentiated from ADMSCs. After induction with retinoic acid, sonic hedgehog, forskolin, and PNA, MN phenotypes were differentiated from ADMSCs, and immunochemical staining, specific for ß-tubulin, neuron-specific enolase, and choline acetyltransferase, was performed. Also, the results of real-time PCR assay indicated nestin, Pax6, Nkx2.2, Hb9, Olig2, and SMN2 expression in the differentiated cells. After 2 weeks of treatment, cultures supplemented with PNA showed a longer survival and a 1.2-fold increase in the expression of SMN2 (an overall 5.6-fold increase; *P ≤ 0.05), as confirmed by the Western blot analysis. The PNA treatment increased the levels of ChAT, Isl1, Hb9, and Nkx2 expression in MN-like cells. Our findings highlight the role of PNA in the upregulation of SMN2 genes from MSC-derived MN-like cells, which may serve as a potential candidate in cellular therapy for SMA patients.

Natural Killer Cells from the Subcutaneous Adipose Tissue Underexpress the NKp30 and NKp44 in Obese Persons and Are Less Active against Major Histocompatibility Complex Class I Non-Expressing Neoplastic Cells.

There are many types of leukocytes reside in subcutaneous adipose tissue (SAT), and among them, natural killer cells (NKs) comprise a major part. We show that the NKs that reside in the SAT (adipose tissue-derived NK cells; ADNKs) of the abdominal region found with phenotypic differences from the NKs circulating in the peripheral blood derived NK cells (PBNKs). In this survey, flow cytometry phenotyping was used to study the differences between the natural cytotoxicity receptor expression on ADNKs and PBNKs of both obese and lean persons. Also, their cytotoxicity and cytokine production patterns were evaluated. The activation experiments on isolated and expanded NKs with IL-2, IL-15, and IL-21 cytokines revealed the main population of the CD56dim within the total ADNKs of obese persons has an under-expression of NKp30 and NKp44 despite the unchanged levels of NKG2D. The data suggest the suppressive condition of the adipose tissue niche on the NKs response against sensitive major histocompatibility complex class I non-expressing neoplastic cells. As the NKs are the first line of the body's defense vs tumor formation, this change may lead to the development of transformed cells into the tumors.

NK Cell-derived Exosomes From NK Cells Previously Exposed to Neuroblastoma Cells Augment the Antitumor Activity of Cytokine-activated NK Cells.

Immune cell-derived exosomes can increase immunity against tumors. In contrast, tumor-derived exosomes can reduce the immunity and can change the tumor microenvironment to further develop and provide metastasis. These effects take place by an alteration in the innate and adaptive immune cell functions. In this experiment, we studied the natural killer (NK) cells' effectiveness on tumor cells after expansion and thereafter incubated it with exosomes. The exosomes were derived from 2 populations of NK cells: (1) naive NK cells and, (2) NK cells previously exposed to neuroblastoma (NB) cells. Moreover, we have studied the NB-derived exosomes on NK cell function. The molecular load of the characterized exosomes (by means of nanoparticle-tracking analysis, flow cytometry, scanning electron microscopy, and western blot) from NK cells exposed to the NB cell revealed their expression of natural killer cell receptors in addition to CD56, NKG2D, and KIR2DL2 receptors. These exosomes were used to treat NK cells and thereafter administered to NB tumor cells both in vitro and in vivo. Our results showed some kind of NK cells' education by the exosomes. This education from NK cells previously exposed to NB cell-derived exosomes caused efficient and greater cytotoxicity against NB tumors, but NB-derived exosomes act as tumor promoters by providing a tumor supporting niche. Hence, this method of preparing the exosomes has a dramatic effect on activation of anti-NK cells against NB cells.