Understanding the challenges to COVID-19 vaccines and treatment options, herd immunity and probability of reinfection.

Unlike pandemics in the past, the outbreak of coronavirus disease 2019 (COVID-19), which rapidly spread worldwide, was met with a different approach to control and measures implemented across affected countries. The lack of understanding of the fundamental nature of the outbreak continues to make COVID-19 challenging to manage for both healthcare practitioners and the scientific community. Challenges to vaccine development and evaluation, current therapeutic options, convalescent plasma therapy, herd immunity, and the emergence of reinfection and new variants remain the major obstacles to combating COVID-19. This review discusses these challenges in the management of COVID-19 at length and highlights the mechanisms needed to provide better understanding of this pandemic.

Experiences and perceptions of COVID-19 infection and vaccination among Palestinian refugees in Jerash camp and Jordanian citizens: a comparative cross-sectional study by face-to-face interviews.

BACKGROUND: During the COVID-19 vaccination, the access to vaccines has been unequal among countries and individuals, for example low-income countries displayed significant low levels of vaccination. Furthermore, most refugees are living in developing low-income countries which struggling to access the essential health-care services including vaccination. Thus, the objective of this study was to assess the experiences and perceptions of COVID-19 infection and vaccination among Palestine refugees in Jerash camp compared to resident Jordanian citizens. METHODS: A face-to-face interview-based comparative cross-sectional study was carried out among Palestine refugees in Jerash camp located in northern Jordan and Jordanian citizens from different cities in Jordan from October, 2021 to March, 2022. A Chi-square test was used to determine the differences in the experiences and perceptions of COVID-19 infection and vaccination between Palestinian refugees and resident Jordanian citizens. Logistic regression analysis was performed to predict factors associated with the beliefs, barriers and hesitancy towards COVID-19 vaccines. RESULTS: The total number of participants was 992, with 501 (50.5%) Palestinian refugees and 491 (49.5%) Jordanian citizens. Most participants (64.1%) who have never been tested for COVID-19 were from the refugees (P < 0.001), whereas about 80.3% of the participants tested for COVID-19 at private healthcare institutions were citizens (P < 0.001). While 70.0% of the participants who tested positive for COVID-19 (n = 303) were from the refugees (P < 0.001). Compared to the citizens, the refugees had significantly lower levels of beliefs about the safety (P = 0.008) and efficiency (P < 0.001) of COVID-19 vaccines. They also had lower rates of vaccine hesitancy (P = 0.002) and vaccine uptake (P < 0.001), and a higher rate of facing difficulties during registration for COVID-19 vaccination (P < 0.001). Furthermore, refugees have more negative attitudes toward the importance and implementation of COVID-19 precautionary activities, including wearing face masks, practicing social distancing and following proper prevention hygiene compared to citizens (P < 0.001). The regression analysis showed that gender (P < 0.001), age (P < 0.001) and level of education (P = 0.001) were significantly associated with COVID-19 vaccine hesitancy. Also, being a refugee (P < 0.001) and being a male (P = 0.012) were significantly associated with facing more difficulties upon the registration to receive a COVID-19 vaccine. CONCLUSIONS: This study showed that, compared to citizens, refugees had lower attitudes and practices toward COVID-19 infection and vaccination. They also had and a lower rate of COVID-19 vaccine hesitancy and uptake with limited access to vaccines. Government sectors and non-government organizations should implement policies and regulations to raise the awareness of refugees towards COVID-19 infection, testing, preventive measures, and the safety and efficacy of vaccines.

Comprehensive literature review of monkeypox.

The current outbreak of monkeypox (MPX) infection has emerged as a global matter of concern in the last few months. MPX is a zoonosis caused by the MPX virus (MPXV), which is one of the Orthopoxvirus species. Thus, it is similar to smallpox caused by the variola virus, and smallpox vaccines and drugs have been shown to be protective against MPX. Although MPX is not a new disease and is rarely fatal, the current multi-country MPX outbreak is unusual because it is occurring in countries that are not endemic for MPXV. In this work, we reviewed the extensive literature available on MPXV to summarize the available data on the major biological, clinical and epidemiological aspects of the virus and the important scientific findings. This review may be helpful in raising awareness of MPXV transmission, symptoms and signs, prevention and protective measures. It may also be of interest as a basis for performance of studies to further understand MPXV, with the goal of combating the current outbreak and boosting healthcare services and hygiene practices.Trial registration: ClinicalTrials.gov identifier: NCT02977715..Trial registration: ClinicalTrials.gov identifier: NCT03745131..Trial registration: ClinicalTrials.gov identifier: NCT00728689..Trial registration: ClinicalTrials.gov identifier: NCT02080767..

The Effects of Tamoxifen on Tolerogenic Cells in Cancer.

Tamoxifen (TAM) is the most prescribed selective estrogen receptor modulator (SERM) to treat hormone-receptor-positive breast cancer patients and has been used for more than 20 years. Its role as a hormone therapy is well established; however, the potential role in modulating tolerogenic cells needs to be better clarified. Infiltrating tumor-microenvironment-regulatory T cells (TME-Tregs) are important as they serve a suppressive function through the transcription factor Forkhead box P3 (Foxp3). Abundant studies have suggested that Foxp3 regulates the expression of several genes (CTLA-4, PD-1, LAG-3, TIM-3, TIGIT, TNFR2) involved in carcinogenesis to utilize its tumor suppressor function through knockout models. TAM is indirectly concomitant via the Cre/loxP system by allowing nuclear translocation of the fusion protein, excision of the floxed STOP cassette and heritable expression of encoding fluorescent protein in a cohort of cells that express Foxp3. Moreover, TAM administration in breast cancer treatment has shown its effects directly through MDSCs by the enrichment of its leukocyte populations, such as NK and NKT cells, while it impairs the differentiation and activation of DCs. However, the fundamental mechanisms of the reduction of this pool by TAM are unknown. Here, we review the vital effects of TAM on Tregs for a precise mechanistic understanding of cancer immunotherapies.

Immunomodulatory Properties of Human Breast Milk: MicroRNA Contents and Potential Epigenetic Effects.

Infants who are exclusively breastfed in the first six months of age receive adequate nutrients, achieving optimal immune protection and growth. In addition to the known nutritional components of human breast milk (HBM), i.e., water, carbohydrates, fats and proteins, it is also a rich source of microRNAs, which impact epigenetic mechanisms. This comprehensive work presents an up-to-date overview of the immunomodulatory constituents of HBM, highlighting its content of circulating microRNAs. The epigenetic effects of HBM are discussed, especially those regulated by miRNAs. HBM contains more than 1400 microRNAs. The majority of these microRNAs originate from the lactating gland and are based on the remodeling of cells in the gland during breastfeeding. These miRNAs can affect epigenetic patterns by several mechanisms, including DNA methylation, histone modifications and RNA regulation, which could ultimately result in alterations in gene expressions. Therefore, the unique microRNA profile of HBM, including exosomal microRNAs, is implicated in the regulation of the genes responsible for a variety of immunological and physiological functions, such as FTO, INS, IGF1, NRF2, GLUT1 and FOXP3 genes. Hence, studying the HBM miRNA composition is important for improving the nutritional approaches for pregnancy and infant's early life and preventing diseases that could occur in the future. Interestingly, the composition of miRNAs in HBM is affected by multiple factors, including diet, environmental and genetic factors.

Applications of Alginate-Based Nanomaterials in Enhancing the Therapeutic Effects of Bee Products.

Since the ancient times, bee products (i.e., honey, propolis, pollen, bee venom, bee bread, and royal jelly) have been considered as natural remedies with therapeutic effects against a number of diseases. The therapeutic pleiotropy of bee products is due to their diverse composition and chemical properties, which is independent on the bee species. This has encouraged researchers to extensively study the therapeutic potentials of these products, especially honey. On the other hand, amid the unprecedented growth in nanotechnology research and applications, nanomaterials with various characteristics have been utilized to improve the therapeutic efficiency of these products. Towards keeping the bee products as natural and non-toxic therapeutics, the green synthesis of nanocarriers loaded with these products or their extracts has received a special attention. Alginate is a naturally produced biopolymer derived from brown algae, the desirable properties of which include biodegradability, biocompatibility, non-toxicity and non-immunogenicity. This review presents an overview of alginates, including their properties, nanoformulations, and pharmaceutical applications, placing a particular emphasis on their applications for the enhancement of the therapeutic effects of bee products. Despite the paucity of studies on fabrication of alginate-based nanomaterials loaded with bee products or their extracts, recent advances in the area of utilizing alginate-based nanomaterials and other types of materials to enhance the therapeutic potentials of bee products are summarized in this work. As the most widespread and well-studied bee products, honey and propolis have garnered a special interest; combining them with alginate-based nanomaterials has led to promising findings, especially for wound healing and skin tissue engineering. Furthermore, future directions are proposed and discussed to encourage researchers to develop alginate-based stingless bee product nanomedicines, and to help in selecting suitable methods for devising nanoformulations based on multi-criteria decision making models. Also, the commercialization prospects of nanocomposites based on alginates and bee products are discussed. In conclusion, preserving original characteristics of the bee products is a critical challenge in developing nano-carrier systems. Alginate-based nanomaterials are well suited for this task because they can be fabricated without the use of harsh conditions, such as shear force and freeze-drying, which are often used for other nano-carriers. Further, conjunction of alginates with natural polymers such as honey does not only combine the medicinal properties of alginates and honey, but it could also enhance the mechanical properties and cell adhesion capacity of alginates.

Reported Adverse Effects and Attitudes among Arab Populations Following COVID-19 Vaccination: A Large-Scale Multinational Study Implementing Machine Learning Tools in Predicting Post-Vaccination Adverse Effects Based on Predisposing Factors.

Background: The unprecedented global spread of coronavirus disease 2019 (COVID-19) has imposed huge challenges on the healthcare facilities, and impacted every aspect of life. This has led to the development of several vaccines against COVID-19 within one year. This study aimed to assess the attitudes and the side effects among Arab communities after receiving a COVID-19 vaccine and use of machine learning (ML) tools to predict post-vaccination side effects based on predisposing factors. Methods: An online-based multinational survey was carried out via social media platforms from 14 June to 31 August 2021, targeting individuals who received at least one dose of a COVID-19 vaccine from 22 Arab countries. Descriptive statistics, correlation, and chi-square tests were used to analyze the data. Moreover, extensive ML tools were utilized to predict 30 post vaccination adverse effects and their severity based on 15 predisposing factors. The importance of distinct predisposing factors in predicting particular side effects was determined using global feature importance employing gradient boost as AutoML. Results: A total of 10,064 participants from 19 Arab countries were included in this study. Around 56% were female and 59% were aged from 20 to 39 years old. A high rate of vaccine hesitancy (51%) was reported among participants. Almost 88% of the participants were vaccinated with one of three COVID-19 vaccines, including Pfizer-BioNTech (52.8%), AstraZeneca (20.7%), and Sinopharm (14.2%). About 72% of participants experienced post-vaccination side effects. This study reports statistically significant associations (p < 0.01) between various predisposing factors and post-vaccinations side effects. In terms of predicting post-vaccination side effects, gradient boost, random forest, and XGBoost outperformed other ML methods. The most important predisposing factors for predicting certain side effects (i.e., tiredness, fever, headache, injection site pain and swelling, myalgia, and sleepiness and laziness) were revealed to be the number of doses, gender, type of vaccine, age, and hesitancy to receive a COVID-19 vaccine. Conclusions: The reported side effects following COVID-19 vaccination among Arab populations are usually non-life-threatening; flu-like symptoms and injection site pain. Certain predisposing factors have greater weight and importance as input data in predicting post-vaccination side effects. Based on the most significant input data, ML can also be used to predict these side effects; people with certain predicted side effects may require additional medical attention, or possibly hospitalization.

Nucleic Acid-Based COVID-19 Therapy Targeting Cytokine Storms: Strategies to Quell the Storm.

Coronavirus disease 2019 (COVID-19) has shaken the world and triggered drastic changes in our lifestyle to control it. Despite the non-typical efforts, COVID-19 still thrives and plagues humanity worldwide. The unparalleled degree of infection has been met with an exceptional degree of research to counteract it. Many drugs and therapeutic technologies have been repurposed and discovered, but no groundbreaking antiviral agent has been introduced yet to eradicate COVID-19 and restore normalcy. As lethality is directly correlated with the severity of disease, hospitalized severe cases are of the greatest importance to reduce, especially the cytokine storm phenomenon. This severe inflammatory phenomenon characterized by elevated levels of inflammatory mediators can be targeted to relieve symptoms and save the infected patients. One of the promising therapeutic strategies to combat COVID-19 is nucleic acid-based therapeutic approaches, including microRNAs (miRNAs). This work is an up-to-date review aimed to comprehensively discuss the current nucleic acid-based therapeutics against COVID-19 and their mechanisms of action, taking into consideration the emerging SARS-CoV-2 variants of concern, as well as providing potential future directions. miRNAs can be used to run interference with the expression of viral proteins, while endogenous miRNAs can be targeted as well, offering a versatile platform to control SARS-CoV-2 infection. By targeting these miRNAs, the COVID-19-induced cytokine storm can be suppressed. Therefore, nucleic acid-based therapeutics (miRNAs included) have a latent ability to break the COVID-19 infection in general and quell the cytokine storm in particular.

Investigating the association of CD36 gene polymorphisms (rs1761667 and rs1527483) with T2DM and dyslipidemia: Statistical analysis, machine learning based prediction, and meta-analysis.

CD36 (cluster of differentiation 36) is a membrane protein involved in lipid metabolism and has been linked to pathological conditions associated with metabolic disorders, such as diabetes and dyslipidemia. A case-control study was conducted and included 177 patients with type-2 diabetes mellitus (T2DM) and 173 control subjects to study the involvement of CD36 gene rs1761667 (G>A) and rs1527483 (C>T) polymorphisms in the pathogenesis of T2DM and dyslipidemia among Jordanian population. Lipid profile, blood sugar, gender and age were measured and recorded. Also, genotyping analysis for both polymorphisms was performed. Following statistical analysis, 10 different neural networks and machine learning (ML) tools were used to predict subjects with diabetes or dyslipidemia. Towards further understanding of the role of CD36 protein and gene in T2DM and dyslipidemia, a protein-protein interaction network and meta-analysis were carried out. For both polymorphisms, the genotypic frequencies were not significantly different between the two groups (p > 0.05). On the other hand, some ML tools like multilayer perceptron gave high prediction accuracy (≥ 0.75) and Cohen's kappa (κ) (≥ 0.5). Interestingly, in K-star tool, the accuracy and Cohen's κ values were enhanced by including the genotyping results as inputs (0.73 and 0.46, respectively, compared to 0.67 and 0.34 without including them). This study confirmed, for the first time, that there is no association between CD36 polymorphisms and T2DM or dyslipidemia among Jordanian population. Prediction of T2DM and dyslipidemia, using these extensive ML tools and based on such input data, is a promising approach for developing diagnostic and prognostic prediction models for a wide spectrum of diseases, especially based on large medical databases.

The role of TNFR2+ Tregs in COVID-19: An overview and a potential therapeutic strategy.

COVID-19 is a multi-faceted disease ranging from asymptomatic to severely ill condition that primarily affects the lungs and could advance to other organs as well. It's causing factor, SARS-CoV-2 is recognized to develop robust cell-mediated immunity that responsible to either control or exaggerate the infection. As an important cell subset that control immune responses and are significantly dysregulated in COVID-19, Tregs is proposed to be considered for COVID-19 management. Among its hallmark, TNFR2 is recently recognized to play important role in the function and survival of Tregs. This review gathers available TNFR2 agonists to directly target Tregs as a potential approach to overcome immune dysregulation that affect the severity in COVID-19. Furthermore, this review performs a rigid body docking of TNF-TNFR2 interaction and such interaction with TNFR2 agonist to predict the optimal targeting approach.

Targeting immunosuppressor cells with nanoparticles in autoimmunity: How far have we come to?

Autoimmunity is the assault of immune response towards self-antigens, resulting to inflammation and tissue injury. It is staged into three phases and caused by malfunction of immune tolerance. In our body, immune tolerance is synchronized by several immunosuppressor cells such as regulatory T cells and B cells as well as myeloid-derived suppressor cells, which are prominently dysregulated in autoimmunity. Hence, targeting these cell populations serve as a significant potential in the therapy of autoimmunity. Nanotechnology with its advantageous properties is shown to be a remarkable tool as drug delivery system in this field. This review focused on the development of therapeutics in autoimmune diseases utilizing various nanoparticles formulation based on two targeting approaches in autoimmunity, passive and active targeting. Lastly, this review outlined the approved present nanomedicines as well as in clinical evaluations and issues regarding the lack of translation of these nanomedicines into the market, despite the abundant of positive experimental observations.

Side Effects and Perceptions Following COVID-19 Vaccination in Jordan: A Randomized, Cross-Sectional Study Implementing Machine Learning for Predicting Severity of Side Effects.

BACKGROUND: Since the coronavirus disease 2019 (COVID-19) was declared a pandemic, there was no doubt that vaccination is the ideal protocol to tackle it. Within a year, a few COVID-19 vaccines have been developed and authorized. This unparalleled initiative in developing vaccines created many uncertainties looming around the efficacy and safety of these vaccines. This study aimed to assess the side effects and perceptions following COVID-19 vaccination in Jordan. METHODS: A cross-sectional study was conducted by distributing an online survey targeted toward Jordan inhabitants who received any COVID-19 vaccines. Data were statistically analyzed and certain machine learning (ML) tools, including multilayer perceptron (MLP), eXtreme gradient boosting (XGBoost), random forest (RF), and K-star were used to predict the severity of side effects. RESULTS: A total of 2213 participants were involved in the study after receiving Sinopharm, AstraZeneca, Pfizer-BioNTech, and other vaccines (38.2%, 31%, 27.3%, and 3.5%, respectively). Generally, most of the post-vaccination side effects were common and non-life-threatening (e.g., fatigue, chills, dizziness, fever, headache, joint pain, and myalgia). Only 10% of participants suffered from severe side effects; while 39% and 21% of participants had moderate and mild side effects, respectively. Despite the substantial variations between these vaccines in the presence and severity of side effects, the statistical analysis indicated that these vaccines might provide the same protection against COVID-19 infection. Finally, around 52.9% of participants suffered before vaccination from vaccine hesitancy and anxiety; while after vaccination, 95.5% of participants have advised others to get vaccinated, 80% felt more reassured, and 67% believed that COVID-19 vaccines are safe in the long term. Furthermore, based on the type of vaccine, demographic data, and side effects, the RF, XGBoost, and MLP gave both high accuracies (0.80, 0.79, and 0.70, respectively) and Cohen's kappa values (0.71, 0.70, and 0.56, respectively). CONCLUSIONS: The present study confirmed that the authorized COVID-19 vaccines are safe and getting vaccinated makes people more reassured. Most of the post-vaccination side effects are mild to moderate, which are signs that body's immune system is building protection. ML can also be used to predict the severity of side effects based on the input data; predicted severe cases may require more medical attention or even hospitalization.

COVID-19 infection and nanomedicine applications for development of vaccines and therapeutics: An overview and future perspectives based on polymersomes.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which emerged in December 2019 and caused the coronavirus disease 2019 (COVID-19) pandemic, took the world by surprise with an unprecedented public health emergency. Since this pandemic began, extraordinary efforts have been made by scientists to understand the pathogenesis of COVID-19, and to fight the infection by providing various preventive, diagnostic and treatment opportunities based on either novel hypotheses or past experiences. Despite all the achievements, COVID-19 continues to be an accelerating health threat with no specifically approved vaccine or therapy. This review highlights the recent advances in COVID-19 infection, with a particular emphasis on nanomedicine applications that can help in the development of effective vaccines or therapeutics against COVID-19. A novel future perspective has been proposed in this review based on utilizing polymersome nano-objects for effectively suppressing the cytokine storm, which may reduce the severity of COVID-19 infection.

Comprehensive Structural and Molecular Comparison of Spike Proteins of SARS-CoV-2, SARS-CoV and MERS-CoV, and Their Interactions with ACE2.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has recently emerged in China and caused a disease called coronavirus disease 2019 (COVID-19). The virus quickly spread around the world, causing a sustained global outbreak. Although SARS-CoV-2, and other coronaviruses, SARS-CoV and Middle East respiratory syndrome CoV (MERS-CoV) are highly similar genetically and at the protein production level, there are significant differences between them. Research has shown that the structural spike (S) protein plays an important role in the evolution and transmission of SARS-CoV-2. So far, studies have shown that various genes encoding primarily for elements of S protein undergo frequent mutation. We have performed an in-depth review of the literature covering the structural and mutational aspects of S protein in the context of SARS-CoV-2, and compared them with those of SARS-CoV and MERS-CoV. Our analytical approach consisted in an initial genome and transcriptome analysis, followed by primary, secondary and tertiary protein structure analysis. Additionally, we investigated the potential effects of these differences on the S protein binding and interactions to angiotensin-converting enzyme 2 (ACE2), and we established, after extensive analysis of previous research articles, that SARS-CoV-2 and SARS-CoV use different ends/regions in S protein receptor-binding motif (RBM) and different types of interactions for their chief binding with ACE2. These differences may have significant implications on pathogenesis, entry and ability to infect intermediate hosts for these coronaviruses. This review comprehensively addresses in detail the variations in S protein, its receptor-binding characteristics and detailed structural interactions, the process of cleavage involved in priming, as well as other differences between coronaviruses.

Antiviral and Immunomodulatory Effects of Phytochemicals from Honey against COVID-19: Potential Mechanisms of Action and Future Directions.

The new coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has recently put the world under stress, resulting in a global pandemic. Currently, there are no approved treatments or vaccines, and this severe respiratory illness has cost many lives. Despite the established antimicrobial and immune-boosting potency described for honey, to date there is still a lack of evidence about its potential role amid COVID-19 outbreak. Based on the previously explored antiviral effects and phytochemical components of honey, we review here evidence for its role as a potentially effective natural product against COVID-19. Although some bioactive compounds in honey have shown potential antiviral effects (i.e., methylglyoxal, chrysin, caffeic acid, galangin and hesperidinin) or enhancing antiviral immune responses (i.e., levan and ascorbic acid), the mechanisms of action for these compounds are still ambiguous. To the best of our knowledge, this is the first work exclusively summarizing all these bioactive compounds with their probable mechanisms of action as antiviral agents, specifically against SARS-CoV-2.

Artificial Neural Networks Model for Predicting Type 2 Diabetes Mellitus Based on VDR Gene FokI Polymorphism, Lipid Profile and Demographic Data.

Type 2 diabetes mellitus (T2DM) is a multifactorial disease associated with many genetic polymorphisms; among them is the FokI polymorphism in the vitamin D receptor (VDR) gene. In this case-control study, samples from 82 T2DM patients and 82 healthy controls were examined to investigate the association of the FokI polymorphism and lipid profile with T2DM in the Jordanian population. DNA was extracted from blood and genotyped for the FokI polymorphism by polymerase chain reaction (PCR) and DNA sequencing. Lipid profile and fasting blood sugar were also measured. There were significant differences in high-density lipoprotein (HDL) cholesterol and triglyceride levels between T2DM and control samples. Frequencies of the FokI polymorphism (CC, CT and TT) were determined in T2DM and control samples and were not significantly different. Furthermore, there was no significant association between the FokI polymorphism and T2DM or lipid profile. A feed-forward neural network (FNN) was used as a computational platform to predict the persons with diabetes based on the FokI polymorphism, lipid profile, gender and age. The accuracy of prediction reached 88% when all parameters were included, 81% when the FokI polymorphism was excluded, and 72% when lipids were only included. This is the first study investigating the association of the VDR gene FokI polymorphism with T2DM in the Jordanian population, and it showed negative association. Diabetes was predicted with high accuracy based on medical data using an FNN. This highlights the great value of incorporating neural network tools into large medical databases and the ability to predict patient susceptibility to diabetes.

A profile of TNFR2+ regulatory T cells and CD103+ dendritic cells in the peripheral blood of patients with asthma.

The interaction of tolerogenic CD103+ dendritic cells (DCs) with regulatory T (Tregs) cells modulates immune responses by inducing immune tolerance. Hence, we determined the proportion of these cells in the peripheral blood mononuclear cells (PBMC) of asthmatic patients. We observed lower trends of CD11b-CD103+ DCs and CD86 within CD11b-CD103+ DCs, while increased levels of Foxp3 expressing CD25+/-TNFR2+ cells in asthmatics. There was a positive correlation in the expression of Foxp3 within CD3+CD4+CD25+TNFR2+ Tregs and CD11b-CD103+ as well as the expression of CD86 within HLA-DR+CD11c+CD11b-CD103+ DCs. In conclusion, we suggest that the increased levels of Tregs in blood could continuously suppress the T helper 2 (Th2) cells activation in the circulation which is also supported by the increase of anti-inflammatory cytokines IL-10 and TNF. Overall, functional immunoregulation of the regulatory cells, particularly Tregs, exhibit immune suppression and induce immune tolerance linked with the immune activation by the antigen presenting cells (APC).

Laboratory Diagnosis of Paratyphoid Fever: Opportunity of Surface Plasmon Resonance.

Paratyphoid fever is caused by the bacterium Salmonella enterica serovar Paratyphi (A, B and C), and contributes significantly to global disease burden. One of the major challenges in the diagnosis of paratyphoid fever is the lack of a proper gold standard. Given the absence of a licensed vaccine against S. Paratyphi, this diagnostic gap leads to inappropriate antibiotics use, thus, enhancing antimicrobial resistance. In addition, the symptoms of paratyphoid overlap with other infections, including the closely related typhoid fever. Since the development and utilization of a standard, sensitive, and accurate diagnostic method is essential in controlling any disease, this review discusses a new promising approach to aid the diagnosis of paratyphoid fever. This advocated approach is based on the use of surface plasmon resonance (SPR) biosensor and DNA probes to detect specific nucleic acid sequences of S. Paratyphi. We believe that this SPR-based genoassay can be a potent alternative to the current conventional diagnostic methods, and could become a rapid diagnostic tool for paratyphoid fever.

Antioxidant-Based Medicinal Properties of Stingless Bee Products: Recent Progress and Future Directions.

Stingless bees are a type of honey producers that commonly live in tropical countries. Their use for honey is being abandoned due to its limited production. However, the recent improvements in stingless bee honey production, particularly in South East Asia, have brought stingless bee products back into the picture. Although there are many stingless bee species that produce a wide spread of products, known since old eras in traditional medicine, the modern medical community is still missing more investigational studies on stingless bee products. Whereas comprehensive studies in the current era attest to the biological and medicinal properties of honeybee (Apis mellifera) products, the properties of stingless bee products are less known. This review highlights for the first time the medicinal benefits of stingless bee products (honey, propolis, pollen and cerumen), recent investigations and promising future directions. This review emphasizes the potential antioxidant properties of these products that in turn play a vital role in preventing and treating diseases associated with oxidative stress, microbial infections and inflammatory disorders. Summarizing all these data and insights in one manuscript may increase the commercial value of stingless bee products as a food ingredient. This review will also highlight the utility of stingless bee products in the context of medicinal and therapeutic properties, some of which are yet to be discovered.

Biomarkers for Temporomandibular Disorders: Current Status and Future Directions.

Numerous studies have been conducted in the previous years with an objective to determine the ideal biomarker or set of biomarkers in temporomandibular disorders (TMDs). It was recorded that tumour necrosis factor (TNF), interleukin 8 (IL-8), IL-6, and IL-1 were the most common biomarkers of TMDs. As of recently, although the research on TMDs biomarkers still aims to find more diagnostic agents, no recent study employs the biomarker as a targeting point of pharmacotherapy to suppress the inflammatory responses. This article represents an explicit review on the biomarkers of TMDs that have been discovered so far and provides possible future directions towards further research on these biomarkers. The potential implementation of the interactions of TNF with its receptor 2 (TNFR2) in the inflammatory process has been interpreted, and thus, this review presents a new hypothesis towards suppression of the inflammatory response using TNFR2-agonist. Subsequently, this hypothesis could be explored as a potential pain elimination approach in patients with TMDs.