Hasil untuk "Infectious and parasitic diseases"

S. Mukherjee, S. Huda, S. P. Sinha Babu

Immunopolymorphism is considered as an important aspect behind the resistance or susceptibility of the host to an infectious disease. Over the years, researchers have explored many genetic factors for their role in immune surveillance against infectious diseases. Polymorphic characters in the gene encoding Toll‐like receptors (TLRs) play profound roles in inducing differential immune responses by the host against parasitic infections. Protein(s) encoded by TLR gene(s) are immensely important due to their ability of recognizing different types of pathogen associated molecular patterns (PAMPs). This study reviews the polymorphic residues present in the nucleotide or in the amino acid sequence of TLRs and their influence on alteration of inflammatory signalling pathways promoting either susceptibility or resistance to major infectious diseases, including tuberculosis, leishmaniasis, malaria and filariasis. Population‐based studies exploring TLR polymorphisms in humans are primarily emphasized to discuss the association of the polymorphic residues with the occurrence and epidemiology of the mentioned infectious diseases. Principal polymorphic residues in TLRs influencing immunity to infection are mostly single nucleotide polymorphisms (SNPs). I602S (TLR1), R677W (TLR2), P554S (TLR3), D299G (TLR4), F616L (TLR5), S249P (TLR6), Q11L (TLR7), M1V (TLR8), G1174A (TLR9) and G1031T (TLR10) are presented as the major influential SNPs in shaping immunity to pathogenic infections. The contribution of these SNPs in the structure‐function relationship of TLRs is yet not clear. Therefore, molecular studies on such polymorphisms can improve our understanding on the genetic basis of the immune response and pave the way for therapeutic intervention in a more feasible way.

Anastasia Lam, Yana C Vierboom, Jessica S West

Background Objective measurements estimated that 1.57 billion people globally had hearing loss in 2019. However, where audiologists are sparse, self-reported measures have been suggested as alternatives to assess burden. Moreover, research suggests this number varies by gender, due to biological and social mechanisms. Further refining our knowledge of the global prevalence of hearing loss will provide better understanding of which groups are most affected and how to best allocate resources.Methods Using Gateway to Global Ageing data and the South African National Income Dynamics Study, we estimated the prevalence and men:women ratio of self-reported hearing loss and hearing aid use for 28 countries. Hearing loss was measured as having fair/poor hearing or reporting hearing aid use. We included 664 580 observations of individuals aged 50+ years.Results We found that the four countries with the highest levels of hearing loss (China 65%, South Korea 39%, Mexico 33%, Brazil 31%) also had the lowest reported hearing aid use (as low as 1% in China). Though men were more likely than women to report hearing loss in nearly all countries, especially in regions with higher hearing aid use (USA, Northern/Western Europe), China, South Korea and South Africa reported no gender difference. As the prevalence of hearing loss and hearing aid use increased with age, gender differences generally decreased.Conclusion International variation underscores the importance of country context in shaping perceived hearing and hearing aid use. Regions with high levels of hearing loss and low hearing aid use may be especially amenable to interventions.

Gustavo A. Sousa, Diogo L. M. Souza, Enrique C. Gabrick et al.

The study of infectious disease propagation is essential for understanding and controlling epidemics. One of the most useful tools for gaining insights into the spread of infectious diseases is mathematical modelling. In terms of mathematical epidemiology, the main models are based on compartments, such as SI, SIR, and SEIR. These models offer mathematical frameworks for representing the proliferation dynamics of various diseases, for instance flu and smallpox. In this work, we explore these models using two distinct mathematical approaches, Cellular Automata (CA) and ODEs. They are able to reproduce the spread dynamics of diseases with their own individuality. CA models incorporate the local interaction among individuals with discrete time and space, while ODEs provide a continuous and simplified view of a disease propagation in large and homogeneous populations. By comparing these two approaches, we find that the shape of the curves of all models is similar for both representations. Although, the growth rates differ between CA and ODE. One of our results is to show that the CA yields a power-law growth, while the ODE growth rate is well-represented by an exponential function. Furthermore, a substantial contribution of our work is using a hyperbolic tangent to fit the initial growth of infected individuals for all the considered models. Our results display a strong correlation between simulated data and adjusted function. We mainly address this successful result by the fact that the hyperbolic function captures both growing: the power-law (when considered the first terms of infinite sums) and combinations of exponential (when the hyperbolic function is written via exponential). Therefore, our work shows that when modelling a disease the choice of mathematical representation is crucial, in particular to model the onset of an epidemic.

Ayesha Baig, Li Zhouxin

As global living standards improve and medical technology advances, many infectious diseases have been effectively controlled. However, certain diseases, such as the recent COVID-19 pandemic, continue to pose significant threats to public health. This paper explores the evolution of infectious disease modeling, from early ordinary differential equation-based models like the SIR framework to more complex reaction-diffusion models that incorporate both temporal and spatial dynamics. The study highlights the importance of numerical methods, such as the Runge-Kutta method, implicit-explicit time-discretization techniques, and finite difference methods, in solving these models. By analyzing the development and application of these methods, this research underscores their critical role in predicting disease spread, informing public health strategies, and mitigating the impact of future pandemics.

Li Guo, M. Rondina

Platelets are anucleate cells produced by megakaryocytes. In recent years, a robust body of literature supports the evolving role of platelets as key sentinel and effector cells in infectious diseases, especially critical in bridging hemostatic, inflammatory, and immune continuums. Upon intravascular pathogen invasion, platelets can directly sense viral, parasitic, and bacterial infections through pattern recognition receptors and integrin receptors or pathogen: immunoglobulin complexes through Fc and complement receptors—although our understanding of these interactions remains incomplete. Constantly scanning for areas of injury or inflammation as they circulate in the vasculature, platelets also indirectly respond to pathogen invasion through interactions with leukocytes and the endothelium. Following antigen recognition, platelets often become activated. Through a diverse repertoire of mechanisms, activated platelets can directly sequester or kill pathogens, or facilitate pathogen clearance by activating macrophages and neutrophils, promoting neutrophil extracellular traps (NETs) formation, forming platelet aggregates and microthrombi. At times, however, platelet activation may also be injurious to the host, exacerbating inflammation and promoting endothelial damage and thrombosis. There are many gaps in our understandings of the role of platelets in infectious diseases. However, with the emergence of advanced technologies, our knowledge is increasing. In the current review, we mainly discuss these evolving roles of platelets under four different infectious pathogen infections, of which are dengue, malaria, Esterichia coli (E. coli) and staphylococcus aureus S. aureus, highlighting the complex interplay of these processes with hemostatic and thrombotic pathways.

Hansong Zhu, Si Chen, Weixia Qin et al.

Abstract Objective At different times, public health faces various challenges and the degree of intervention measures varies. The research on the impact and prediction of meteorology factors on influenza is increasing gradually, however, there is currently no evidence on whether its research results are affected by different periods. This study aims to provide limited evidence to reveal this issue. Methods Daily data on influencing factors and influenza in Xiamen were divided into three parts: overall period (phase AB), non-COVID-19 epidemic period (phase A), and COVID-19 epidemic period (phase B). The association between influencing factors and influenza was analysed using generalized additive models (GAMs). The excess risk (ER) was used to represent the percentage change in influenza as the interquartile interval (IQR) of meteorology factors increases. The 7-day average daily influenza cases were predicted using the combination of bi-directional long short memory (Bi-LSTM) and random forest (RF) through multi-step rolling input of the daily multifactor values of the previous 7-day. Results In periods A and AB, air temperature below 22 °C was a risk factor for influenza. However, in phase B, temperature showed a U-shaped effect on it. Relative humidity had a more significant cumulative effect on influenza in phase AB than in phase A (peak: accumulate 14d, AB: ER = 281.54, 95% CI = 245.47 ~ 321.37; A: ER = 120.48, 95% CI = 100.37 ~ 142.60). Compared to other age groups, children aged 4–12 were more affected by pressure, precipitation, sunshine, and day light, while those aged ≥ 13 were more affected by the accumulation of humidity over multiple days. The accuracy of predicting influenza was highest in phase A and lowest in phase B. Conclusions The varying degrees of intervention measures adopted during different phases led to significant differences in the impact of meteorology factors on influenza and in the influenza prediction. In association studies of respiratory infectious diseases, especially influenza, and environmental factors, it is advisable to exclude periods with more external interventions to reduce interference with environmental factors and influenza related research, or to refine the model to accommodate the alterations brought about by intervention measures. In addition, the RF-Bi-LSTM model has good predictive performance for influenza.

Nils Wetzstein, Margo Diricks, Thomas B. Anton et al.

Abstract Background The Mycobacterium avium complex (MAC) comprises the most frequent non-tuberculous mycobacteria (NTM) in Central Europe and currently includes twelve species. M. avium (MAV), M. intracellulare subsp. intracellulare (MINT), and M. intracellulare subsp. chimaera (MCH) are clinically most relevant. However, the population structure and genomic landscape of MAC linked with potential pathobiological differences remain little investigated. Methods Whole genome sequencing (WGS) was performed on a multi-national set of MAC isolates from Germany, France, and Switzerland. Phylogenetic analysis was conducted, as well as plasmids, resistance, and virulence genes predicted from WGS data. Data was set into a global context with publicly available sequences. Finally, detailed clinical characteristics were associated with genomic data in a subset of the cohort. Results Overall, 610 isolates from 465 patients were included. The majority could be assigned to MAV (n = 386), MCH (n = 111), and MINT (n = 77). We demonstrate clustering with less than 12 SNPs distance of isolates obtained from different patients in all major MAC species and the identification of trans-European or even trans-continental clusters when set into relation with 1307 public sequences. However, none of our MCH isolates clustered closely with the heater-cooler unit outbreak strain Zuerich-1. Known plasmids were detected in MAV (325/1076, 30.2%), MINT (62/327, 19.0%), and almost all MCH-isolates (457/463, 98.7%). Predicted resistance to aminoglycosides or macrolides was rare. Overall, there was no direct link between phylogenomic grouping and clinical manifestations, but MCH and MINT were rarely found in patients with extra-pulmonary disease (OR 0.12 95% CI 0.04–0.28, p < 0.001 and OR 0.11 95% CI 0.02–0.4, p = 0.004, respectively) and MCH was negatively associated with fulfillment of the ATS criteria when isolated from respiratory samples (OR 0.28 95% CI 0.09-0.7, p = 0.011). With 14 out of 43 patients with available serial isolates, co-infections or co-colonizations with different strains or even species of the MAC were frequent (32.6%). Conclusions This study demonstrates clustering and the presence of plasmids in a large proportion of MAC isolates in Europe and in a global context. Future studies need to urgently define potential ways of transmission of MAC isolates and the potential involvement of plasmids in virulence.

Yuan Yin, Jennifer A. Flegg, Mark B. Flegg

In the infectious disease literature, significant effort has been devoted to studying dynamics at a single scale. For example, compartmental models describing population-level dynamics are often formulated using differential equations. In cases where small numbers or noise play a crucial role, these differential equations are replaced with memoryless Markovian models, where discrete individuals can be members of a compartment and transition stochastically. Classic stochastic simulation algorithms, such as the next reaction method, can be employed to solve these Markovian models exactly. The intricate coupling between models at different scales underscores the importance of multiscale modelling in infectious diseases. However, several computational challenges arise when the multiscale model becomes non-Markovian. In this paper, we address these challenges by developing a novel exact stochastic simulation algorithm. We apply it to a showcase multiscale system where all individuals share the same deterministic within-host model while the population-level dynamics are governed by a stochastic formulation. We demonstrate that as long as the within-host information is harvested at a reasonable resolution, the novel algorithm will always be accurate. Furthermore, our implementation is still efficient even at finer resolutions. Beyond infectious disease modelling, the algorithm is widely applicable to other multiscale systems, providing a versatile, accurate, and computationally efficient framework.

Pierluigi Colli, Gabriela Marinoschi, Elisabetta Rocca et al.

Partial differential equation (PDE) models for infectious disease have received renewed interest in recent years. Most models of this type extend classical compartmental formulations with additional terms accounting for spatial dynamics, with Fickian diffusion being the most common such term. However, while diffusion may be appropriate for modeling vector-borne diseases, or diseases among plants or wildlife, the spatial propagation of airborne diseases in human populations is heavily dependent on human contact and mobility patterns, which are not necessarily well-described by diffusion. By including an additional chemotaxis-inspired term, in which the infection is propagated along the positive gradient of the susceptible population (from regions of low- to high-density of susceptibles), one may provide a more suitable description of these dynamics. This article introduces and analyzes a mathematical model of infectious disease incorporating a modified chemotaxis-type term. The model is analyzed mathematically and the well-posedness of the resulting PDE system is demonstrated. A series of numerical simulations are provided, demonstrating the ability of the model to naturally capture important phenomena not easily observed in standard diffusion models, including propagation over long spatial distances over short time scales and the emergence of localized infection hotspots

Mercy Asiedu, Nenad Tomasev, Chintan Ghate et al.

While large language models (LLMs) have shown promise for medical question answering, there is limited work focused on tropical and infectious disease-specific exploration. We build on an opensource tropical and infectious diseases (TRINDs) dataset, expanding it to include demographic and semantic clinical and consumer augmentations yielding 11000+ prompts. We evaluate LLM performance on these, comparing generalist and medical LLMs, as well as LLM outcomes to human experts. We demonstrate through systematic experimentation, the benefit of contextual information such as demographics, location, gender, risk factors for optimal LLM response. Finally we develop a prototype of TRINDs-LM, a research tool that provides a playground to navigate how context impacts LLM outputs for health.

Rasoul Mirzaei, Sajad Karampoor, N. L. Korotkova

microRNAs (miRNAs) are small, non-coding RNA molecules that play crucial regulatory roles in numerous cellular processes. Recent investigations have highlighted the significant involvement of miRNA-122 (miR-122) in the pathogenesis of infectious diseases caused by diverse pathogens, encompassing viral, bacterial, and parasitic infections. In the context of viral infections, miR-122 exerts regulatory control over viral replication by binding to the viral genome and modulating the host's antiviral response. For instance, in hepatitis B virus (HBV) infection, miR-122 restricts viral replication, while HBV, in turn, suppresses miR-122 expression. Conversely, miR-122 interacts with the hepatitis C virus (HCV) genome, facilitating viral replication. Regarding bacterial infections, miR-122 has been found to regulate host immune responses by influencing inflammatory cytokine production and phagocytosis. In Vibrio anguillarum infections, there is a significant reduction in miR-122 expression, contributing to the pathophysiology of bacterial infections. Toll-like receptor 14 (TLR14) has been identified as a novel target gene of miR-122, affecting inflammatory and immune responses. In the context of parasitic infections, miR-122 plays a crucial role in regulating host lipid metabolism and immune responses. For example, during Leishmania infection, miR-122-containing extracellular vesicles from liver cells are unable to enter infected macrophages, leading to a suppression of the inflammatory response. Furthermore, miR-122 exhibits promise as a potential biomarker for various infectious diseases. Its expression level in body fluids, particularly in serum and plasma, correlates with disease severity and treatment response in patients affected by HCV, HBV, and tuberculosis. This paper also discusses the potential of miR-122 as a biomarker in infectious diseases. In summary, this review provides a comprehensive and insightful overview of the emerging role of miR-122 in infectious diseases, detailing its mechanism of action and potential implications for the development of novel therapeutic strategies.

Rocío Marisol Espinoza-Chávez, A. Salerno, A. Liuzzi et al.

Targeted protein degradation (TPD) is emerging as one of the most innovative strategies to tackle infectious diseases. Particularly, proteolysis-targeting chimera (PROTAC)-mediated protein degradation may offer several benefits over classical anti-infective small-molecule drugs. Because of their peculiar and catalytic mechanism of action, anti-infective PROTACs might be advantageous in terms of efficacy, toxicity, and selectivity. Importantly, PROTACs may also overcome the emergence of antimicrobial resistance. Furthermore, anti-infective PROTACs might have the potential to (i) modulate “undruggable” targets, (ii) “recycle” inhibitors from classical drug discovery approaches, and (iii) open new scenarios for combination therapies. Here, we try to address these points by discussing selected case studies of antiviral PROTACs and the first-in-class antibacterial PROTACs. Finally, we discuss how the field of PROTAC-mediated TPD might be exploited in parasitic diseases. Since no antiparasitic PROTAC has been reported yet, we also describe the parasite proteasome system. While in its infancy and with many challenges ahead, we hope that PROTAC-mediated protein degradation for infectious diseases may lead to the development of next-generation anti-infective drugs.

L. Dykman

ABSTRACT Introduction Vaccination remains very effective in stimulating protective immune responses against infections. An important task in antibody and vaccine preparation is to choose an optimal carrier that will ensure a high immune response. Particularly promising in this regard are nanoscale particle carriers. An antigen that is adsorbed or encapsulated by nanoparticles can be used as an adjuvant to optimize the immune response during vaccination. a very popular antigen carrier used for immunization and vaccination is gold nanoparticles, with are being used to make new vaccines against viral, bacterial, and parasitic infections. Areas covered This review summarizes what is currently known about the use of gold nanoparticles as an antigen carrier and adjuvant to prepare antibodies in vivo and design vaccines against viral, bacterial, and parasitic infections. The basic principles, recent advances, and current problems in the use of gold nanoparticles are discussed. Expert opinion Gold nanoparticles can be used as adjuvants to increase the effectiveness of vaccines by stimulating antigen-presenting cells and ensuring controlled antigen release. Studying the characteristics of the immune response obtained from the use of gold nanoparticles as a carrier and an adjuvant will permit the particles’ potential for vaccine design to be increased.

Yan W, Wu J, Wang S et al.

Wenjuan Yan,1,&ast; Jiaojiao Wu,2,&ast; Shanmei Wang,1 Qi Zhang,1 Youhua Yuan,1 Nan Jing,1 Jiangfeng Zhang,1 Hangchan He,3 Yi Li1 1Department of Clinical Microbiology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, Henan, People’s Republic of China; 2Department of Clinical Microbiology, Xiayi People’s Hospital, Shangqiu, Henan, People’s Republic of China; 3Department of Clinical Laboratory, Baofeng Traditional Chinese Medicine Hospital, Pingdingshan, Henan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yi Li, Department of Clinical Microbiology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, Henan, People’s Republic of China, Tel +8615939039006, Email liyilabmed@henu.edu.cnPurpose: To analyze the risk factors and clinical outcomes of patients isolated with polymyxin B-resistant (PR) Enterobacterales from various clinical specimens to prevent and control the spread of these strains.Methods: This retrospective case-control study included 72 PR Enterobacterales-positive cases and 144 polymyxin B-susceptible (PS) Enterobacterales controls from 2018 to 2022. Patients with PR Enterobacterales isolated in various clinical cultures were defined as cases. Patients with PS Enterobacterales cultures at similar anatomic sites during the same period were randomly selected as controls. Data were collected from clinical and laboratory test records. Bivariable logistic regression and Pearson’s chi-square tests were used to assess risk factors.Results: PR strains were predominantly Klebsiella pneumoniae (72.2%) and Salmonella enteritidis (8.3%). Of the patients, 66.04% were admitted to an intensive care unit (ICU). Risk factors for isolation with PR strains included chronic heart disease (P = 0.012; odds ratio [OR] 1.15; 95% confidence interval [CI] 1.03– 1.28), immunosuppressant use (P = 0.016; OR 1.04 [1.0– 1.07), drainage tube [head] (P = 0.006; OR 1.1 [1.0– 1.1]), and polymyxin B exposure (P = 0.007; OR 1.03 [1.0– 1.06]. With respect to outcomes, admission to an ICU (P = 0.003; OR 7.1 [1.9– 25.4]), hypertension (P = 0.035; OR 1.4 [1.02– 1.83]), and drainage tube [head] (P = 0.044; OR 1.1 [1.0– 1.15]) were associated with treatment failure. Additionally, treatment failure was more frequent in patients (45.83%) than in controls (14.58%).Conclusion: The major risk factors for isolation with PR strains were chronic heart disease, exposure to immunosuppressants, use of drainage tubes, and polymyxin B exposure. The isolation of PR strains in patients was a predictor of unfavorable outcomes. These findings provide a basis for monitoring the spread of PR Enterobacterales.Keywords: polymyxin B resistance, treatment failure, Klebsiella pneumoniae, Salmonella enteritidis

Daniel B. Chastain, Kayla R. Stover

Hu CY, Cui WS, Lei Y et al.

Cheng-Yi Hu,1 Wen-Shuai Cui,1 Yi Lei,1 Yu-Wen Tang,1 Yan-Yan Zhang,1 Qi-Min Su,1 Fang Peng,2 Yun-Fei Zeng,1 Jia-Lin Song,1 Cheng-Na Luo,1 Yan Zhou,1 Xin-Yan Li,1 Zhu-Xiang Zhao1 1Department of Infectious Diseases, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, People’s Republic of China; 2Department of Critical Care Medicine, the Third Affiliated Hospital of Guang Zhou Medical University, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Zhu-Xiang Zhao, Department of Infectious Diseases, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, 510515, People’s Republic of China, Email zhaozhuxiang@126.comPurpose: To compare the effectiveness of azvudine and nirmatrelvir/ritonavir for the treatment of coronavirus disease (COVID-19).Patients and Methods: We conducted a retrospective analysis of data from 576 patients with COVID-19, comprising 195 patients without antiviral therapy, 226 patients treated with azvudine, 114 patients treated with nirmatrelvir/ritonavir, and 41 patients were treated with azvudine and nirmatrelvir/ritonavir concurrently. We compared their symptoms, mortality rates, and the length and cost of hospitalization.Results: The incidence of symptoms was similar in patients treated with azvudine and in those treated with nirmatrelvir/ritonavir. However, among patients experiencing weakness, the duration of weakness was significantly shorter in the azvudine group than in the nirmatrelvir/ritonavir group (P=0.029). Mortality did not differ significantly between the azvudine group and the nirmatrelvir/ritonavir group (18.14% vs.10.53%, P=0.068). Among “severe patients”, the mortality rate was markedly lower in patients treated with nirmatrelvir/ritonavir than in patients treated with azvudine (16.92% vs.32.17%, P=0.026). In patients with hepatic insufficiency, those treated with nirmatrelvir/ritonavir had substantially lower mortality than those treated with azvudine (15.09% vs.34.25%, P=0.016). In addition, patients treated with nirmatrelvir/ritonavir had longer hospital stays (P=0.002) and higher hospital costs (P< 0.001) than those receiving azvudine. Compared with patients treated with nirmatrelvir/ritonavir or azvudine alone, patients taking nirmatrelvir/ritonavir and azvudine concurrently had no significant improvement in survival (P> 0.05), length of stay (P> 0.05), or hospital costs (P> 0.05).Conclusion: Azvudine is recommended for patients with non-severe COVID-19 with weakness. Nirmatrelvir/ritonavir is recommended for patients with severe COVID-19, to reduce mortality, and it could be the best choice for patients with hepatic insufficiency. The concurrent use of nirmatrelvir/ritonavir and azvudine in patients with COVID-19 could be not recommended.Keywords: azvudine, nirmatrelvir/ritonavir, COVID-19, SARS-CoV-2

Susan E. Little

H. Shamshad, R. Bakri, A. Mirza

Parasitic diseases have a serious impact on the world in terms of health and economics and are responsible for worldwide mortality and morbidity. The present review features the hybrid targeting involving three main enzymes for the treatment of different parasitic diseases. The enzymes Dihydrofolate reductase, thymidylate synthase, and Serine hydroxy methyltransferase play an essential role in the folate pathway. The present review focuses on these enzymes, which can be targeted against several diseases. It shed light on the past, present, and future of these targets, and it can be assessed that these targets can play a significant role against several infectious diseases. For combating viral and protozoal infectious diseases, these targets in combination should be addressed.

I. Okagu, J. C. Ndefo, E. C. Aham et al.

The health benefits and toxicity of plant products are largely dependent on their secondary metabolite contents. These compounds are biosynthesized by plants as protection mechanisms against environmental factors and infectious agents. This review discusses the traditional uses, phytochemical constituents and health benefits of plant species in genus Zanthoxylum with a focus on cancer, microbial and parasitic infections, and sickle cell disease as reported in articles published from 1970 to 2021 in peer-reviewed journals and indexed in major scientific databases. Generally, Z. species are widely distributed in Asia, America and Africa, where they are used as food and for disease treatment. Several compounds belonging to alkaloids, flavonoids, terpenoids, and lignans, among others have been isolated from Z. species. This review discusses the biological activities reported for the plant species and their phytochemicals, including anticancer, antibacterial, antifungal, antiviral, anti-trypanosomal, antimalarial and anti-sickling properties. The safety profiles and suggestions for conservation of the Z. species were also discussed. Taken together, this review demonstrates that Z. species are rich in a wide range of bioactive phytochemicals with multiple health benefits, but more research is needed towards their practical application in the development of functional foods, nutraceuticals and lead compounds for new drugs.

K. Ahmadi, Zahra Gharibi, P. Davoodian et al.

Smoking is a well-known major risk factor for respiratory tract and other systemic infections. The World Health Organization estimates that between 2000 and 2025, about 9% of deaths will be caused by tobacco use, and more than half of all smokers die from smoking-related diseases. Smoking can damage almost all organs of the human body and is a major risk factor for respiratory infections and other infectious diseases. Smoking can increase the risk of respiratory infections through various mechanisms, which include changes in the structural, functional, and immune defenses of the host. Smoking is one of the most serious public health problems in the world. Promoting smoking cessation is the most practical and economical preventive measure to reduce the severity of tobacco-related infections. In this study, we investigated the role of smoking in increasing the risk of bacterial, fungal, viral, and parasitic infections. We also evaluated various mechanisms by which smoking increases the risk of tobacco-related infections.