Introduction

Having knowledge regarding the trends as well as current patterns on Human Immunodeficiency Virus (HIV) infections is crucial for planning and evaluating prevention strategies and for resource allocation (Hall et al., 2008). Data on AIDS incidence, diagnoses, and prevalence have been used to plan and target HIV prevention strategies. Undoubtedly, timely information on HIV incidence is required to provide more accurate picture regarding the pandemic of the virus. This may lead to improved reach as well as to impact of local programs (Hall et al., 2008). 

Initially, back-calculation was used in countries such as the United States in order to provide incidence data as well as probability of distribution from HIV infection to AIDS diagnosis trends. However, the methods were not effective because of their inability to provide timely data. A method such as cohort studies was not effective since it was based on a small selected population. Likewise, the method never provided incidence trends over time. Due to the weaknesses of earlier methods, laboratory assay methods that differentiate recent trends against long-time HIV infections have been developed. Therefore, it is now possible to measure directly the incidence of HIV. This research will examine pathology of HIV infections using laboratory methods. 

For instance, Hall and colleagues (2008) used the serologic testing algorithm for recent HIV seroconversion (STARHS) for approximating HIV incidence in the United States. From this analysis, it was determined that HIV incidence had increased significantly from 1977 with the peak being during 1984-85. However, the incidence decreased afterwards until late 1990s when it peaked again, and decreased again in early 2000s (Hall et al., 2008). The researchers also found out that new infections in the US among gays and black individuals remained high (Hall et al., 2008). Likewise, Patterson-Lomba, Wu, and Pagano (2015) noted that identifying recent HIV infection cases has significant implications on public health as well as clinical undertakings. For instance, the knowledge about recent infection cases can help in estimating incidence rates, monitoring epidemic trends, and evaluating effectiveness of interventions to be used (Patterson-Lomba et al., 2015). It is also important in preventing further infections given crucial role of recently infected individuals in terms of transmission. 

This study is important because it has assessed certain biases that have been present in evaluating HIV classification. The analysis of time since infection (TSI) formed the core of the study, and the end result is a distribution with a bimodal shape where it was easier to identify recent chronic cases. Right skew distribution signifies the assays’ worst performance due to inability to differentiate between recent and past chronic cases. Left skew distribution is associated with low precision due to low prevalence of recent cases. The investigators predicted that assay variability is lower with time since infection is bimodal, but it becomes larger when TSI is left-skewed, particularly if the recency is six months. Many authors consider recency between 6 and 12 months as the most appropriate one. 

Serological and molecular-based methods have also been used to identify HIV infection recency. Moyo and colleagues (2015) reviewed the methods because the need for accurate identification of HIV infections continues to elicit research interests. Serological tests of recent HIV infections are numerous, and some of them will be highlighted below. Firstly, there are Less Sensitive Enzyme Immunoassays (LS-EIA) based on steady increase of HIV-1 antibodies with time after seroconversion (Moyo et al., 2015). Secondly, there is a proportion of HIV-1 Specific IgG Antibodies method that estimates the proportion of HIV-1 specific IgG relative to the total IgG (Moyo et al., 2015). The method identifies recent HIV infections whenever HIV-specific IgG becomes lower than the total IgG. The assay uses peptides derived from immunodominant regions of gp41 glycoprotein of different HIV-1 strains. 

Thirdly, the authors also highlighted the Antibody Avidity Assays method that measures the strength of antibody-antigen binding. Antibodies with low ratio of avidity indicate recent HIV infection (Moyo et al., 2015). Moreover, there is the Inno-LIA HIV Adaptation method that measures the increase in reaction between antibodies and antigens after seroconversion. Antibodies emerge to HIV-1 proteins at different times after seroconversion, and this notion can be used for determining recency of infection (Moyo et al., 2015). These methods are characterized by such issues as false-recency rates, decreased antibody responses able to lead to inaccurate classification, and the varying false-recency rates. The latter is as a result of varying HIV-1 strains as well as geographical regions. On the other hand, molecular methods for testing recent HIV infections include high resolution melting assay, sequence ambiguities, hamming distances, native bayes classifiers, and sequence clustering-based diversity measure. 

Human retroviruses usually develop resistance to antiretroviral drugs after genomic mutations. This has led to the emergence of drug-resistant human immunodeficiency virus type 1 (HIV-1) that has been a major obstacle in treating HIV infection itself. Developing rapid drug-susceptibility assays is critical in acquiring phenotypic information as well as determining appropriate antiretroviral agents. Therefore, Matsunaga and colleagues (2015) developed an in vitro method known as cell-free drug susceptibility assay (CFDSA) to monitor phenotypic information on drug resistance to HIV-1 protease. Unlike current complex, labor intensive, and expensive phenotypic drug resistance assays, the model proposed by Matsunaga et al (2015) is a non-infectious, rapid, accessible, and reliable method for evaluating protease inhibitor-resistant HIV-1 infections.

Pradier and colleagues (2001) sought for evaluating the impact of short-run adherence success of highly active antiretroviral therapy (HAART) on virological and immunological assays. The study conducted among HIV-infected drug users (IDUs) was based on the knowledge that inadequate adherence may have serious effects on an individual as well as on public health effectiveness of HAART including protease inhibitors (Pradier et al., 2001). The study confirmed the data obtained in other groups. This might not be possible for total inhibition of viral replication to occur in more than 50% of patients who are treated with HAART drug combinations. Similarly, the study confirmed that adherence to protease inhibitor therapy is required for virological success; however, it is difficult for many patients to achieve the level of adherence in a short time. Significant correlation was found between the patients’ viral load and self-reports regarding adherence to injected drug users. This outcome lends validity to using patients’ declarations as a way of assessing such adherence. Nonetheless, the study could not establish the relationships between different adherence levels and types of virological and immunological responses to HAART (Pradier et al., 2001). 

Indeed, some physicians have argued that HAART should be withheld from disadvantaged patients such as IDUs who are associated with high risks of non-adherence. This may lead to the diffusion of untreatable strains of drug-resistant HIV infections. The study was very important because it showed that, it is possible to have positive effect of HAART on CD4+ T cell counts even with limited adherence, which is significant in pathology of HIV infections (Pradier et al., 2001). Haqqani and colleagues (2015) record that CD4+ T cells drive support recombination events in vivo.  The cells are the preferential targets of double infection by HIV-1. Importantly, CD8+ T cells have been found not involved in viral control during early phases of infection. This is a marked contrast from CD4+ T cells that have been detected in spleen as well as in bone marrow. However, CD4+ T cells are not found in blood of infected animals. This indicates that viral replication during the acute phase is not constrained by CD8+ T cells, but it targets at the lymphoid tissues (Petit et al., 2015). 

There have been extensive studies on the impact of opioids on the immune system. However, as Wang and colleagues (2015) recognized, there is still limited information on the precise actions of opioids in terms of intracellular antiviral innate immunity against HIV infections. Therefore, the researchers sought for determining if heroin, which is considered one of the mostly abused drugs, can inhibit the expression of intracellular HIV restriction in miRNA and promote replication of HIV in macrophages. The HIV restriction in miRNA enzymes plays a key role in intracellular immunity; thus, the determination whether environmental factors have the ability to disbalance enzymes is of great significance (Wang et al., 2015). 

Notably, Wang and colleagues (2015) started from determining the effect of heroin dosage on HIV infections in macrophages. The effect was that heroin treatment increased the susceptibility of microphages to infection with HIV strains. Similarly, heroin treatment was found to increase the activity of HIV restriction depending on the time of post infection. Finally, macrophages pretreated with opioid receptor agonist completely abrogated the enhancing result of heroin on HIV restriction activity (Wang et al., 2015). Based on the outcomes of this study, the researchers concluded that heroin enhances the replication of HIV in macrophages. However, this occurs when intracellular HIV restriction in miRNA is inhibited. The previous thought that all pseudogenes are transcriptionally silent is not correct (Gupta, Titus, Zheng & Adami, 2015). Pseudogene transcripts contribute to the non-coding RNA pool of the cells that regulate gene expression. This is important because pseudogene transcription is anticipated in other cellular responses as well as in host responses to the environment.

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