HIV-Proteins-Associated CNS Neurotoxicity, Their Mediators, and Alternative Treatments.

Human immunodeficiency virus (HIV)-infected people's livelihoods are gradually being prolonged with the use of combined antiretroviral therapy (ART). Conversely, despite viral suppression by ART, the symptoms of HIV-associated neurocognitive disorder (HAND) endure. HAND persists because ART cannot really permanently confiscate the virus from the body. HAND encompasses a variety of conditions based on clinical presentation and severity level, comprising asymptomatic neurocognitive impairment, moderate neurocognitive disorder, and HIV-associated dementia. During the early stages of HIV infection, inflammation compromises the blood-brain barrier, allowing toxic virus, infected monocytes, macrophages, T-lymphocytes, and cellular products from the bloodstream to enter the brain and eventually the entire central nervous system. Since there are no resident T-lymphocytes in the brain, the virus will live for decades in macrophages and astrocytes, establishing a reservoir of infection. The HIV proteins then inflame neurons both directly and indirectly. The purpose of this review is to provide a synopsis of the effects of these proteins on the central nervous system and conceptualize avenues to be considered in mitigating HAND. We used bioinformatics repositories extensively to simulate the transcription factors that bind to the promoter of the HIV-1 protein and possibly could be used as a target to circumvent HIV-associated neurocognitive disorders. In the same vein, a protein-protein interaction complex was also deduced from a Search Tool for the Retrieval of Interacting Genes. In conclusion, this provides an alternative strategy that could be used to avert HAND.

Altered diversity and composition of gut microbiota in patients with allergic rhinitis.

BACKGROUND: Recently, multiple studies have suggested an association between gut dysbiosis and allergic rhinitis (AR) development. However, the role of gut microbiota in AR development remains obscure. METHODS: The goal of this study was to compare the gut microbiota composition and short-chain fatty acid (SCFAs) differences associated with AR (N = 18) and HCs (healthy controls, N = 17). Gut microbiota 16SrRNA gene sequences were analyzed based on next-generation sequencing. SCFAs in stool samples were analyzed by gas chromatography-mass spectrometry (GC-MS). RESULTS: Compared with HCs, the gut microbiota composition of AR was significantly different in diversity and richness. At the phylum level, the abundance of Firmicutes in the AR group were significantly lower than those in the HCs group. At the genus level, the abundance of Blautia, Eubacterium_hallii_group, Romboutsia, Collinsella, Dorea, Subdoligranulum and Fusicatenibacter in the AR group were significantly lower than that in the HCs group. The concentrations of SCFAs were significantly lower in the AR group compared with the HCs group. Correlation analysis showed that the Eubacterium-hallii-group and Blautia correlated positively with SCFAs. CONCLUSION: Our results demonstrate compositional and functional alterations of the gut microbiome in AR.

The application of texture quantification in hepatocellular carcinoma using CT and MRI: a review of perspectives and challenges.

Recently, radiomic texture quantification of tumors has received much attention from radiologists, scientists, and stakeholders because several results have shown the feasibility of using the technique to diagnose and manage oncological conditions. In patients with hepatocellular carcinoma, radiomics has been applied in all stages of tumor evaluation, including diagnosis and characterization of the genotypic behavior of the tumor, monitoring of treatment responses and prediction of various clinical endpoints. It is also useful in selecting suitable candidates for specific treatment strategies. However, the clinical validation of hepatocellular carcinoma radiomics is limited by challenges in imaging protocol and data acquisition parameters, challenges in segmentation techniques, dimensionality reduction, and modeling methods. Identification of the best segmentation and optimal modeling methods, as well as texture features most stable to imaging protocol variability would go a long way in harmonizing HCC radiomics for personalized patient care. This article reviews the process of HCC radiomics, its clinical applications, associated challenges, and current optimization strategies.