Seasonal Changes in Serum Metabolites in Multiple Sclerosis Relapse.

Multiple sclerosis (MS) is a debilitating chronic disease of unknown etiology. There are limited treatment options due to an incomplete understanding of disease pathology. The disease is shown to have seasonal exacerbation of clinical symptoms. The mechanisms of such seasonal worsening of symptoms remains unknown. In this study, we applied targeted metabolomics analysis of serum samples using LC-MC/MC to determine seasonal changes in metabolites throughout the four seasons. We also analyzed seasonal serum cytokine alterations in patients with relapsed MS. For the first time, we can demonstrate seasonal changes in various metabolites in MS compared to the control. More metabolites were affected in MS in the fall season followed by spring, while summer MS was characterized by the smallest number of affected metabolites. Ceramides were activated in all seasons, suggesting their central role in the disease pathogenesis. Substantial changes in glucose metabolite levels were found in MS, indicating a potential shift to glycolysis. An increased serum level of quinolinic acid was demonstrated in winter MS. Histidine pathways were affected, suggesting their role in relapse of MS in the spring and fall. We also found that spring and fall seasons had a higher number of overlapping metabolites affected in MS. This could be explained by patients having a relapse of symptoms during these two seasons.

Cytokine, Chemokine, and Metalloprotease Activation in the Serum of Patients with Nephropathia Epidemica from the Republic of Tatarstan and the Republic of Mordovia, Russia.

Nephropathia Epidemica (NE), endemic to several Volga regions of Russia, including the Republic of Tatarstan (RT) and the Republic of Mordovia (RM), is a mild form of hemorrhagic fever with renal syndrome caused by infection with rodent-borne orthohantaviruses. Although NE cases have been reported for decades, little is known about the hantavirus strains associated with human infection in these regions. There is also limited understanding of the pathogenesis of NE in the RT and the RM. To address these knowledge gaps, we conducted comparative analyses of patients with NE in the RT and the RM. Clinical symptoms were more severe in patients with NE from the RM with longer observed duration of fever symptoms and hospitalization. Analysis of patient sera showed changes in the levels of numerous cytokines, chemokines, and matrix metalloproteases (MMPs) in patients with NE from both the RT and the RM, suggesting leukocyte activation, extracellular matrix degradation, and leukocyte chemotaxis. Interestingly, levels of several cytokines were distinctly different between patients NE from the RT when compared with those from the RM. These differences were not related to the genetic variation of orthohantaviruses circulating in those regions, as sequence analysis showed that Puumala virus (PUUV) was the causative agent of NE in these regions. Additionally, only the "Russia" (RUS) genetic lineage of PUUV was detected in the serum samples of patients with NE from both the RT and the RM. We therefore conclude that differences in serum cytokine, chemokine, and MMP levels between the RT and the RM are related to environmental factors and lifestyle differences that influence individual immune responses to orthohantavirus infection.

Serum and Cerebrospinal Fluid Cytokine Biomarkers for Diagnosis of Multiple Sclerosis.

BACKGROUND: Multiple sclerosis (MS) is a chronic debilitating disorder characterized by persisting damage to the brain caused by autoreactive leukocytes. Leukocyte activation is regulated by cytokines, which are readily detected in MS serum and cerebrospinal fluid (CSF). OBJECTIVE: Serum and CSF levels of forty-five cytokines were analyzed to identify MS diagnostic markers. METHODS: Cytokines were analyzed using multiplex immunoassay. ANOVA-based feature and Pearson correlation coefficient scores were calculated to select the features which were used as input by machine learning models, to predict and classify MS. RESULTS: Twenty-two and twenty cytokines were altered in CSF and serum, respectively. The MS diagnosis accuracy was ≥92% when any randomly selected five of these biomarkers were used. Interestingly, the highest accuracy (99%) of MS diagnosis was demonstrated when CCL27, IFN-γ, and IL-4 were part of the five selected cytokines, suggesting their important role in MS pathogenesis. Also, these binary classifier models had the accuracy in the range of 70-78% (serum) and 60-69% (CSF) to discriminate between the progressive (primary and secondary progressive) and relapsing-remitting forms of MS. CONCLUSION: We identified the set of cytokines from the serum and CSF that could be used for the MS diagnosis and classification.

Mutational Frequencies of SARS-CoV-2 Genome during the Beginning Months of the Outbreak in USA.

SARS-CoV-2 has spread very quickly from its first reported case on 19 January 2020 in the United Stated of America, leading WHO to declare pandemic by 11 March 2020. RNA viruses accumulate mutations following replication and passage in human population, which prompted us to determine the rate and the regions (hotspots) of the viral genome with high rates of mutation. We analyzed the rate of mutation accumulation over a period of 11 weeks (submitted between 19th January to 15 April 2020) in USA SARS-CoV-2 genome. Our analysis identified that majority of the viral genes accumulated mutations, although with varying rates and these included NSP2, NSP3, RdRp, helicase, Spike, ORF3a, ORF8, and Nucleocapsid protein. Sixteen mutations accumulated in Spike protein in which four mutations are located in the receptor binding domain. Intriguingly, we identified a fair number of viral proteins (NSP7, NSP9, NSP10, NSP11, Envelop, ORF6, and ORF7b proteins), which did not accumulate any mutation. Limited changes in these proteins may suggest that they have conserved functions, which are essential for virus propagation. This provides a basis for a better understanding of the genetic variation in SARS-CoV-2 circulating in the US, which could help in identifying potential therapeutic targets for controlling COVID-19.

Recent advances in the diagnosis of leptospirosis.

Leptospirosis can be found in virtually all tropical and temperate areas of the world and is presumed to be the widely spread zoonotic infection in the world. Because of the variety of clinical symptoms seen in the symptomatic cases, leptospirosis at its onset is often misdiagnosed as aseptic meningitis, influenza, hepatic disease or fever (pyrexia) of unknown origin. The disease has been widely spread, ranging from subclinical infection to a severe syndrome of multiorgan infection with high mortality. It is an occupational hazard for people who work outdoors or with animals, such as rice and sugar-cane field workers, farmers, sewer workers, veterinarians, dairy workers, and military personnel. Various diagnostic methods have been developed for the diagnosis of leptospirosis that includes direct examination; serology and molecular based techniques, but have various shortcomings, so there is a need to develop an effective surveillance system to monitor the trends of disease to control this life-threatening zoonosis. Now a day's biosensor based technology becomes an excellent platform in the field of diagnostics due to their better sensitivity and specificity. So different types of biosensors such as enzyme-based, tissue-based, immunosensor, DNA biosensors, thermal and piezoelectric biosensors have been discussed here to highlight their indispensable applications in different fields. In this review, we will examine the current utilization of functionalized detection methods with other synthetic mixes for the development of biosensor prompting to the location of particular analytes with low discovery cut-off and quick reaction.

Hetero-Polysaccharides Secreted from Dunaliella salina Exhibit Immunomodulatory Activity Against Peripheral Blood Mononuclear Cells and RAW 264.7 Macrophages.

Several species of microalgae have been known to produce exopolysaccharides (EPS) with potential immune activity. In the present investigation, ethyl acetate fraction of crude EPS secreted by Dunaliella salina was explored for immunomodulatory activity against peripheral blood mononuclear cells (PBMC) and RAW 264.7 macrophages. Effect of EPS on cell growth and cytokines production were measured using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay and ELISA respectively. Griess reagent was used for measuring the nitric oxide production in RAW 264.7 macrophages. FTIR analysis and mass spectroscopy were carried out for the characterization. Ethyl acetate fraction exhibited dose dependent increase in proliferative index and cytokines production (IFN-γ, TNF-α, TGF-ß). At low concentration (250 and 500 µg/mL), it showed growth inhibition and at higher concentration (1000 and 1500 µg/mL), it enhanced the cell growth. Interestingly, the pronounced increased TNF-α production was observed in ethyl acetate fraction treated PBMC cells at higher concentration (750 and 1000 µg/mL) indicating the immunostimulatory effect. In RAW cells, concentration dependent diminished cell growth (IC50 = 691 µg/mL) and nitric oxide production (IC50 = 630 µg/mL) was observed. FTIR analysis showed the presence of polysaccharides due to the detection of hydroxyl (-OH), Carbonyl (C-O) and alkyl (C-H) groups. Mass spectroscopy results revealed ethyl acetate fraction as penta-saccharide (m/z = 887.56 and 886.54) which are confirmed to be hetero-polysaccharides consisting of hexoses and pentoses along with association of ions. These results suggest that penta-saccharide (ethyl acetate fraction) isolated from D. salina may have the potential to be used for therapeutic purpose as immunomodulatory agent.

Computational Intelligence Technique for Prediction of Multiple Sclerosis Based on Serum Cytokines.

Multiple sclerosis (MS) is a neurodegenerative disease characterized by lesions in the central nervous system (CNS). Inflammation and demyelination are the leading causes of neuronal death and brain lesions formation. The immune reactivity is believed to be essential in the neuronal damage in MS. Cytokines play important role in differentiation of Th cells and recruitment of auto-reactive B and T lymphocytes that leads to neuron demyelination and death. Several cytokines have been found to be linked with MS pathogenesis. In the present study, serum level of eight cytokines (IL-1ß, IL-2, IL-4, IL-8, IL-10, IL-13, IFN-γ, and TNF-α) was analyzed in USA and Russian MS to identify predictors for the disease. Further, the model was extended to classify MS into remitting and non-remitting by including age, gender, disease duration, Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Severity Score (MSSS) into the cytokines datasets in Russian cohorts. The individual serum cytokines data for the USA cohort was generated by Z score percentile method using R studio, while serum cytokines of the Russian cohort were analyzed using multiplex immunoassay. Datasets were divided into training (70%) and testing (30%). These datasets were used as an input into four machine learning models (support vector machine, decision tree, random forest, and neural networks) available in R programming language. Random forest model was identified as the best model for diagnosis of MS as it performed remarkable on all the considered criteria i.e., Gini, accuracy, specificity, AUC, and sensitivity. RF model also performed best in predicting remitting and non-remitting MS. The present study suggests that the concentration of serum cytokines could be used as prognostic markers for the prediction of MS.

Metadherin: A Therapeutic Target in Multiple Cancers.

Altered expression of many genes and proteins is essential for cancer development and progression. Recently, the affected expression of metadherin (MTDH), also known as AEG-1 (Astrocyte Elevated Gene 1) and Lyric, has been implicated in various aspects of cancer progression and metastasis. Elevated expression of MTDH/AEG-1 has been reported in many cancers including breast, prostate, liver, and esophageal cancers, whereas its expression is low or absent in non-malignant tissues. These expression studies suggest that MTDH may represent a potential tumor associated antigen. MTDH also regulates multiple signaling pathways including PI3K/Akt, NF-κB, Wnt/ß-catenin, and MAPK which cooperate to promote the tumorigenic and metastatic potential of transformed cells. Several microRNA have also been found to be associated with the increased MTDH expression in different cancers. Increased MTDH levels were linked to the tumor chemoresistance making it an attractive novel therapeutic target. In this review, we summarize data on MTDH function in various cancers.