Pair-wise interactions of polymerization inhibitory contact site mutations of hemoglobin-S

The linkage of pair-wise interactions of contact site mutations of HbS has been studied using Le Lamentin [His-20 (α)→Gln], Hoshida [Glu-43 (β)→Gln] and α₂β₂^T87Q mutations as the prototype of three distinct classes of contact sites of deoxy HbS fiber. Binary mixture experiments established that β^A-chain with the Thr-87 (β)→Gln mutation is as potent as the γ-chain of HbF (α₂γ₂) in inhibiting polymerization. On combining the influence of Le Lamentin mutation with that of β₂^T87Q mutations; the net influence is only partial additivity. On the other hand, in binary mixture studies, combined influence of Hoshida mutation with that of β₂^T87Q mutations is synergistic. Besides, a significant level of synergistic complementation is also seen when the Le Lamentin and Hoshida mutations are combined in HbS (symmetrical tetramers). Le Lamentin and Hoshida mutation introduced into the cis-dimer of the asymmetric hybrid tetramer completely neutralizes the Val-6 (β) dependent polymerization. Accordingly, we propose that combining the perturbation of intra-double strand contact site with that of an inter-double strand contact site exhibit synergy when they are present in two different chains of the αβ dimer. A comparison of the present results with that of the earlier studies suggest that when the two contact site perturbations are from the same sub-unit of the αβ dimer only partial additivity is observed. The map of interaction linkage of the contact site mutations exposes new strategies in the design of novel anti-sickling Hbs for the gene therapy of sickle cell disease.     

In vitro free radical scavenging activity of wild edible mushroom, Pleurotus squarrosulus (Mont.) Singer

Cellular damage caused by reactive oxygen species has been implicated in several diseases and hence antioxidants have significant importance in human health. Cold water, hot water and methanolic extract of Pleurotus squarrosulus were evaluated for antioxidant activity against hydroxyl radical, DPPH (1,1-Diphenyl-2-picrylhydrazyl) radical, superoxide radical, nitric oxide (NO) scavenging, reducing power, ferrous ion chelating ability and beta-carotenellinoleic acid assay. Total phenol, flavonoid, beta-carotene and lycopene content were also determined. Hot water extract showed significant antioxidant activity in all the test systems. Hydroxyl radical scavenging activity of all the extracts has been significant compared to positive control. Hot water extract has been found to have higher phenolic, total flavonoid, beta-carotene and lycopene content than cold water and methanolic extract of the mushroom. Results of this study showed that, hot water extract has maximum antioxidant property and may be utilized as a promising source of therapeutics.     

Artificial intelligence in differentiating tropical infections: A step ahead

Background and objectiveDifferentiating tropical infections are difficult due to its homogenous nature of clinical and laboratorial presentations among them. Sophisticated differential tests and prediction tools are better ways to tackle this issue. Here, we aimed to develop a clinician assisted decision making tool to differentiate the common tropical infections.MethodologyA cross sectional study through 9 item self-administered questionnaire were performed to understand the need of developing a decision making tool and its parameters. The most significant differential parameters among the identified infections were measured through a retrospective study and decision tree was developed. Based on the parameters identified, a multinomial logistic regression model and a machine learning model were developed which could better differentiate the infection.ResultsA total of 40 physicians involved in the management of tropical infections were included for need analysis. Dengue, malaria, leptospirosis and scrub typhus were the common tropical infections in our settings. Sodium, total bilirubin, albumin, lymphocytes and platelets were the laboratory parameters; and abdominal pain, arthralgia, myalgia and urine output were the clinical presentation identified as better predictors. In multinomial logistic regression analysis with dengue as a reference revealed a predictability of 60.7%, 62.5% and 66% for dengue, malaria and leptospirosis, respectively, whereas, scrub typhus showed only 38% of predictability. The multi classification machine learning model observed to have an overall predictability of 55–60%, whereas a binary classification machine learning algorithms showed an average of 79–84% for one vs other and 69–88% for one vs one disease category.ConclusionThis is a first of its kind study where both statistical and machine learning approaches were explored simultaneously for differentiating tropical infections. Machine learning techniques in healthcare sectors will aid in early detection and better patient care.     

Effects of procaine on hypoxia induced abnormalities in canine myocardial tissues

Combined effects of hypoxia, hyperkalemia and acidosis (HH&A) produced contracture (increased resting tension) in canine ventricular muscle tissues but not in Purkinje fibers perfused for the same length of time. Administration of procaine during such contracture stabilized the resting tension somewhat. High [Ca]o during HH&A causes contracture to appear much sooner. On return to oxygenated tyrode oscillatory after potentials (or oscillations in diastole) developed in ventricular muscles, and these oscillations disappeared in the presence of procaine.     

Antioxidant and nitric oxide synthase activation properties of Auricularia auricula

In vitro evaluation of antioxidant activities of Auricularia auricula showed significant inhibition of lipid peroxidation, and potent hydroxyl radical scavenging activity when compared with standard drug catechin. IC5o value of crude, boiled and ethanolic extracts of A. auricula represented 403, 510, and 373 microg/ml respectively in case of hydroxyl radical scavenging activity and 310, 572 and 398 microg/ml respectively in case of lipid peroxidation. Furthermore, crude, boiled and ethanolic extracts also increase significantly nitric oxide production (664, 191 and 850 pmole/mg dry wt/hr respectively) over the control. The present results revealed that A. auricula had potential therapeutic use.     

Changes in Skeletal Mineral in Patients on Prolonged Maintenance Dialysis

The measurement of bone loss in patients undergoing maintenance dialysis over a period of two and a half years is reported. The tendency to lose bone is a likely event in renal failure, but depends more on the individual patient than on the type of dialysis used, provided that steps are taken to prevent avoidable calcium loss during dialysis. Vitamin D therapy was an important factor in preventing bone loss in some cases. The tendency to lose bone more readily when both kidneys were absent may have reflected a deficiency of 1-25 dihydrocholecalciferol. On the other hand, bone loss was also observed in transplanted patients. The need to measure bone loss at regular intervals once renal failure has been diagnosed is stressed.     

GC/MS Profiling and Evaluation of Leaf Essential Oil for Bactericidal Effect and Free Radical Scavenging Activity of Plectranthus amboinicus (Lour.) Spreng Collected from Odisha,India

Plectranthus amboinicus (Lour.) Spreng, known as the Indian borage or Mexican mint, is one of the most documented species in the family Lamiaceae for its therapeutic and pharmaceutical values. It is found in the tropical and subtropical regions of the world. The leaf essential oil has immense medicinal benefits like treating illnesses of the skin and disorders like colds, asthma, constipation, headaches, coughs, and fevers. After analyzing earlier reports with regard to the quantity and quality of leaf oil yield, we discovered that the germplasm taken from Odisha is preferable to other germplasms. The objective of the present work is to evaluate the free radical scavenging activity and bactericidal effect of leaf essential oil (EO) of Plectranthus amboinicus (Lour.) Spreng collected from the state of Odisha, India. The hydro distillation technique has been used for essential oil extraction. Upon GC/MS analysis, approximately 57 compounds were identified with Carvacrol as the major compound (peak area=20.25 %), followed by p-thymol (peak area=20.17 %), o-cymene (peak area=19.41 %) and carene (peak area=15.89 %). On evaluation of free radical scavenging activity, it was recorded that the best value of inhibitory concentration, was for DPPH with IC₅₀=18.64 ppm and for H₂O₂ with IC₅₀=9.35 ppm. The EO showed efficient bactericidal effect against both gram positive (Mycobacterium smegmatis, Staphylococcus aureus, Enterococcus faecium) and gram negative (Escherichia coli, Vibrio cholerae, Klebsiella pneumoniae) bacteria studied through well diffusion method. Fumigatory action of the essential oil was found against M. smegmatis, the model organism for tuberculosis study. Alamar Blue assay, gave a result with MIC value for M. smegmatis i. e., 0.12 μg/ml and the MBC value of 0.12 μg/ml. Hence, P. amboinicus found in Odisha can be suggested as an elite variety and should be further investigated for efficient administration in drug formulation.     

A consensus multi-view multi-objective gene selection approach for improved sample classification

Background

High-dimensional flow cytometry and mass cytometry allow systemic-level characterization of more than 10 protein profiles at single-cell resolution and provide a much broader landscape in many biological applications, such as disease diagnosis and prediction of clinical outcome. When associating clinical information with cytometry data, traditional approaches require two distinct steps for identification of cell populations and statistical test to determine whether the difference between two population proportions is significant. These two-step approaches can lead to information loss and analysis bias.

Results

We propose a novel statistical framework, called LAMBDA (Latent Allocation Model with Bayesian Data Analysis), for simultaneous identification of unknown cell populations and discovery of associations between these populations and clinical information. LAMBDA uses specified probabilistic models designed for modeling the different distribution information for flow or mass cytometry data, respectively. We use a zero-inflated distribution for the mass cytometry data based the characteristics of the data. A simulation study confirms the usefulness of this model by evaluating the accuracy of the estimated parameters. We also demonstrate that LAMBDA can identify associations between cell populations and their clinical outcomes by analyzing real data. LAMBDA is implemented in R and is available from GitHub (https://github.com/abikoushi/lambda).