Comparison of Modules of Wild Type and Mutant Huntingtin and TP53 Protein Interaction Networks: Implications in Biological Processes and Functions

Disease-causing mutations usually change the interacting partners of mutant proteins. In this article, we propose that the biological consequences of mutation are directly related to the alteration of corresponding protein protein interaction networks (PPIN). Mutation of Huntingtin (HTT) which causes Huntington's disease (HD) and mutations to TP53 which is associated with different cancers are studied as two example cases. We construct the PPIN of wild type and mutant proteins separately and identify the structural modules of each of the networks. The functional role of these modules are then assessed by Gene Ontology (GO) enrichment analysis for biological processes (BPs). We find that a large number of significantly enriched (p<0.0001) GO terms in mutant PPIN were absent in the wild type PPIN indicating the gain of BPs due to mutation. Similarly some of the GO terms enriched in wild type PPIN cease to exist in the modules of mutant PPIN, representing the loss. GO terms common in modules of mutant and wild type networks indicate both loss and gain of BPs. We further assign relevant biological function(s) to each module by classifying the enriched GO terms associated with it. It turns out that most of these biological functions in HTT networks are already known to be altered in HD and those of TP53 networks are altered in cancers. We argue that gain of BPs, and the corresponding biological functions, are due to new interacting partners acquired by mutant proteins. The methodology we adopt here could be applied to genetic diseases where mutations alter the ability of the protein to interact with other proteins.Comment: 35 pages, 10 eps figures, (Supplementary material and Datasets are available on request

Correlation of spirometry and six minute walk test in patients with chronic obstructive pulmonary disease from Sundargarh, Odisha, India

Background: Six‑Minute Walk Test (6MWT) is a simple, objective, reproducible test which correlated well with different spirometric indices, and thus able to predict severity of Chronic Obstructive Pulmonary Disease (COPD) and can replace spirometry in resource poor set‑up. Here, author evaluated the correlation of 6 minute walk distance (6MWD) with spirometric indices in COPD patients and the potential of 6MWT as an alternative to the assessment of severity of COPD.Methods: This cross-sectional observational study included a total of 80 COPD patients, diagnosed by GOLD criteria (Post bronchodilator FEV1/ FVC ratio <0.7). Modified Medical Research Council (mMRC) grading was used (age, weight, height, body mass index- BMI and breathlessness) and all the patients underwent spirometric measurement of FEV1, FVC and FEV1/ FVC ratio and tests were repeated after bronchodilation using 200-400 μg of salbutamol. 6MWT was performed following American Thoracic Society (ATS) protocol of 6MWT and distance was measured in meters.Results: Author found significant negative correlation of 6MWT with age (r=-0.384, p=0.00) and mMRC grading of dyspnea (r=-0.559, p=0.00) and significant positive correlation with height (r=0.267, p=0.019) and weight (r=0.293, p=0.008). Significant positive correlation of 6MWD was noted with post bronchodilator FEV1(r=0.608, p=0.00), FEV1% (r=0.429, p=0.00), FVC (r=0.514 p=0.00), FVC% (r=0.313 p=0.005), FEV1/FVC % (r=0.336, p=0.001). Positive correlation was also observed between 6MWT and BMI but statistically insignificant (r=0.177, p=0.116). There was significant negative correlation between 6MWT and GOLD staging (r=-0.536, p=0.00).Conclusions: This finding concludes that 6MWT can be used for the assessment of severity of disease in COPD patients in places where spirometry is not available

FAST DISSOLVING ORAL FILMS: A TABULAR UPDATE

Fast-dissolving oral films have emerged as alternative dosage forms for the patients who experience difficulties in swallowing traditional oral solid dosage forms such as tablets, capsules, and syrups etc.   These dosage forms disintegrate or dissolve very quickly within seconds when placed in the mouth cavity without need of water or chewing. Due to fast dissolution it provide faster onset of action, bypassing the first pass metabolism, reducing gastric degradation and metabolism of drugs and thus enhance their oral bioavailability. These properties of oral films with patient convenience and compliance made popular and accepted dosage form for pediatric and geriatric as well as adult population. These formulations are suitable for cough, cold, sore throat, allergenic conditions, nausea, pain, hypertension and CNS disorders, epilepsy and many more diseases. The present review provides up to date review in fast dissolving oral films in tabular form so researches can easily track various technologies/research in design and development of oral fast dissolving film. Keywords: Mouth dissolving films, Oral dispersible film, Oral dissolving film, Oral disintegrating film

Genetic diversity and population structure of Indian golden silkmoth (Antheraea assama)

Background The Indian golden saturniid silkmoth (Antheraea assama), popularly known as muga silkmoth, is a semi-domesticated silk producing insect confined to a narrow habitat range of the northeastern region of India. Owing to the prevailing socio-political problems, the muga silkworm habitats in the northeastern region have not been accessible hampering the phylogeography studies of this rare silkmoth. Recently, we have been successful in our attempt to collect muga cocoon samples, although to a limited extent, from their natural habitats. Out of 87 microsatellite markers developed previously for A. assama, 13 informative markers were employed to genotype 97 individuals from six populations and analyzed their population structure and genetic variation. Methodology/Principal Findings We observed highly significant genetic diversity in one of the populations (WWS-1, a population derived from West Garo Hills region of Meghalaya state). Further analysis with and without WWS-1 population revealed that dramatic genetic differentiation (global FST = 0.301) was due to high genetic diversity contributed by WWS-1 population. Analysis of the remaining five populations (excluding WWS-1) showed a marked reduction in the number of alleles at all the employed loci. Structure analysis showed the presence of only two clusters: one formed by WWS-1 population and the other included the remaining five populations, inferring that there is no significant genetic diversity within and between these five populations, and suggesting that these five populations are probably derived from a single population. Patterns of recent population bottlenecks were not evident in any of the six populations studied. Conclusions/Significance A. assama inhabiting the WWS-1 region revealed very high genetic diversity, and was genetically divergent from the five populations studied. The efforts should be continued to identify and study such populations from this region as well as other muga silkworm habitats. The information generated will be very useful in conservation of dwindling muga culture in Northeast India

Evaluating air quality and criteria pollutants prediction disparities by data mining along a stretch of urban-rural agglomeration includes coal-mine belts and thermal power plants

Air pollution has become a threat to human life around the world since researchers have demonstrated several effects of air pollution to the environment, climate, and society. The proposed research was organized in terms of National Air Quality Index (NAQI) and air pollutants prediction using data mining algorithms for particular timeframe dataset (01 January 2019, to 01 June 2021) in the industrial eastern coastal state of India. Over half of the study period, concentrations of PM2.5, PM10 and CO were several times higher than the NAQI standard limit. NAQI, in terms of consistency and frequency analysis, revealed that moderate level (ranges 101–200) has the maximum frequency of occurrence (26–158 days), and consistency was 36%–73% throughout the study period. The satisfactory level NAQI (ranges 51–100) frequency occurrence was 4–43 days with a consistency of 13%–67%. Poor to very poor level of air quality was found 13–50 days of the year, with a consistency of 9%–25%. Random Forest (RF), Support Vector Machine (SVM), Bagged Multivariate Adaptive Regression Splines (MARS) and Bayesian Regularized Neural Networks (BRNN) are the data mining algorithms, that showed higher efficiency for the prediction of PM2.5, PM10, NO2 and SO2 except for CO and O3 at Talcher and CO at Brajrajnagar. The Root Mean Square Error (RMSE) between observed and predicted values of PM2.5 (ranges 12.40–17.90) and correlation coefficient (r) (ranges 0.83–0.92) for training and testing data indicate about slightly better prediction of PM2.5 by RF, SVM, bagged MARS, and BRNN models at Talcher in comparison to PM2.5 RMSE (ranges 13.06–21.66) and r (ranges 0.64–0.91) at Brajrajnagar. However, PM10 (RMSE: 25.80–43.41; r: 0.57–0.90), NO2 (RMSE: 3.00–4.95; r: 0.42–0.88) and SO2 (RMSE: 2.78–5.46; r: 0.31–0.88) at Brajrajnagar are better than PM10 (RMSE: 35.40–55.33; r: 0.68–0.91), NO2 (RMSE: 4.99–9.11; r: 0.48–0.92), and SO2 (RMSE: 4.91–9.47; r: 0.20–0.93) between observed and predicted values of training and testing data at Talcher using RF, SVM, bagged MARS and BRNN models, respectively. Taylor plots demonstrated that these algorithms showed promising accuracy for predicting air quality. The findings will help scientific community and policymakers to understand the distribution of air pollutants to strategize reduction in air pollution and enhance air quality in the study region

Ionization yield measurement in a germanium CDMSlite detector using photo-neutron sources

Two photo-neutron sources, $^{88}$Y$^{9}$Be and $^{124}$Sb$^{9}$Be, have been used to investigate the ionization yield of nuclear recoils in the CDMSlite germanium detectors by the SuperCDMS collaboration. This work evaluates the yield for nuclear recoil energies between 1 keV and 7 keV at a temperature of $\sim$ 50 mK. We use a Geant4 simulation to model the neutron spectrum assuming a charge yield model that is a generalization of the standard Lindhard model and consists of two energy dependent parameters. We perform a likelihood analysis using the simulated neutron spectrum, modeled background, and experimental data to obtain the best fit values of the yield model. The ionization yield between recoil energies of 1 keV and 7 keV is shown to be significantly lower than predicted by the standard Lindhard model for germanium. There is a general lack of agreement among different experiments using a variety of techniques studying the low-energy range of the nuclear recoil yield, which is most critical for interpretation of direct dark matter searches. This suggests complexity in the physical process that many direct detection experiments use to model their primary signal detection mechanism and highlights the need for further studies to clarify underlying systematic effects that have not been well understood up to this point

Search for low-mass dark matter via bremsstrahlung radiation and the Migdal effect in SuperCDMS

We present a new analysis of previously published SuperCDMS data using a profile likelihood framework to search for sub-GeV dark matter (DM) particles through two inelastic scattering channels: bremsstrahlung radiation and the Migdal effect. By considering these possible inelastic scattering channels, experimental sensitivity can be extended to DM masses that are undetectable through the DM-nucleon elastic scattering channel, given the energy threshold of current experiments. We exclude DM masses down to 220  MeV/c2 at 2.7×10−30  cm2 via the bremsstrahlung channel. The Migdal channel search provides overall considerably more stringent limits and excludes DM masses down to 30  MeV/c2 at 5.0×10−30  cm2