Transcriptome Analysis Revealed Osmoregulation Related Regulatory Networks and Hub Genes in the Gills of Hilsa shad, Tenualosa ilisha, during the Migratory Osmotic Stress.

Tenualosa ilisha (Hilsa shad), an anadromous fish, usually inhabits coastal and estuarine waters, and migrates to freshwater for spawning. In this study, large-scale gill transcriptome analyses from three salinity regions, i.e., fresh, brackish and marine water, revealed 3277 differentially expressed genes (DEGs), out of which 232 were found to be common between marine vs freshwater and brackish vs freshwater. These genes were mapped into 54 KEGG Pathways, and the most significant of these were focal adhesion, adherens junction, tight junction, and PI3K-Akt signaling pathways. A total of 24 osmoregulatory genes were found to be differentially expressed in different habitats. The gene members of slc16 and slc2 families showed a dissimilar pattern of expressions, while two claudin genes (cldn11 & cldn10), transmembrane tm56b, and voltage-gated potassium channel gene kcna10 were downregulated in freshwater samples, as compared to that of brackish and marine environment. Protein-protein interaction (PPI) network analysis of 232 DEGs showed 101 genes to be involved in PPI, while fn1 gene was found to be interacting with the highest number of genes (36). Twenty-five hub genes belonged to 12 functional groups, with muscle structure development with seven genes, forming the major group. These results provided valuable information about the genes, potentially involved in the molecular mechanisms regulating water homeostasis in gills, during migration for spawning and low-salinity adaptation in Hilsa shad. These genes may form the basis for the bio-marker development for adaptation to the stress levied by major environmental changes, due to hatchery/culture conditions.

Spatio-temporal analysis of rainfall in relation to monsoon teleconnections and agriculture at Regional Scale in Haryana, India.

This study examined the long-term (1980-2019) spatio-temporal trends, variability and teleconnections of Indian summer monsoon rainfall (ISMR) of all districts of Haryana, India and their impact on agricultural productivity. The gridded datasets of India Meteorological Department (IMD) were used to statistically analyse the rainfall distribution, trend, coefficient of variation and intensity of rainfall. The gridded datasets of European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis V5 (ERA5) were examined for lower and upper tropospheric wind circulation (850 hPa and 200hpa), vertically integrated moisture transport (VIMT) and surface moisture flux (SMF). The datasets of National Oceanic and Atmospheric Administration (NOAA) were correlated with ISMR and composite deviation of rainfall and rainfall intensity during El Niño and La Niña from neutral years was examined at district level. Our analysis revealed that districts lying in eastern agroclimatic zone (EAZ) of Haryana received more ISMR during each month of monsoon season as compared to the ones situated in western agroclimatic zone (WAZ). Trend-free pre-whitening Mann-Kendall (TFPW-MK) test revealed that Kurukshetra, Panipat, Ambala, Rohtak, Faridabad, Jhajjar, Sonipat, Fatehabad and Palwal have shown a decreasing trend while Mahendragarh and Panchkula have shown an increasing trend of rainfall. During the El Niño years, most of the locations in the state received deficient to large deficient category, whereas during the La Niña episodes, most of the locations received excess to large excess category of ISMR, which is indicative of the influence of El Niño-Southern Oscillation (ENSO) on the regional scale. The influence of ISMR on bajra productivity for the districts lying in WAZ and rice productivity for the districts lying in EAZ was undertaken. This study is beneficial for understanding the impacts of climate change and climate variability on ISMR dynamics in Haryana which may further guide the policy-makers and beneficiaries for optimising the use of hydrological resources.

Recurrent Neural Model to Analyze the Effect of Physical Training and Treatment in Relation to Sports Injuries.

Artificial intelligence has rapidly grown and has made the scenario that no field can function without it. Like every field, it also plays a vital role in the sports field nowadays. In certain sports, injuries happen very often due to heavy training and sudden speedy actions, especially in athletics and football. Here arises a need to analyze the effect of physical training in sportsperson by collecting data from their daily training. With the help of artificial intelligence, a recurrent neural model is developed to analyze the effect of physical training and treatment concerning sports injury. A Recurrent Neural Network (RNN) can be a subsection of Artificial Neural Networks (ANN) that uses the neural nodes connected in a temporal sequence. The temporal sequence is one of the essential terms in this research, which denotes a data sequence of events in a given timeframe. The recurrent neural model is an intelligent machine learning method that comprises a neural schema replicating humans. This neural schema studies the data it collects from the athletes/players and processes it by analyzing previous injuries. Sports injuries have to be analyzed because, in some cases, it becomes more dangerous to the sportsperson that they may even lose their career due to disability. Sometimes it may cause a massive loss to the club or company that hired the sportsperson for the sport. The prediction process can give the player rest until he recovers, thus becoming the safest approach in sports. Therefore, it is essential to analyze the sportsperson's track data to keep an eye on his health. In this research, RNN model is compared with the existing Support Vector Machine (SVM) in concerning to the effect of physical training and treatment for sports. The results show that the proposed model has achieved 99% accuracy, which is higher than the existing algorithm.

The prospective study of change of perception of postgraduate students on objective structured clinical examination in burns and plastic surgery.

BACKGROUND: In this study, we attempted to assess the change of perception of postgraduate students on objective structured clinical examination (OSCE) in burns and plastic surgery after first five OSCE. METHODS: A prevalidated feedback questionnaire was used to assess and score the perception of postgraduate students on OSCE in burns and plastic surgery. The opinion of postgraduate students on the feedback questionnaire after first and fifth assessment tests based on OSCE was analyzed. The results were compiled on a data sheet and analyzed using Microsoft Excel and plotted as graphical interpretation. The statistical analysis was done using MedCalc software. RESULTS: The results of the study showed that there is a positive change in perception of students in favor of monthly assessment based on OSCE in burns and plastic surgery after fifth assessment. The mean students' favorable perception score after the first assessment with was 30.2 ± 2.828 (mean ± standard deviation [SD]) and after fifth assessment, 43 ± 2.828 (mean SD) with Student's test t = 10.119 and P < 0.0001 which is highly significant statistically in favor of OSCE after fifth assessment. CONCLUSIONS: We observed in our study that the monthly assessment based on OSCE is well accepted by the students of our subspecialty after few assessments; however, further studies are required to augment the evidence.

Impact of monsoon teleconnections on regional rainfall and vegetation dynamics in Haryana, India.

Our study has investigated the impact of El Niño-Southern Oscillation (ENSO) on spatio-temporal dynamics of Indian summer monsoon rainfall (ISMR) as well as vegetation for a period of 1980 to 2019 at regional scale in Haryana, India. The gridded rainfall datasets of India Meteorological Department (IMD) were examined on monthly and seasonal scale using various statistical methods like mean climatology, coefficient of variation, slope of linear, Sen's slope, Mann-Kendall Z statistic, and hierarchical cluster analysis. The influence of ENSO on spatial distribution of ISMR was observed, where we found increasing and decreasing rainfall patterns during La Niña and El Niño years, respectively. We attempted to establish a link between ISMR and various teleconnections using time series of the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Laboratory, and statistically significant and positive correlation was observed with the Southern Oscillation Index (SOI), whereas significantly negative correlations were observed with SST of Niño 3, Niño 3.4, and Niño 4 regions. The gridded datasets of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis V5 (ERA5) were used to evaluate the influence of ENSO on atmospheric dynamics using lower and upper tropospheric wind circulation (850 hPa and200 hpa), vertically integrated moisture transport (VIMT), and surface moisture flux (SMF). We have used satellite-based normalised difference vegetation index (NDVI) datasets of the Global Inventory Monitoring and Modeling System (GIMMS) to investigate the impact of ENSO on vegetation dynamics of Haryana and found that NDVI values were higher and lower in case of La Niña and El Niño years, respectively.

Transcriptome analysis revealed hub genes for muscle growth in Indian major carp, Catla catla (Hamilton, 1822).

Catla (Catla catla) is the fastest growing Indian major carp species and forms an important component of the freshwater aquaculture systems in the Indian sub-continent. The molecular mechanisms of growth of the species in response to seasonal water temperature variations hitherto are still unknown. In the current study, high-throughput transcriptome sequencing was used to study the differential gene expression pattern in catla muscle tissues between pre-winter and post-winter fingerling groups and fast-growing table size fish. Transcriptome analysis identified 1677 differentially expressed genes (DEGs) in three different growth stages and 236 common DEGs between fingerling at low temperature and table fish post-winter, including four genes under GH/IGF1 axis and 163 genes under signature for compensatory muscle growth. Molecular pathways for the mapped genes identified 42 KEGG pathways and the critical pathways under Environmental Information Processing identified were PI3K-Akt signaling, AMPK signaling pathway, Calcium signaling pathway and MAPK signaling pathway. In this study, 14 differentially expressed potential regulatory hub genes for growth were identified, for the first time and categorized into three major GO groups: unfolded protein binding, rNA processing and biogenesis and muscle development and differentiation. These regulatory hub genes, except acta1, were found to be upregulated in fast-growing table size and post-winter fingerling groups. The results provided valuable information about the key genes, with potential to be used as biomarkers of growth in breeding programs and contributed to our understanding of the molecular mechanisms and pathways regulating muscle growth, in response to temperature fluctuations and different growth stages in C. catla.

Free Vascularized Supraclavicular Autologous Heterotopic Lymph Node Transfers Without Skin Paddle for Lymphedema Lower Limb.

Free vascularized lymph node transfer (VLNT) is one of the new and highly efficacious procedures in the cases of lymphedema. In this case, we present a case of lower-limb lymphedema which was managed by this procedure where a supraclavicular LN was harvested and transferred to the lower leg. VLNT from the supraclavicular region is a very effective treatment for physiological restoration of the lymphatic flow in established cases of lower-limb lymphedema because of well-hidden favorable scar and minimal chances of secondary iatrogenic lymphedema in the donor region unlike other sites such as groin and axilla. The VLNT should be preferred over manual lymphatic drainage because it is very effective treatment for physiological restoration of the lymphatic flow, however, the further analytical studies are required to confirm statistically the effectiveness of the same over other modalities.

Discovery of alternatively spliced isoforms and long non-coding RNA in full length brain transcriptomes of anadromous Hilsa shad, Tenualosa ilisha (Hamilton, 1822).

BACKGROUND: Full length transcriptomes, achieved through long-read sequencing, along with the isoform analysis can reveal complexities in the gene expression profiles, as well as annotate the transcriptomes of non-model organisms. METHODS AND RESULT: Full length transcripts of brain transcriptome of Tenualosa ilisha, Hilsa shad, were generated through PacBio single molecule real-time sequencing and were characterized. A total of 8.30 Gb clean reads were generated, with PacBio RSII, which resulted in 57,651 high quality consensus transcripts. After removing redundant reads, a total of 19,220 high-quality non-redundant transcripts and 17,341 full length ORF transcripts were classified to 7522 putative ortholog groups. Genes involved in various neural pathways were identified. In addition, isoform clusters and lncRNAs were discovered, along with Hilsa specific transcripts with coding frames and 29,147 SSRs in 944 transcripts (1141 annotated). CONCLUSION: The present study provided, for the first time, a comprehensive view of the alternative isoforms of genes and transcriptome complexity in Hilsa shad brain and forms a rich resource for functional studies in brain of this anadromous fish.