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MicroRNAs are found to regulate various biological processes which are produced from precursor microRNA. As the length of such microRNA are small, homology-based searching is not very useful. Hence, various machine learning based tools have been designed for prediction of such hairpin loops using various thermodynamic and sequential features. In this research, we discuss about the comparative statistical analysis of various features used the in development of machine learning based predictive tools. The sequence features of insect precursor microRNA were compared with precursor microRNA of other available organisms. We initially established that features such as Length, GC content, Minimum Free Energy (MFE) of folding, etc., differs in insects as compared to other organisms using Kolmogorov-Smirnov (KS) test. We further trained a predictive model for one-vs-rest binary classification using XGBoost between insects, human, monocots, aves, ruminants, sauria, dogs and rodents. We performed PCA and retained 14 principal components for classification using cumulative explained variance. Various parameters of XGBoost was tuned with 5-fold CV and the parameter values with highest CV score were considered. We used independent held-out data test the models. The accuracy of insect, monocots, rodents, human, ruminants, sauria, aves and dogs was found to be 0.8549, 0.8626, 0.6835, 0.7005, 0.8875, 0.6972, 0.7591 and 0.6588 respectively. This shows that ancestral lineage specific ML models can be developed for detection of precursor microRNA for different classes of organism.

Pre-MicroRNAs are the hairpin loops from which microRNAs are produced that have been found to negatively regulate gene expression in several organisms. In insects, microRNAs participate in several biological processes including metamorphosis, reproduction, immune response, etc. Numerous tools have been designed in recent years to predict novel pre-microRNA using binary machine learning classifiers where prediction models are trained with true and pseudo pre-microRNA hairpin loops. Currently, there are no existing tool that is exclusively designed for insect pre-microRNA detection. Application of machine learning algorithms to develop an open source tool for prediction of novel precursor microRNA in insects and search for their miRNA targets in the model insect organism, Drosophila melanogaster. Machine learning algorithms such as Random Forest, Support Vector Machine, Logistic Regression and K-Nearest Neighbours were used to train insect true and false pre-microRNA features with 10-fold Cross Validation on SMOTE and Near-Miss datasets. miRNA targets IDs were collected from miRTarbase and their corresponding transcripts were collected from FlyBase. We used miRanda algorithm for the target searching. In our experiment, SMOTE performed significantly better than Near-Miss for which it was used for modelling. We kept the best performing parameters after obtaining initial mean accuracy scores >90% of Cross Validation. The trained models on Support Vector Machine achieved accuracy of 92.19% while the Random Forest attained an accuracy of 80.28% on our validation dataset. These models are hosted online as web application called RNAinsecta. Further, searching target for the predicted pre-microRNA in Drosophila melanogaster has been provided in RNAinsecta.

Among all types of cancer, breast cancer is the most aggressive, as it is responsible for most of the cancer related death of women. Though several medical therapies are available, the scenario of curing such disease is not favorable. Therefore, there is an urgent need to find alternatives to deal with it. The knowledge of ethnopharmacy might give some better solution to mitigate such deadly diseases. Here, we are using the rhizome of Curcuma caesia Roxb. (Black turmeric), as well as gold nanoparticles (GNPs) synthesized with it to check their specific cytotoxic potentiality against breast cancer cell lines. In our study, ethanolic extract was used to evaluate the cytotoxic effect of the rhizome. GNPs were synthesized by using the same extract and characterized by UV–Vis spectroscopy (UV–Vis), Transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and Thermo gravimetric analysis (TGA). The TEM, XRD, FTIR and TGA results revealed the successful synthesis and capping of GNPs. The UV–Vis Spectrum showed a sharp and narrow absorption peak at 550 nm and HRTEM confirmed both the stability and successful synthesis of the nanoparticles. The MTT assay of the crude extract revealed strong cytotoxicity against breast cancer cell lines viz. MCF-7 (ER + ) and MDA MB-231 (Triple Negative Breast Cancer, TNBC) by showing IC 50 values as 15.70 ± 0.029 and 21.57 ± 0.031 μg/mL respectively. For extract mediated GNPs, the IC 50 values were found to be 6.44 ± 0.045 and 5.87 ± 0.031μg/mL respectively in both breast cancer cell lines. As the IC 50 value for GNPs was found to be much lower than that of crude extract, it indicates a higher efficiency of the GNP. However, both the rhizome extract and its mediated GNPs showed more toxicity towards MDA MB-231 (TNBC) cell lines. It was also observed that the GNPs showed more toxicity towards TNBC cell lines compared to the rhizome extract. No toxicity was found in case of other cell lines such as L 929 and HeLa for both crude extract as well as for GNPs. These observations suggests that both the crude rhizome extract and its derived GNPs exhibit selective cytotoxic potential against breast cancer cell lines, which might be exploited for target specific treatment. Moreover, with an understanding of the mechanism behind the GNPs therapeutic efficiency, it can be developed as a personalized therapy to treat such type of cancers.

Uziflies (Family: Tachinidae) are dipteran endoparasites of sericigenous insects which cause major economic loss in the silk industry globally. Here, we are presenting the first full mitogenome of Blepharipa sp. (Acc: KY644698, 15,080 bp, A + T = 78.41%), a dipteran parasitoid of Muga silkworm ( Antheraea assamensis ) found in the Indian states of Assam and Meghalaya. This study has confirmed that Blepharipa sp. mitogenome gene content and arrangement is similar to other Tachinidae and Sarcophagidae flies of Oestroidea superfamily, typical of ancestral Diptera. Although, Calliphoridae and Oestridae flies have undergone tRNA translocation and insertion, forming unique intergenic spacers (IGS) and overlapping regions (OL) and a few of them (IGS, OL) have been conserved across Oestroidea flies. The Tachinidae mitogenomes exhibit more AT content and AT biased codons in their protein-coding genes (PCGs) than the Oestroidea counterpart. About 92.07% of all (3722) codons in PCGs of this new species have A/T in their 3rd codon position. The high proportion of AT and repeats in the control region (CR) affects sequence coverage, resulting in a short CR ( Blepharipa sp.: 168 bp) and a smaller tachinid mitogenome. Our research unveils those genes with a high AT content had a reduced effective number of codons, leading to high codon usage bias. The neutrality test shows that natural selection has a stronger influence on codon usage bias than directed mutational pressure. This study also reveals that longer PCGs (e.g., nad5 , cox1 ) have a higher codon usage bias than shorter PCGs (e.g., atp8 , nad4l ). The divergence rates increase nonlinearly as AT content at the 3rd codon position increases and higher rate of synonymous divergence than nonsynonymous divergence causes strong purifying selection. The phylogenetic analysis explains that Blepharipa sp. is well suited in the family of insectivorous tachinid maggots. It's possible that biased codon usage in the Tachinidae family reduces the effective number of codons, and purifying selection retains the core functions in their mitogenome, which could help with efficient metabolism in their endo-parasitic life style and survival strategy.

Muga (Antheraea assamensis) is an economically important silkmoth endemic to the states of Assam and Meghalaya in India and is the producer of the strongest known commercial silk. However, there is a scarcity of genomic and proteomic data for understanding the organism at a molecular level. Our present study is on decoding the complete mitochondrial genome (mitogenome) of A. assamensis using next generation sequencing technology and comparing it with other available lepidopteran mitogenomes. Mitogenome of A. assamensis is an AT rich circular molecule of 15,272 bp (A+T content ~80.2%). It contains 37 genes comprising of 13 protein coding genes (PCGs), 22 tRNA and 2 rRNA genes along with a 328 bp long control region. Its typical tRNAMet-tRNAIle-tRNAGln arrangement differed from ancestral insects (tRNAIle-tRNAGln-tRNAMet). Two PCGs cox1 and cox2 were found to have CGA and GTG as start codons, respectively as reported in some lepidopterans. Interestingly, nad4l gene showed higher transversion mutations at intra-species than inter-species level. All PCGs evolved under strong purifying selection with highest evolutionary rates observed for atp8 gene while lowest for cox1 gene. We observed the typical clover-leaf shaped secondary structures of tRNAs with a few exceptions in case of tRNASer1 and tRNATyr where stable DHU and TΨC loop were absent. A significant number of mismatches (35) were found to spread over 19 tRNA structures. The control region of mitogenome contained a six bp (CTTAGA/G) deletion atypical of other Antheraea species and lacked tandem repeats. Phylogenetic position of A. assamensis was consistent with the traditional taxonomic classification of Saturniidae. The complete annotated mitogenome is available in GenBank (Accession No. KU379695). To the best of our knowledge, this is the first report on complete mitogenome of A. assamensis.

Beyond natural enzymes, the artificially synthesized nanozymes have attracted a significant interest as it can overcome the limitations of the former. Here, we report synthesis of shape controlled nanozymes showing proteolytic activity using Carica papaya L. (papaya) latex. The nanozymes synthesized under optimized reaction conditions exhibited sharp SPR peak around 550 nm with high abundance (45.85%) of prism shaped particles. FTIR analysis and coagulation test indicated the presence of papaya latex enzymes as capping agents over the gold nanoprisms. The milk clot assay and the inhibition test with egg white confirmed the proteolytic activity of the nanozymes and the presence of cysteine protease on it, respectively. The nanozymes were found to be biocompatible and did not elicit any toxic response in both in-vitro and in-vivo study. Based on our findings, we envisage that these biocompatible, shape-specific nanozymes can have potential theragnostic applications.

Efforts to replace conventional chromatographic methods for environmental monitoring with cheaper and easy to use biosensors for precise detection and estimation of hazardous environmental toxicants, water or air borne pathogens as well as various other chemicals and biologics are gaining momentum. Out of the various types of biosensors classified according to their bio-recognition principle, nucleic-acid-based sensors have shown high potential in terms of cost, sensitivity, and specificity. The discovery of catalytic activities of RNA (ribozymes) and DNA (DNAzymes) which could be triggered by divalent metallic ions paved the way for their extensive use in detection of heavy metal contaminants in environment. This was followed with the invention of small oligonucleotide sequences called aptamers which can fold into specific 3D conformation under suitable conditions after binding to target molecules. Due to their high affinity, specificity, reusability, stability, and non-immunogenicity to vast array of targets like small and macromolecules from organic, inorganic, and biological origin, they can often be exploited as sensors in industrial waste management, pollution control, and environmental toxicology. Further, rational combination of the catalytic activity of DNAzymes and RNAzymes along with the sequence-specific binding ability of aptamers have given rise to the most advanced form of functional nucleic-acid-based sensors called aptazymes. Functional nucleic-acid-based sensors (FNASs) can be conjugated with fluorescent molecules, metallic nanoparticles, or quantum dots to aid in rapid detection of a variety of target molecules by target-induced structure switch (TISS) mode. Although intensive research is being carried out for further improvements of FNAs as sensors, challenges remain in integrating such bio-recognition element with advanced transduction platform to enable its use as a networked analytical system for tailor made analysis of environmental monitoring.

An increase in the expression of estrogen receptors (ER) and the expanded population of ER-positive cells are two common phenotypes of breast cancer. Detection of the aberrantly expressed ERα in breast cancer is carried out using ERα-antibodies and radiolabelled ligands to make decisions about cancer treatment and targeted therapy. Capitalizing on the beneficial advantages of aptamer over the conventional antibody or radiolabelled ligand, we have identified a DNA aptamer that selectively binds and facilitates the detection of ERα in human breast cancer tissue sections. The aptamer is identified using the high throughput sequencing assisted SELEX screening. Biophysical characterization confirms the binding and formation of a thermodynamically stable complex between the identified DNA aptamer (ERaptD4) and ERα (Ka = 1.55±0.298×108 M(-1); ΔH = 4.32×104±801.1 cal/mol; ΔS = -108 cal/mol/deg). Interestingly, the specificity measurements suggest that the ERaptD4 internalizes into ERα-positive breast cancer cells in a target-selective manner and localizes specifically in the nuclear region. To harness these characteristics of ERaptD4 for detection of ERα expression in breast cancer samples, we performed the aptamer-assisted histochemical analysis of ERα in tissue samples from breast cancer patients. The results were validated by performing the immunohistochemistry on same samples with an ERα-antibody. We found that the two methods agree strongly in assay output (kappa value = 0.930, p-value <0.05 for strong ERα positive and the ERα negative samples; kappa value = 0.823, p-value <0.05 for the weak/moderate ER+ve samples, n = 20). Further, the aptamer stain the ERα-positive cells in breast tissues without cross-reacting to ERα-deficient fibroblasts, adipocytes, or the inflammatory cells. Our results demonstrate a significant consistency in the aptamer-assisted detection of ERα in strong ERα positive, moderate ERα positive and ERα negative breast cancer tissues. We anticipate that the ERaptD4 aptamer targeting ERα may potentially be used for an efficient grading of ERα expression in cancer tissues.

Diptera, the true flies are frequently found in nature and their habitat is found all over the world including Antarctica and Polar Regions. The number of documented species for order diptera is quite high and thought to be 14% of the total animal present in the earth [1]. Most of the study in diptera has focused on the taxa of economic and medical importance, such as the fruit flies Ceratitis capitata and Bactrocera spp. (Tephritidae), which are serious agricultural pests; the blowflies (Calliphoridae) and oestrid flies (Oestridae), which can cause myiasis; the anopheles mosquitoes (Culicidae), are the vectors of malaria; and leaf-miners (Agromyzidae), vegetable and horticultural pests [2]. Insect mitochondrion consists of 13 protein coding genes, 22 tRNAs and 2 rRNAs, are the remnant portion of alpha-proteobacteria is responsible for simultaneous function of energy production and thermoregulation of the cell through the bi-genomic system thus different adaptability in different climatic condition might have compensated by complementary changes is the both genomes [3,4]. In this study we have collected complete mitochondrial genome and occurrence data of one hundred thirteen such dipteran insects from different databases and literature survey. Our understanding of the genetic basis of climatic adaptation in diptera is limited to the basic information on the occurrence location of those species and mito genetic factors underlying changes in conspicuous phenotypes. To examine this hypothesis, we have taken an approach of Nucleotide substitution analysis for 13 protein coding genes of mitochondrial DNA individually and combined by different software for monophyletic group as well as paraphyletic group of dipteran species. Moreover, we have also calculated codon adaptation index for all dipteran mitochondrial protein coding genes. Following this work, we have classified our sample organisms according to their location data from GBIF (https://www.gbif.org). Finally, result suggests that dipteran insects from different regions are gone through distinct selection process and even our outcome also indicate that dipteran mitochondrial genes from different climatic condition shows differential efficacy in their translation process.

Background: Life event research is the cornerstone for assessment of psychosocial factors causing stress and illness. Somatoform disorder is a chronic debilitating illness and stress increases disability in it. Yet, studies in this area is sparse. Aim of the study: The aim of this study was to assess if there is an association of stress with depression in patients of somatoform disorder. Materials and methods: A hospital based cross sectional study was conducted in a tertiary healthcare setup of Assam. The sociodemographic and clinical variables of patients of somatoform disorder diagnosed as per ICD-10 were collected. Stress was assessed using the presumptive stressful life events scale and severity of depression was evaluated in patients with co-morbid depression using HAM-D scale. Results: Majority were between 50-60 years of age (32%), home-maker (28%), from rural area (58%) and had presented with a duration of illness between 0-5yrs (43%) and 30% belonged to the somatization disorder group. Depression was present in 55% and mild depression was most common. Financial stress was most commonly reported stressful life event; stress was found to have a strong positive correlation to presence and severity of depression (p-value<0.01). 'Presence of unmarried adult son/daughter' as a self-reported life stressor was a novel finding in this study. Conclusion: Presence of stress amplifies the chances and severity of depression in patients of somatoform disorder. Thus, management of stress is an integral part in management of these patients.