Cooperative and individualistic functions of the microRNAs in the miR-23a~27a~24-2 cluster and its implication in human diseases

The small RNA molecules of about 19-22 nucleotides in length, aptly called microRNAs, perform the task of gene regulation in the cell. Interestingly, till the early nineties very little was known about them but eventually, the microRNAs have become forefront in the area of research. The huge number of microRNAs plus each one of them targeting a vast number of related as well as unrelated genes makes them very interesting molecules to study. To add to the mystery of miRNAs is the fact that the same miRNA can have antagonizing role in two different cell types i.e. in one cell type; the miRNA promotes proliferation whereas in another cell type the same miRNA inhibits proliferation. Another remarkable aspect of the microRNAs is that many of them exist in clusters. In humans alone, out of 721 microRNAs known, 247 of them occur in 64 clusters at an inter-miRNA distance of less than 5000bp. The reason for this clustering of miRNAs is not fully understood but since the miRNA clusters are evolutionary conserved, their significance cannot be ruled out. The objective of this review is to summarize the recent progress on the functional characterization of miR-23a~27a~24-2 cluster in humans in relation to various health and diseased conditions and to highlight the cooperative effects of the miRNAs of this cluster

Assessment of Water Quality in Harike Wetland - A Review

Harike, designated as Ramsar site, is the largest manmade riverine wetland in North India.  It came into existence in 1952 with the construction of barrage near confluence of rivers Sutlej and Beas. It has high ecological significance as it is the habitat of diverse flora and fauna, source of food for animals and humans and plays an important role in underground water recharge. Despite all these diverse functions, the wetland is facing a threat of extinction because of increasing anthropogenic pressure from industrial development, agriculture and over extraction of water for irrigation.  A number of studies have been undertaken to assess the water quality of Harike and the water is found to be unsafe for aquatic life as well as for human consumption. The review deals with the status of harike wetland in terms of water quality and causes of wetland loss. It also provides an overview of the methodology employed for physicochemical and biological analysis, heavy metal determination and use of remote sensing techniques for monitoring of various water quality parameters

Less is More -- Towards parsimonious multi-task models using structured sparsity

Model sparsification in deep learning promotes simpler, more interpretable models with fewer parameters. This not only reduces the model's memory footprint and computational needs but also shortens inference time. This work focuses on creating sparse models optimized for multiple tasks with fewer parameters. These parsimonious models also possess the potential to match or outperform dense models in terms of performance. In this work, we introduce channel-wise l1/l2 group sparsity in the shared convolutional layers parameters (or weights) of the multi-task learning model. This approach facilitates the removal of extraneous groups i.e., channels (due to l1 regularization) and also imposes a penalty on the weights, further enhancing the learning efficiency for all tasks (due to l2 regularization). We analyzed the results of group sparsity in both single-task and multi-task settings on two widely-used Multi-Task Learning (MTL) datasets: NYU-v2 and CelebAMask-HQ. On both datasets, which consist of three different computer vision tasks each, multi-task models with approximately 70% sparsity outperform their dense equivalents. We also investigate how changing the degree of sparsification influences the model's performance, the overall sparsity percentage, the patterns of sparsity, and the inference time.Comment: Under revie

Multi-Task Meta Learning: learn how to adapt to unseen tasks

This work proposes Multi-task Meta Learning (MTML), integrating two learning paradigms Multi-Task Learning (MTL) and meta learning, to bring together the best of both worlds. In particular, it focuses simultaneous learning of multiple tasks, an element of MTL and promptly adapting to new tasks, a quality of meta learning. It is important to highlight that we focus on heterogeneous tasks, which are of distinct kind, in contrast to typically considered homogeneous tasks (e.g., if all tasks are classification or if all tasks are regression tasks). The fundamental idea is to train a multi-task model, such that when an unseen task is introduced, it can learn in fewer steps whilst offering a performance at least as good as conventional single task learning on the new task or inclusion within the MTL. By conducting various experiments, we demonstrate this paradigm on two datasets and four tasks: NYU-v2 and the taskonomy dataset for which we perform semantic segmentation, depth estimation, surface normal estimation, and edge detection. MTML achieves state-of-the-art results for three out of four tasks for the NYU-v2 dataset and two out of four for the taskonomy dataset. In the taskonomy dataset, it was discovered that many pseudo-labeled segmentation masks lacked classes that were expected to be present in the ground truth; however, our MTML approach was found to be effective in detecting these missing classes, delivering good qualitative results. While, quantitatively its performance was affected due to the presence of incorrect ground truth labels. The the source code for reproducibility can be found at https://github.com/ricupa/MTML-learn-how-to-adapt-to-unseen-tasks

Role of intrauterine tubo-peritoneal insemination and intrauterine insemination in the treatment of infertility

Background: Infertility management has become more substantial and relevant with an increase in the number of infertile patients as well as advances in the science of reproduction. The objective of our study was to assess the role of intrauterine tuboperitoneal insemination (IUTPI) and intrauterine insemination (IUI) in the treatment of infertile patients.Methods: 236 infertile patients, 118 in each group attending the infertility clinic, after applying both inclusion and exclusion criteria were enrolled in the present study. Patients in each study group were given clomiphene citrate for ovarian stimulation followed by injection hCG for triggering ovulation. Insemination with washed husband’s sperm was performed about 36-40 hours after hCG administration, using 10ml of  inseminate in IUTPI and 0.5ml inseminate in IUI. The patient was then called after 2 weeks for urine pregnancy test (UPT) which, if positive was considered as clinical pregnancy.Results: Out of the total 236 cases, 42 cases had a positive outcome. Out of these 42 positive cases, 27 were from IUTPI group whereas 15 from IUI group. The pregnancy rate was 22.88% in IUTPI and 12.71% in IUI (p=0.039), which was a statistically significant difference. Endometrial thickness, preovulatory follicle number and prewash sperm motility significantly affected positive outcome in IUTPI. Factors like patient’s age, BMI<25, bilateral patent tubes and decreased duration of infertility also positively affected the treatment outcome.Conclusions: Our study found IUTPI to have better pregnancy rate compared to IUI. IUTPI may become a first line option for treatment of infertile patients

Functional Knowledge Transfer with Self-supervised Representation Learning

This work investigates the unexplored usability of self-supervised representation learning in the direction of functional knowledge transfer. In this work, functional knowledge transfer is achieved by joint optimization of self-supervised learning pseudo task and supervised learning task, improving supervised learning task performance. Recent progress in self-supervised learning uses a large volume of data, which becomes a constraint for its applications on small-scale datasets. This work shares a simple yet effective joint training framework that reinforces human-supervised task learning by learning self-supervised representations just-in-time and vice versa. Experiments on three public datasets from different visual domains, Intel Image, CIFAR, and APTOS, reveal a consistent track of performance improvements on classification tasks during joint optimization. Qualitative analysis also supports the robustness of learnt representations. Source code and trained models are available on GitHub.Comment: Accepted at IEEE International Conference on Image Processing (ICIP 2023

Utility of Serum Neopterin and Serum IL-2 Receptor Levels to Predict Absolute CD4 T Lymphocyte Count in HIV Infected Cases

A prospective study was carried out to evaluate the efficacy of serum neopterin and soluble IL-2 receptor (sIL-2R) concentrations in comparison to CD4 count to study the progression of HIV disease and monitor response to ART in HIV cases. One hundred newly diagnosed HIV seropositive subjects were recruited. CD4 counts were determined by FACS system. Serum neopterin and sIL-2R levels were measured using enzyme immunoassay. In our study, levels of neopterin and sIL-2R were significantly higher in subjects with CD4 <200 cells/μL (with S. neopterin levels of >25.1 nmol/L and sIL-2R levels of >47.1 pM as cutoff values for CD4 <200 cells/μL) compared to those in subjects with CD4 >200 cells/μL at baseline which indicate that these markers can be utilized for initiation of ART in HIV cases. The levels of these markers decreased significantly after initiation of ART. In patients with CD4 >200 cells/μL, these markers are helpful in predicting disease progression

Small Interfering RNA against Transcription Factor STAT6 Leads to Increased Cholesterol Synthesis in Lung Cancer Cell Lines

STAT6 transcription factor has become a potential molecule for therapeutic intervention because it regulates broad range of cellular processes in a large variety of cell types. Although some target genes and interacting partners of STAT6 have been identified, its exact mechanism of action needs to be elucidated. In this study, we sought to further characterize the molecular interactions, networks, and functions of STAT6 by profiling the mRNA expression of STAT6 silenced human lung cells (NCI-H460) using microarrays. Our analysis revealed 273 differentially expressed genes after STAT6 silencing. Analysis of the gene expression data with Ingenuity Pathway Analysis (IPA) software revealed Gene expression, Cell death, Lipid metabolism as the functions associated with highest rated network. Cholesterol biosynthesis was among the most enriched pathways in IPA as well as in PANTHER analysis. These results have been validated by real-time PCR and cholesterol assay using scrambled siRNA as a negative control. Similar findings were also observed with human type II pulmonary alveolar epithelial cells, A549. In the present study we have, for the first time, shown the inverse relationship of STAT6 with the cholesterol biosynthesis in lung cancer cells. The present findings are potentially significant to advance the understanding and design of therapeutics for the pathological conditions where both STAT6 and cholesterol biosynthesis are implicated viz. asthma, atherosclerosis etc

El tubo endotraqueal no protege contra la aspiración de un cuerpo extraño hacia adentro de la tráquea: reporte de caso

ResumenDescribimos el caso del corte inadvertido de una sonda introducida por la nariz para medir la temperatura intraquirúrgica, en un paciente de 26años. El segmento faltante de la sonda se recuperó de la tráquea, un sitio inusual en vista de la presencia del tubo endotraqueal con balón. Este caso sirve para recordar que el tubo endotraqueal con balón no protege necesariamente a la vía aérea contra la aspiración de cuerpos extraños sólidos provenientes de la vía oral o la vía nasal.AbstractWe describe a case of a 26year old patient wherein a temperature probe introduced through the nose for intra operative temperature monitoring was inadvertently cut during the ongoing surgical procedure. The missing segment of the probe was retrieved from the trachea which formed an unusual site in spite of the presence of a cuffed endotracheal tube. The present case serves as a reminder that cuffed endotracheal tube does not necessarily protect the airway from aspiration of solid foreign bodies from the oral or nasal airway

Higher susceptibility of males to bleomycin-induced pulmonary inflammation is associated with sex-specific transcriptomic differences in myeloid cells

Idiopathic pulmonary fibrosis, a condition with likely genetic and environmental etiology, is relatively more prevalent with poor prognosis in human males. However, the underlying mechanisms for these gender-associated differences in the severity of fibrosis remain unknown. Here, we tested the hypothesis that the transcriptomic repertoire of myeloid cells determines the higher susceptibility of male mice to bleomycin (BLM)-induced lung fibrosis. Adult mice were oropharyngeally challenged with saline or BLM. Lung injury, inflammation, and fibrosis outcomes were assessed, and airspace myeloid-cells were subjected to RNA-sequencing. As compared with the female mice, the male mice manifested significantly increased lung injury, inflammation, proinflammatory cytokines (IL-6, IL-1β, IL-7, and IP-10), and fibrosis in response to BLM challenge. Interestingly, several pro-inflammatory and extracellular matrix-associated genes were significantly up-regulated in male myeloid-cells compared to female myeloid-cells in the saline-control group. Similarly, BLM challenge resulted in greater pro-inflammatory and pro-fibrotic transcriptomic changes in male compared to female myeloid cells. On the other hand, anti-inflammatory and regulatory cytokine, Il10 and Ifng respectively, were uniquely upregulated in BLM-challenged female but not in male myeloid cells when compared to their respective saline-control groups. Further, cross-sex bone marrow transplantation experiments revealed that male hematopoietic progenitor cells (HPCs) increased the granulocytic infiltration in female mice while female HPCs decreased the granulocytic infiltration in male mice post-BLM challenge. These findings suggest that there are inherent transcriptomic differences between the male and female lung myeloid cells and that the pro-inflammatory nature of male myeloid cells is sufficient to increase the susceptibility of female mice to BLM-induced inflammation