Exploring the crosstalk between long non-coding RNAs and microRNAs to unravel potential prognostic and therapeutic biomarkers in ß-thalassemia.

ß-thalassemia is a prevalent monogenic disorder characterized by reduced or absent synthesis of the ß-globin chain. Although great effort has been made to ameliorate the disease severity of ß-thalassemic patients, progress has been stymied due to limited understanding of the detailed molecular mechanism of disease pathogenesis. Recently, non-coding RNAs have been established as key players in regulating various physiological and pathological processes. Many ncRNAs are involved in hematopoiesis and erythroid development. Furthermore, various studies have also reported the complex interplay between different ncRNAs, such as miRNA, lncRNAs, etc. in regulating disease progression and pathogenesis. Both lncRNAs and miRNAs have been identified as independent regulators of globin gene expression and are intricately involved in disease pathogenesis; yet accumulating evidence suggests that the cross-talk between lncRNAs and miRNAs is intricately involved in the underlying globin gene expression, fine-tuning the effect of their independent regulation. In this review, we summarize the current progress of research on the roles of lncRNAs and miRNAs implicated in ß-thalassemia disease, including their interactions and regulatory networks. This can provide important insights into the detailed epigenetic regulation of globin gene switching and has the potential to develop novel therapeutic approaches against ß-thalassemia.

Deciphering the intricate dynamics of inflammasome regulation in visceral and post-kala-azar dermal leishmaniasis: A meta-analysis of consistencies.

Post Kala-azar dermal leishmaniasis (PKDL) arises as a significant dermal sequel following Visceral leishmaniasis (VL) caused by protozoan parasite Leishmania donovani (LD). PKDL acts as a significant constrain for VL elimination serving as a crucial reservoir for LD. PKDL patients exhibit depigmented macular and papular lesions on their skin, which results in social discrimination due to loss of natural skin color. Inflammatory reactions, prevalent in both VL and PKDL, potentially lead to tissue damage in areas harboring the parasite. Disruption of the immune-inflammasomal network not only facilitates LD persistence but also leads to the skin hypopigmentation seen in PKDL, impacting social well-being. Activation of inflammasomal markers like STAT1, NLRP1, NLRP3, AIM2, CASP11, and NLRP12 have been identified as a common host-defense mechanism across various Leishmania infections. Conversely, Leishmania modulates inflammasome activation to sustain its presence within the host. Nevertheless, in specific instances of Leishmania infection, inflammasome activation can worsen disease pathology by promoting parasite proliferation and persistence. This study encompasses recent transcriptomic analyses conducted between 2016 and 2023 on human and murine subjects afflicted with VL/PKDL, elucidating significant alterations in inflammasomal markers in both conditions. It offers a comprehensive understanding how these markers contribute in disease progression, drawing upon available literature for logical analysis. Furthermore, our analysis identifies validated miRNA network that could potentially disrupt this crucial immune-inflammasomal network, thereby offering a plausible explanation on how secreted LD-factors could enable membrane-bound LD, isolated from the host cytoplasm, to modulate cytoplasmic inflammasomal markers. Insights from this study could guide the development of host-directed therapeutics to impede transmission and address hypopigmentation, thereby mitigating the social stigma associated with PKDL.

Full genomic sequence of the HLA-A*02:01:01:241 allele identified by next-generation sequencing.

HLA-A*02:01:01:241 differs from HLA-A*02:01:01:01 by a single nucleotide substitution at position 178 in intron 1.

Identification of hub genes to determine drug-disease correlation in breast carcinomas.

The exact molecular mechanism underlying the heterogeneous drug response against breast carcinoma remains to be fully understood. It is urgently required to identify key genes that are intricately associated with varied clinical response of standard anti-cancer drugs, clinically used to treat breast cancer patients. In the present study, the utility of transcriptomic data of breast cancer patients in discerning the clinical drug response using machine learning-based approaches were evaluated. Here, a computational framework has been developed which can be used to identify key genes that can be linked with clinical drug response and progression of cancer, offering an immense opportunity to predict potential prognostic biomarkers and therapeutic targets. The framework concerned utilizes DeSeq2, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape, and machine learning techniques to find these crucial genes. Total RNA extraction and qRT-PCR were performed to quantify relative expression of few hub genes selected from the networks. In our study, we have experimentally checked the expression of few key hub genes like APOA2, DLX5, APOC3, CAMK2B, and PAK6 that were predicted to play an immense role in breast cancer tumorigenesis and progression in response to anti-cancer drug Paclitaxel. However, further experimental validations will be required to get mechanistic insights of these genes in regulating the drug response and cancer progression which will likely to play pivotal role in cancer treatment and precision oncology.