RESUMO
Plant insect interactions are governed by various factors. Nectar availability and floral nectar composition play a significant role in deciding the pollinator pool that visits a particular plant species. This study investigates nectar sugar composition and volume from three endemic species from Western Ghats of India viz. Canthium dicoccum (Gaertn.) Teijsm. & Binn., Ligustrum perrottetii A. DC., and Wendlandia thyrsoidea (Roth) Steud., in their natural habitats. Our results demonstrate intraspecific variation in nectar sugar composition in these endemic plant species. Fructose, mannose and glucose sugars were found in the nectar of all three species. In addition to these three, arabinose was found in Ligustrum and sucrose in Canthium. Nectar volume showed variations in bagged and unbagged conditions. The highest average nectar quantity was found in Canthium (1.27â µl/flower), followed by Ligustrum (0. 31â µl/flower), and Wendlandia (0.14â µl/flower). Floral visitor diversity with a specific emphasis on butterflies showed the highest number of visitors on Ligustrum i. e., 42 out of 45 total butterfly species across all three plant species. This is the first report of standing nectar crop and nectar-sugar composition data compiled for these plant species.
Assuntos
Borboletas , Rubiaceae , Animais , Biodiversidade , Carboidratos , Néctar de Plantas , Plantas , AçúcaresRESUMO
Cellular resistance in tumour cells to different therapeutic approaches has been a limiting factor in the curative treatment of cancer. Resistance to therapeutic radiation is a common phenomenon which significantly reduces treatment options and impacts survival. One of the mechanisms of acquiring resistance to ionizing radiation is the overexpression or activation of various oncogenes like the EGFR (epidermal growth factor receptor), RAS (rat sarcoma) oncogene or loss of PTEN (phosphatase and tensin homologue) which in turn activates the phosphatidyl inositol 3-kinase/protein kinase B (PI3-K)/AKT pathway responsible for radiation resistance in various tumours. Blocking the pathway enhances the radiation response both in vitro and in vivo. Due to the differential activation of this pathway (constitutively activated in tumour cells and not in the normal host cells), it is an excellent candidate target for molecular targeted therapy to enhance radiation sensitivity. In this regard, HIV protease inhibitors (HPIs) known to interfere with PI3-K/AKT signaling in tumour cells, have been shown to sensitize various tumour cells to radiation both in vitro and in vivo. As a result, HPIs are now being investigated as possible radiosensitizers along with various chemotherapeutic drugs. This review describes the mechanisms by which PI3-K/AKT pathway causes radioresistance and the role of HIV protease inhibitors especially nelfinavir as a potential candidate drug to target the AKT pathway for overcoming radioresistance and its use in various clinical trials for different malignancies.
Assuntos
Inibidores da Protease de HIV/uso terapêutico , Neoplasias/tratamento farmacológico , Neoplasias/radioterapia , Proteína Oncogênica v-akt/genética , Radiossensibilizantes/uso terapêutico , Receptores ErbB/biossíntese , Humanos , Neoplasias/patologia , Proteína Oncogênica p21(ras)/biossíntese , Proteína Oncogênica v-akt/antagonistas & inibidores , PTEN Fosfo-Hidrolase/biossíntese , Fosfatidilinositol 3-Quinases/genética , Radiação Ionizante , Transdução de Sinais/efeitos dos fármacosRESUMO
Introduction: Stigma contributes to a significant part of the burden of schizophrenia (SCZ), therefore reducing false positives from the diagnosis would be liberating for the individuals with SCZ and desirable for the clinicians. The stigmatization associated with schizophrenia advocates the need for high-precision diagnosis. In this study, we present an ensemble learning-based approach for high-precision diagnosis of SCZ using peripheral blood gene expression profiles. Methodology: The machine learning (ML) models, support vector machines (SVM), and prediction analysis for microarrays (PAM) were developed using differentially expressed genes (DEGs) as features. The SCZ samples were classified based on a voting ensemble classifier of SVM and PAM. Further, microarray-based learning was used to classify RNA sequencing (RNA-Seq) samples from our case-control study (Pune-SCZ) to assess cross-platform compatibility. Results: Ensemble learning using ML models resulted in a significantly higher precision of 80.41% (SD: 0.04) when compared to the individual models (SVM-radial: 71.69%, SD: 0.04 and PAM 77.20%, SD: 0.02). The RNA sequencing samples from our case-control study (Pune-SCZ) resulted in a moderate precision (59.92%, SD: 0.05). The feature genes used for model building were enriched for biological processes such as response to stress, regulation of the immune system, and metabolism of organic nitrogen compounds. The network analysis identified RBX1, CUL4B, DDB1, PRPF19, and COPS4 as hub genes. Conclusion: In summary, this study developed robust models for higher diagnostic precision in psychiatric disorders. Future efforts will be directed towards multi-omic integration and developing "explainable" diagnostic models.
RESUMO
Schizophrenia is a disorder that is characterized by delusions, hallucinations, disorganized speech or behavior, and socio-occupational impairment. The duration of observation and variability in symptoms can make the accurate diagnosis difficult. Identification of biomarkers for schizophrenia (SCZ) can help in early diagnosis, ascertaining the diagnosis, and development of effective treatment strategies. Here we review peripheral blood-based gene expression studies for identification of gene expression biomarkers for SCZ. A literature search was carried out in PubMed and Web of Science databases for blood-based gene expression studies in SCZ. A list of differentially expressed genes (DEGs) was compiled and analyzed for overlap with genetic markers, differences based on drug status of the participants, functional enrichment, and for effect of antipsychotics. This literature survey identified 61 gene expression studies. Seventeen out of these studies were based on expression microarrays. A comparative analysis of the DEGs (n = 227) from microarray studies revealed differences between drug-naive and drug-treated SCZ participants. We found that of the 227 DEGs, 11 genes (ACOT7, AGO2, DISC1, LDB1, RUNX3, SIGIRR, SLC18A1, NRG1, CHRNB2, PRKAB2, and ZNF74) also showed genetic and epigenetic changes associated with SCZ. Functional enrichment analysis of the DEGs revealed dysregulation of proline and 4-hydroxyproline metabolism. Also, arginine and proline metabolism was the most functionally enriched pathway for SCZ in our analysis. Follow-up studies identified effect of antipsychotic treatment on peripheral blood gene expression. Of the 27 genes compiled from the follow-up studies AKT1, DISC1, HP, and EIF2D had no effect on their expression status as a result of antipsychotic treatment. Despite the differences in the nature of the study, ethnicity of the population, and the gene expression analysis method used, we identified several coherent observations. An overlap, though limited, of genetic, epigenetic and gene expression changes supports interplay of genetic and environmental factors in SCZ. The studies validate the use of blood as a surrogate tissue for biomarker analysis. We conclude that well-designed cohort studies across diverse populations, use of high-throughput sequencing technology, and use of artificial intelligence (AI) based computational analysis will significantly improve our understanding and diagnostic capabilities for this complex disorder.
RESUMO
Sister chromatid cohesion is essential for tension-sensing mechanisms that monitor bipolar attachment of replicated chromatids in metaphase. Cohesion is mediated by the association of cohesins along the length of sister chromatid arms. In contrast, centromeric cohesin generates intrastrand cohesion and sister centromeres, while highly cohesin enriched, are separated by >800 nm at metaphase in yeast. Removal of cohesin is necessary for sister chromatid separation during anaphase, and this is regulated by evolutionarily conserved polo-like kinase (Cdc5 in yeast, Plk1 in humans). Here we address how high levels of cohesins at centromeric chromatin are removed. Cdc5 associates with centromeric chromatin and cohesin-associated regions. Maximum enrichment of Cdc5 in centromeric chromatin occurs during the metaphase-to-anaphase transition and coincides with the removal of chromosome-associated cohesin. Cdc5 interacts with cohesin in vivo, and cohesin is required for association of Cdc5 at centromeric chromatin. Cohesin removal from centromeric chromatin requires Cdc5 but removal at distal chromosomal arm sites does not. Our results define a novel role for Cdc5 in regulating removal of centromeric cohesins and faithful chromosome segregation.