Coping with Illness: Insight from the Bhagavad Gita

The Shrimad Bhagavad Gita enlightens everyone on how to cope up with various situations in life. It uses the conversation between Lord Krishna and Arjuna to highlight initial negative coping mechanisms exhibited by the latter. It goes on to showcase positive coping skills suggested by Lord Krishna and implemented by Arjuna. The Bhagavad Gita, through this case-based methodology, teaches us how to cope with a demanding situation. Diabetes is a lifestyle disease, which warrants a thorough change in one\u27s lifestyle, including changes in basic activities such as diet and exercise. This brief communication utilizes the teachings of Bhagavad Gita to help in coping with illness, especially chronic illness such as diabetes. The article cites verses from the Bhagavad Gita to show how one may cope with the stress of illness such as diabetes

Point Mutation Specific Antibodies in B-Cell and T-Cell Lymphomas and Leukemias: Targeting IDH2, KRAS, BRAF and Other Biomarkers RHOA, IRF8, MYD88, ID3, NRAS, SF3B1 and EZH2

B-cell and T-cell lymphomas and leukemias often have distinct genetic mutations that are diagnostically defining or prognostically significant. A subset of these mutations consists of specific point mutations, which can be evaluated using genetic sequencing approaches or point mutation specific antibodies. Here, we describe genes harboring point mutations relevant to B-cell and T-cell malignancies and discuss the current availability of these targeted point mutation specific antibodies. We also evaluate the possibility of generating novel antibodies against known point mutations by computationally assessing for chemical and structural features as well as epitope antigenicity of these targets. Our results not only summarize several genetic mutations and identify existing point mutation specific antibodies relevant to hematologic malignancies, but also reveal potential underdeveloped targets which merit further study

Point Mutation Specific Antibodies in B-Cell and T-Cell Lymphomas and Leukemias: Targeting IDH2, KRAS, BRAF and Other Biomarkers RHOA, IRF8, MYD88, ID3, NRAS, SF3B1 and EZH2.

B-cell and T-cell lymphomas and leukemias often have distinct genetic mutations that are diagnostically defining or prognostically significant. A subset of these mutations consists of specific point mutations, which can be evaluated using genetic sequencing approaches or point mutation specific antibodies. Here, we describe genes harboring point mutations relevant to B-cell and T-cell malignancies and discuss the current availability of these targeted point mutation specific antibodies. We also evaluate the possibility of generating novel antibodies against known point mutations by computationally assessing for chemical and structural features as well as epitope antigenicity of these targets. Our results not only summarize several genetic mutations and identify existing point mutation specific antibodies relevant to hematologic malignancies, but also reveal potential underdeveloped targets which merit further study

A meta-analysis of SARS-CoV-2 patients identifies the combinatorial significance of D-dimer, C-reactive protein, lymphocyte, and neutrophil values as a predictor of disease severity.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to be the causative agent of COVID-19, has led to a worldwide pandemic. At presentation, individual clinical laboratory blood values, such as lymphocyte counts or C-reactive protein (CRP) levels, may be abnormal and associated with disease severity. However, combinatorial interpretation of these laboratory blood values, in the context of COVID-19, remains a challenge.MethodsTo assess the significance of multiple laboratory blood values in patients with SARS-CoV-2 and develop a COVID-19 predictive equation, we conducted a literature search using PubMed to seek articles that included defined laboratory data points along with clinical disease progression. We identified 9846 papers, selecting primary studies with at least 20 patients for univariate analysis to identify clinical variables predicting nonsevere and severe COVID-19 cases. Multiple regression analysis was performed on a training set of patient studies to generate severity predictor equations, and subsequently tested on a validation cohort of 151 patients who had a median duration of observation of 14 days.ResultsTwo COVID-19 predictive equations were generated: one using four variables (CRP, D-dimer levels, lymphocyte count, and neutrophil count), and another using three variables (CRP, lymphocyte count, and neutrophil count). In adult and pediatric populations, the predictive equations exhibited high specificity, sensitivity, positive predictive values, and negative predictive values.ConclusionUsing the generated equations, the outcomes of COVID-19 patients can be predicted using commonly obtained clinical laboratory data. These predictive equations may inform future studies evaluating the long-term follow-up of COVID-19 patients

A meta-analysis of SARS-CoV-2 patients identifies the combinatorial significance of D-dimer, C-reactive protein, lymphocyte, and neutrophil values as a predictor of disease severity.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to be the causative agent of COVID-19, has led to a worldwide pandemic. At presentation, individual clinical laboratory blood values, such as lymphocyte counts or C-reactive protein (CRP) levels, may be abnormal and associated with disease severity. However, combinatorial interpretation of these laboratory blood values, in the context of COVID-19, remains a challenge.MethodsTo assess the significance of multiple laboratory blood values in patients with SARS-CoV-2 and develop a COVID-19 predictive equation, we conducted a literature search using PubMed to seek articles that included defined laboratory data points along with clinical disease progression. We identified 9846 papers, selecting primary studies with at least 20 patients for univariate analysis to identify clinical variables predicting nonsevere and severe COVID-19 cases. Multiple regression analysis was performed on a training set of patient studies to generate severity predictor equations, and subsequently tested on a validation cohort of 151 patients who had a median duration of observation of 14 days.ResultsTwo COVID-19 predictive equations were generated: one using four variables (CRP, D-dimer levels, lymphocyte count, and neutrophil count), and another using three variables (CRP, lymphocyte count, and neutrophil count). In adult and pediatric populations, the predictive equations exhibited high specificity, sensitivity, positive predictive values, and negative predictive values.ConclusionUsing the generated equations, the outcomes of COVID-19 patients can be predicted using commonly obtained clinical laboratory data. These predictive equations may inform future studies evaluating the long-term follow-up of COVID-19 patients

Reverse turn induced π-facial selectivity during polyaniline-supported cobalt(II) salen catalyzed aerobic epoxidation of N-cinnamoyl L-proline derived peptides

A novel chemo- and diastereoselective aerobic epoxidation of the N-cinnamoyl peptides catalyzed by polyaniline-supported cobalt(II) salen (PASCOS) is described. The N-cinnamoyl proline derived peptides 1 show a high π-facial selectivity during these epoxidations. The origin of this diastereoselectivity in 1 has been attributed to (i) the propensity of the N-cinnamoyl proline amide to exist predominantly as trans rotamer in CDCl3, DMSO-d6, and CH3CN medium and (ii) existence of these peptides as organized structures (γ- and β-turns) due to the presence of intramolecular hydrogen bonds. An extensive solution NMR and MD simulation study on 1d and 1f indicates that the origin of the high π-facial selectivity is due to the well-defined γ- and β-turns which result in the hindrance of one face of the cinnamoyl double bond in the transition state of the epoxidation reaction

Synthesis of a novel cis-proline-derived cyclic type VI β-turn mimic via ring-closing metathesis

A cis-proline derived cyclic mimic of a type VI β-turn is synthesized via a ring-closing metathesis reaction. The solution NMR conformational study indicates that the major conformer of the cyclic peptide adopts a type VIa β-turn in CDCl3 and a type VIb β-turn in DMSO-d6