Paradigm Shifts in Mast Cell and Basophil Biology and Function: An Emerging View of Immune Regulation in Health and Disease

Phytoflavonoids as alternative therapeutic effect for melanoma: Integrative Network pharmacology, molecular dynamics and drug-likeness profiling for lead discovery

Melanoma, an aggressive skin cancer, poses significant therapeutic challenges due to its resistance to conventional therapies and high metastatic potential. From this perspective, phytoflavonoids from different medicinal and aromatic plants gained attention due to their diverse multimodal anticancer effects with higher antioxidant and anti-inflammatory properties. This study explores phytoflavonoid potency against melanoma via a computer-aided drug design (CADD) platform. Using the core moiety of flavonoids (flavan), four most putative targets, such as cyclin-dependent kinases 1 and 5 (CDK1, CDK5), cell division cycles 25B and 225 C (CDC25B, and CDC225C), have been identified through a network pharmacology approach using TNMplot datasets (GenChip and RNA sequence). Further, 44 phytoflavonoids were selected from extensive literature, and molecular docking studies were carried out against four targets along with standard drugs using AutoDock 4.2 software. Subsequently, physicochemical, toxicity, pharmacokinetics, and drug-ability profiles of phytoflavonoids were predicted. Based on potency and drug-ability, we have selected 'CDK1-naringenin' with the standard drug complex, 'CDK1-dinaciclib,' for molecular dynamic simulation at 100 nanoseconds using GROMACS 2020 software. Based on potency (average docking score: 8.35 kcal/mol.), physicochemical properties (obeyed Lipinski rule of five), toxicity (class-IV), fifty percent lethal dose (2000 mg/kg), bioavailability (0.55), drug-likeness score (0.82), along with ideal pharmacokinetics profiles and higher protein-ligand stability, naringenin is considered as a potential and non-toxic anticancer candidate to be used for melanoma as alternative or complementary agent. The integrative and systematic analyses not only highlight the potential of phytoflavonoids but also select the potential lead from the library within limited resources to accelerate the current anticancer drug discovery process.

TEMR: Trans-ethnic mendelian randomization method using large-scale GWAS summary datasets

Available large-scale genome-wide association study (GWAS) summary datasets predominantly stem from European populations, while sample sizes for other ethnicities, notably Central/South Asian, East Asian, African, Hispanic, etc., remain comparatively limited, resulting in low precision of causal effect estimations within these ethnicities when using Mendelian randomization (MR). In this paper, we propose a trans-ethnic MR method, TEMR, to improve the statistical power and estimation precision of MR in a target population that is underrepresented, using trans-ethnic large-scale GWAS summary datasets. TEMR incorporates trans-ethnic genetic correlation coefficients through a conditional likelihood-based inference framework, producing calibrated p values with substantially improved MR power. In the simulation study, compared with other existing MR methods, TEMR exhibited superior precision and statistical power in causal effect estimation within the target populations. Finally, we applied TEMR to infer causal relationships between concentrations of 16 blood biomarkers and the risk of developing five diseases (hypertension, ischemic stroke, type 2 diabetes, schizophrenia, and major depression disorder) in East Asian, African, and Hispanic/Latino populations, leveraging biobank-scale GWAS summary data obtained from individuals of European descent. We found that the causal biomarkers were mostly validated by previous MR methods, and we also discovered 17 causal relationships that were not identified using previously published MR methods.

Unveiling the influence of circulating immune cells count on type 1 diabetes: Insight from bidirectional Mendelian randomization

Observational studies have demonstrated an association between circulating immune cell and type 1 diabetes (T1D) risk. However, it is unknown whether this relationship is causal. Herein, we adopted a 2-sample bidirectional Mendelian randomization study to figure out whether circulating immune cell profiles causally impact T1D liability. Summary statistical data were obtained from genome-wide association study (GWAS) to investigate the causal relationship between white cell (WBC) count, 5 specific WBC count, and lymphocyte subtypes cell count and T1D risk. After false discovery rate (FDR) correction, the results indicated that lower lymphocyte cell count (odds ratio [OR] per 1 standard deviation [SD] decrease = 0.746, 95% confidence interval (CI): 0.673-0.828, PFDR = 0.036), and basophil cell count (OR per 1 SD decrease = 0.808, 95% CI: 0.700-0.932, PFDR = 0.010) were causally associated with T1D susceptibility. However, the absolute count of WBC, monocyte, neutrophil, eosinophil, and lymphocyte subtypes cell had no statistically significant effect on T1D risk. Taken together, this study indicates suggestive association between circulating immune cell count and T1D. Moreover, lower numbers of circulating lymphocyte and basophil cell were associated with the increased risk of T1D, which confirmed the immunity predisposition for T1D.

The Value of a Complete Blood Count (CBC) for Sepsis Diagnosis and Prognosis

Sepsis represents an important global health burden due to its high mortality and morbidity. The rapid detection of sepsis is crucial in order to prevent adverse outcomes and reduce mortality. However, the diagnosis of sepsis is still challenging and many efforts have been made to identify reliable biomarkers. Unfortunately, many investigated biomarkers have several limitations that do not support their introduction in clinical practice, such as moderate diagnostic and prognostic accuracy, long turn-around time, and high-costs. Complete blood count represents instead a precious test that provides a wealth of information on individual health status. It can guide clinicians to early-identify patients at high risk of developing sepsis and to predict adverse outcomes. It has several advantages, being cheap, easy-to-perform, and available in all wards, from the emergency department to the intensive care unit. Noteworthy, it represents a first-level test and an alteration of its parameters must always be considered within the clinical context, and the eventual suspect of sepsis must be confirmed by more specific investigations. In this review, we describe the usefulness of basic and new complete blood count parameters as diagnostic and prognostic biomarkers of sepsis.