BioGenex (India)

Hematopoietic stem cells (HSCs) sustain lifelong hematopoiesis through their capacity for self-renewal and multilineage differentiation. However, the isolation and functional characterization of HSCs remain challenging due to their cellular heterogeneity and dynamically regulated transcriptional and epigenetic landscapes. Advances in experimental and computational biology, including single-cell RNA sequencing (scRNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), network inference algorithms, and machine learning, have improved our ability to resolve transcriptional states, trace lineage trajectories, and reconstruct gene regulatory networks (GRN) at single-cell resolution. These approaches enable the discovery of novel HSC subtypes and regulatory factors, and facilitate the integration of multi-omics data to uncover epigenetic and transcriptional mechanisms that drive stem cell fate decisions. Additionally, machine learning models trained on high-throughput datasets provide predictive power for identifying novel enhancers, transcription factors, and therapeutic targets. This review underscores the synergistic role of computational tools in deciphering HSC biology and highlights their potential to improve stem cell therapies and precision treatments for hematologic disorders.

To study consumer knowledge and use of food labels. A cross-sectional study employing both quantitative and qualitative methods. Intercept interviews were conducted with 1832 consumers at supermarket sites selected using a stratified random sampling procedure. This information was triangulated with twenty-one focus group discussions. New Delhi and Hyderabad, two metro-cities from north and south India. Adolescent (10-19 years), adult (20-59 years) and elderly (≥60 years) consumers. While the national urban literacy rate is 84 %, about 99 % of the study participants were educated. About 45 % reported that they buy pre-packaged foods once weekly and about a fifth buy them every day. Taste, quality, convenience and ease of use are the main reasons for buying pre-packaged foods. Although 90 % of consumers across the age groups read food labels, the majority (81 %) looked only for the manufacturing date or expiry/best before date. Of those who read labels, only a third checked nutrition information and ingredients. Nutrient information on labels was not often read because most consumers either lacked nutrition knowledge or found the information too technical to understand. About 60 % read quality symbols. A positive association was found between education level and checking various aspects of food labels. Women and girls concerned about 'fat' and 'sugar' intake read the nutrition facts panel. The intention of promoting healthy food choices through use of food labels is not being completely met. Since a majority of people found it difficult to comprehend nutrition information, there is a need to take up educational activities and/or introduce new forms of labelling.

Abstract Background: Cervical cancer is the second most common cancer among women worldwide. Many studies have confirmed a strong correlation between p16 overexpression and high-grade premalignant or malignant lesions of the cervix. A newer biomarker ProEx C has been implicated as a useful indicator for cervical cancer. However, data on comparison between these biomarkers in cervical cancer remain limited. In this study, we investigated the expression of ProExC, p16 and Ki-67 in cervical carcinoma and ovarian tumors as comparison. Objective: To determine the value of ProEx C combined with p16 and Ki-67 in detection of cervical carcinoma. Methods: Total of 28 cases of cervical carcinoma biopsies were included in this study, among these one was adenocarcinoma and 27 cases were squamous cell carcinoma type. Ovary tissue microarray (TMA) samples (BioGenex TS-4212) were used for comparison. ProEx C antibody cocktail was prepared from rabbit monoclonal antibodies against minichromosome maintenance protein 2 (MCM2, clone ID: EPR4120) and Topoisomerase II alpha (TOP2A, clone ID: EP1102Y). All tissue samples were examined for expression of p16 and Ki67. Co-localization of ProEx C/p16 and ProEx C/Ki-67 was determined by simultaneous double stain method. Fully automated Xmatrx® system was used for the IHC staining. Results: Overexpression of ProEx C was found in all 28 cases of cervical carcinoma tissues. All the cancer cells and some other proliferative cell types showed nucleus staining pattern. Upregulated expression of p16 was observed in all 28 cases, with both nucleus and cytoplasmic staining. The p16 staining was limited within those cancer cells. Simultaneous double stain for ProEx C/p16 demonstrated that over 90% of cancer cells co-expressing these two biomarkers. Although Ki-67 staining was also observed in all the cases, a variable portion (less than 50%) of cancer cells was Ki-67 positive. ProEx C/Ki-67 double positive cells were ranging from 20% to 40% of total ProEx C positive cells. Of the 41 ovary tissues from TMA, 35 were ovarian tumor samples and ProEx C positive, 17/35 was p16 positive (48.6%). Conclusions: 1) ProEx C is a sensitive proliferation biomarker for diagnosis of cancer, which is more sensitive in determining proliferation status than that of Ki-67. 2) p16 is a more specific biomarker for cervical carcinoma than that for ovarian cancer. 3) Combination of ProEx C and p16 may increase the sensitivity and specificity in cervical cancer detection. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 334. doi:10.1158/1538-7445.AM2011-334