Introduction Several prognostic indices are in use to stratify chronic myeloid leukemia (CML) patients: Sokal, Hasford, and the European Treatment and Outcome Study (EUTOS) being the most commonly reported ones. The application of different scores may cause variability in the determination of disease prognosis. This study was conducted to stratify patients of CML in accordance with Sokal, Hasford, and EUTOS scoring systems and to determine the concordance rate of risk categories, calculated by using all three scoring systems. Methods This study was conducted at King Edward Medical University from January 2013 to May 2019. A total of 114 patients were diagnosed with CML in the chronic phase during the study period and included in the analysis. Variables of interest were computed using Microsoft Excel. These variables include age, spleen size, platelet count, the percentage of myeloblasts in the peripheral blood, as well as the percentage of basophils and eosinophils in the peripheral blood. Using these baseline variables, the prognostic category of each patient was calculated using Sokal, Hasford, and EUTOS scores. Results The male to female ratio of patients included in the study was 1.43. The mean age was 39.3±1.58 years, with an age range of 13 to 95 years. A total of only 4 out of 73 patients were categorized as a low-risk category, whereas 23 out of 80 patients were categorized into a highrisk category by all three scoring systems. The assignment of prognostic categories was variable, depending on which prognostic score was applied. The concordance rate of Sokal vs Hasford was 53%, Sokal vs EUTOS 64%, and Hasford vs EUTOS 98%. Conclusion There is considerable inter-variability between the various prognostic indicators. In general, the Hasford and EUTOS scores assign some patients to a lower risk category when compared to Sokal score.

This research aimed to explore the actual situation of information accessibility for university students with visual impairment at higher academic institutions of Lahore, Pakistan. This research adopted a qualitative research design using interpretative phenomenological analysis (IPA) to investigate the proposed phenomenon. The participants were recruited with purposive sampling from higher academic institutions for data collection. Face to face interview of 15 visually impaired students was conducted using an interview guide. The participants were debriefed for data authentication and verification at the end. Each interview was transcribed and analyzed carefully using IPA. The results indicated that these students utilized interpersonal relationships as the primary source of their academic information. The other available facilities for information access included the internet, disability resources center (if available at the institution), and the university library. The major barriers in accessing needed information included: format barriers, navigational barriers, technical barriers, ICTs illiteracy, and financial barriers. The university administration, especially libraries, should consider students with various disabilities while designing information infrastructure for its community. This research can be used as a guide by library staff in designing need-based information services for students with visual imprisonment. This research would be a worthy contribution to the existing literature as only a few studies were conducted in Pakistan.

Baig et al. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

BCR-ABL1 is a fusion protein as a result of a unique chromosomal translocation (producing the so-called Philadelphia chromosome) that serves as a clinical biomarker primarily for chronic myeloid leukemia (CML); the Philadelphia chromosome also occurs, albeit rather rarely, in other types of leukemia. This fusion protein has proven itself to be a promising therapeutic target. Exploiting the natural vitamin E molecule gamma-tocotrienol as a BCR-ABL1 inhibitor with deep learning artificial intelligence (AI) drug design, this study aims to overcome the present toxicity that embodies the currently provided medications for (Ph+) leukemia, especially asciminib. Gamma-tocotrienol was employed in an AI server for drug design to construct three effective de novo drug compounds for the BCR-ABL1 fusion protein. The AIGT’s (Artificial Intelligence Gamma-Tocotrienol) drug-likeliness analysis among the three led to its nomination as a target possibility. The toxicity assessment research comparing AIGT and asciminib demonstrates that AIGT, in addition to being more effective nonetheless, is also hepatoprotective. While almost all CML patients can achieve remission with tyrosine kinase inhibitors (such as asciminib), they are not cured in the strict sense. Hence it is important to develop new avenues to treat CML. We present in this study new formulations of AIGT. The docking of the AIGT with BCR-ABL1 exhibited a binding affinity of −7.486 kcal/mol, highlighting the AIGT’s feasibility as a pharmaceutical option. Since current medical care only exclusively cures a small number of patients of CML with utter toxicity as a pressing consequence, a new possibility to tackle adverse instances is therefore presented in this study by new formulations of natural compounds of vitamin E, gamma-tocotrienol, thoroughly designed by AI. Even though AI-designed AIGT is effective and adequately safe as computed, in vivo testing is mandatory for the verification of the in vitro results.