AN APPRAISAL OF THE COMPUTING KNOWLEDGE AND SKILLS OF STUDENTS WITH DISABILITIES IN THE UNIVERSITY OF EDUCATION, WINNEBA, GHANA

The study examined the knowledge and skills in using computers by students with disabilities at the University of Education, Winneba (UEW). The study employed the descriptive survey design which used a questionnaire to solicit information from forty-six (46) students who were randomly sampled. The study found out that majority of the students had some knowledge and skills in the use of computers. However, it was established from the results, that many of the students’ knowledge and skills about computers were inadequate for higher education level academic work. Finally, the study found out that the type of disability a person has, does not have any significant influence on their knowledge and skills for computer usage. It was recommended that students with disabilities should have access to specialized Information and Communication Technology (ICT) centre where adaptive services would be organized and delivered to enhance their skills. This ICT centre should be manned by competent ICT personnel who understand the needs of students with disabilities, and whose main responsibilities should be to attend to the technological needs of students with disabilities.  Article visualizations

MUC1-C drives myeloid leukaemogenesis and resistance to treatment by a survivin-mediated mechanism

Acute myeloid leukaemia (AML) is an aggressive haematological malignancy with an unmet need for improved therapies. Responses to standard cytotoxic therapy in AML are often transient because of the emergence of chemotherapy-resistant disease. The MUC1-C oncoprotein governs critical pathways of tumorigenesis, including self-renewal and survival, and is aberrantly expressed in AML blasts and leukaemia stem cells (LSCs). However, a role for MUC1-C in linking leukaemogenesis and resistance to treatment has not been described. In this study, we demonstrate that MUC1-C overexpression is associated with increased leukaemia initiating capacity in an NSG mouse model. In concert with those results, MUC1-C silencing in multiple AML cell lines significantly reduced the establishment of AML in vivo. In addition, targeting MUC1-C with silencing or pharmacologic inhibition with GO-203 led to a decrease in active β-catenin levels and, in-turn, down-regulation of survivin, a critical mediator of leukaemia cell survival. Targeting MUC1-C was also associated with increased sensitivity of AML cells to Cytarabine (Ara-C) treatment by a survivin-dependent mechanism. Notably, low MUC1 and survivin gene expression were associated with better clinical outcomes in patients with AML. These findings emphasize the importance of MUC1-C to myeloid leukaemogenesis and resistance to treatment by driving survivin expression. Our findings also highlight the potential translational relevance of combining GO-203 with Ara-C for the treatment of patients with AML

Nuclear charge radii of silicon isotopes

The nuclear charge radius of $^{32}$Si was determined using collinear laser spectroscopy. The experimental result was confronted with ab initio nuclear lattice effective field theory, valence-space in-medium similarity renormalization group, and mean field calculations, highlighting important achievements and challenges of modern many-body methods. The charge radius of $^{32}$Si completes the radii of the mirror pair $^{32}$Ar - $^{32}$Si, whose difference was correlated to the slope $L$ of the symmetry energy in the nuclear equation of state. Our result suggests $L \leq 60$\,MeV, which agrees with complementary observables

Carcinoma and multiple lymphomas in one patient: establishing the diagnoses and analyzing risk factors

Multiple malignancies may occur in the same patient, and a few reports describe cases with multiple hematologic and non-hematologic neoplasms. We report the case of a patient who showed the sequential occurrence of four different lymphoid neoplasms together with a squamous cell carcinoma of the lung. A 62-year-old man with adenopathy was admitted to the hospital, and lymph node biopsy was positive for low-grade follicular lymphoma. He achieved a partial remission with chemotherapy. Two years later, a PET-CT scan showed a left hilar mass in the lung; biopsy showed a squamous cell carcinoma. Simultaneously, he was diagnosed with diffuse large B cell lymphoma in a neck lymph node; after chemo- and radiotherapy, he achieved a complete response. A restaging PET-CT scan 2 years later revealed a retroperitoneal nodule, and biopsy again showed a low-grade follicular lymphoma, while a biopsy of a cutaneous scalp lesion showed a CD30-positive peripheral T cell lymphoma. After some months, a liver biopsy and a right cervical lymph node biopsy showed a CD30-positive peripheral T cell lymphoma consistent with anaplastic lymphoma kinase-negative anaplastic large cell lymphoma. Flow cytometry and cytogenetic and molecular genetic analysis performed at diagnosis and during the patient’s follow-up confirmed the presence of two clonally distinct B cell lymphomas, while the two T cell neoplasms were confirmed to be clonally related. We discuss the relationship between multiple neoplasms occurring in the same patient and the various possible risk factors involved in their development

The Society for Immunotherapy of Cancer consensus statement on immunotherapy for the treatment of hematologic malignancies: multiple myeloma, lymphoma, and acute leukemia

Increasing knowledge concerning the biology of hematologic malignancies as well as the role of the immune system in the control of these diseases has led to the development and approval of immunotherapies that are resulting in impressive clinical responses. Therefore, the Society for Immunotherapy of Cancer (SITC) convened a hematologic malignancy Cancer Immunotherapy Guidelines panel consisting of physicians, nurses, patient advocates, and patients to develop consensus recommendations for the clinical application of immunotherapy for patients with multiple myeloma, lymphoma, and acute leukemia. These recommendations were developed following the previously established process based on the Institute of Medicine’s clinical practice guidelines. In doing so, a systematic literature search was performed for high-impact studies from 2004 to 2014 and was supplemented with further literature as identified by the panel. The consensus panel met in December of 2014 with the goal to generate consensus recommendations for the clinical use of immunotherapy in patients with hematologic malignancies. During this meeting, consensus panel voting along with discussion were used to rate and review the strength of the supporting evidence from the literature search. These consensus recommendations focus on issues related to patient selection, toxicity management, clinical endpoints, and the sequencing or combination of therapies. Overall, immunotherapy is rapidly emerging as an effective therapeutic strategy for the management of hematologic malignances. Evidence-based consensus recommendations for its clinical application are provided and will be updated as the field evolves

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery