Severe Thrombocytosis in Chronic Liver Disease Secondary to Iron Deficiency Anemia: A Case Report

Thrombocytopenia is the commonest haematological abnormality seen in chronic liver disease. Thrombocytosis is of two types: Primary and secondary. In secondary form of thrombocytosis usually there is mild to moderate elevation of platelet count. Here, we present a case of 60 year old patient, a known case of chronic liver disease who presented with severe thrombocytosis secondary to iron deficiencyanaemia. Thrombocytosis normalized with treatment of iron deficiency anaemia with parenteral iron

Simulation and APL Description of the PDP 11/40

This paper describes the implementation of an assemblersimulator for the PDP 11/40 computer. It is concerned with methods used to implement an assembler, to generate code which is interpretively executed by a simulator. Program-controlled input/output as well as device-initiated input, has been implemented. The assembler-simulator programs are written in PL/l, and are implemented on the IBM 360/65.Computing and Information Science

Hypokalemic Quadriparesis Associated with Dengue: A Case Series

Dengue is an important viral cause of febrile illness in tropical and subtropical regions. Manifestations may range from an asymptomatic infection to life threatening hemorrhagic fever and shock syndrome. Neurological presentations of this disease are rare. Here, we are presenting a case series of three confirmedcases of dengue fever with hypokalemic paralysis presenting as acute pure motor reversible quadriparesis. A clinician should keep dengue virus associated hypokalemic paralysis in mind while dealing with a case of fever with quadriparesis

Moving towards a unified classification of glioblastomas utilizing artificial intelligence and deep machine learning integration

Glioblastoma a deadly brain cancer that is nearly universally fatal. Accurate prognostication and the successful application of emerging precision medicine in glioblastoma relies upon the resolution and exactitude of classification. We discuss limitations of our current classification systems and their inability to capture the full heterogeneity of the disease. We review the various layers of data that are available to substratify glioblastoma and we discuss how artificial intelligence and machine learning tools provide the opportunity to organize and integrate this data in a nuanced way. In doing so there is the potential to generate clinically relevant disease sub-stratifications, which could help predict neuro-oncological patient outcomes with greater certainty. We discuss limitations of this approach and how these might be overcome. The development of a comprehensive unified classification of glioblastoma would be a major advance in the field. This will require the fusion of advances in understanding glioblastoma biology with technological innovation in data processing and organization

Perception and preferences of second professional undergraduate medical students for pharmacology teaching: a questionnaire based cross-sectional study

Background: Feedback from students provides an opportunity to assess lacunae in current systems of teaching and forms the basis for framing desired modifications in the teaching methodology to enhance the magnitude of learning. This study was undertaken to know the views of students on current methodology of pharmacology teaching and to delineate the required changes to be made in it.Methods: The questionnaire based cross-sectional study was conducted on 167 students of second professional undergraduate medical students. The questionnaire was divided in 2 different parts. Part A consisted 20 multiple choice questions on perception and preferences of students for pharmacology teaching and opinion on changes to be made was taken in the part B of the questionnaire.Results: Pharmacology was marked as one of the most interesting and useful subjects by 49.1% and 67.06% of students respectively. Central nervous system (19.76%) and endocrinology (17.96%) were two most boring systems. The central (35.92%) and autonomic (31.73%) nervous systems were two most difficult systems to understand. The combination of lecture notes and textbooks was the preferred reading materials of 58.68% of students. The most preferred teaching media was the combination of blackboard and chalk with power point presentation (80.24%). Increased use of figures, flow charts and diagrams, inclusion of more clinical examples and interactive classes were marked as suggested reforms to enhance the outcome of lecture classes.Conclusions: This study revealed that students are in favour of a substantial change in the current teaching methodology of pharmacology in place of outdated and useless methods

Analyzing historical and future acute neurosurgical demand using an AI-enabled predictive dashboard

Characterizing acute service demand is critical for neurosurgery and other emergency-dominant specialties in order to dynamically distribute resources and ensure timely access to treatment. This is especially important in the post-Covid 19 pandemic period, when healthcare centers are grappling with a record backlog of pending surgical procedures and rising acute referral numbers. Healthcare dashboards are well-placed to analyze this data, making key information about service and clinical outcomes available to staff in an easy-to-understand format. However, they typically provide insights based on inference rather than prediction, limiting their operational utility. We retrospectively analyzed and prospectively forecasted acute neurosurgical referrals, based on 10,033 referrals made to a large volume tertiary neurosciences center in London, U.K., from the start of the Covid-19 pandemic lockdown period until October 2021 through the use of a novel AI-enabled predictive dashboard. As anticipated, weekly referral volumes significantly increased during this period, largely owing to an increase in spinal referrals (p < 0.05). Applying validated time-series forecasting methods, we found that referrals were projected to increase beyond this time-point, with Prophet demonstrating the best test and computational performance. Using a mixed-methods approach, we determined that a dashboard approach was usable, feasible, and acceptable among key stakeholders

SUPFAM: A database of sequence superfamilies of protein domains

BACKGROUND: SUPFAM database is a compilation of superfamily relationships between protein domain families of either known or unknown 3-D structure. In SUPFAM, sequence families from Pfam and structural families from SCOP are associated, using profile matching, to result in sequence superfamilies of known structure. Subsequently all-against-all family profile matches are made to deduce a list of new potential superfamilies of yet unknown structure. DESCRIPTION: The current version of SUPFAM (release 1.4) corresponds to significant enhancements and major developments compared to the earlier and basic version. In the present version we have used RPS-BLAST, which is robust and sensitive, for profile matching. The reliability of connections between protein families is ensured better than before by use of benchmarked criteria involving strict e-value cut-off and a minimal alignment length condition. An e-value based indication of reliability of connections is now presented in the database. Web access to a RPS-BLAST-based tool to associate a query sequence to one of the family profiles in SUPFAM is available with the current release. In terms of the scientific content the present release of SUPFAM is entirely reorganized with the use of 6190 Pfam families and 2317 structural families derived from SCOP. Due to a steep increase in the number of sequence and structural families used in SUPFAM the details of scientific content in the present release are almost entirely complementary to previous basic version. Of the 2286 families, we could relate 245 Pfam families with apparently no structural information to families of known 3-D structures, thus resulting in the identification of new families in the existing superfamilies. Using the profiles of 3904 Pfam families of yet unknown structure, an all-against-all comparison involving sequence-profile match resulted in clustering of 96 Pfam families into 39 new potential superfamilies. CONCLUSION: SUPFAM presents many non-trivial superfamily relationships of sequence families involved in a variety of functions and hence the information content is of interest to a wide scientific community. The grouping of related proteins without a known structure in SUPFAM is useful in identifying priority targets for structural genomics initiatives and in the assignment of putative functions. Database URL:

Efficacy of a Mindfulness-Based Intervention in Ameliorating Inattentional Blindness Amongst Young Neurosurgeons: A Prospective, Controlled Pilot Study

BACKGROUND: Human factors are increasingly being recognised as vital components of safe surgical care. One such human cognitive factor: inattention blindness (IB), describes the inability to perceive objects despite being visible, typically when one’s attention is focused on another task. This may contribute toward operative ‘never-events’ such as retained foreign objects and wrong-site surgery. METHODS: An 8-week, mindfulness-based intervention (MBI) programme, adapted for surgeons, was delivered virtually. Neurosurgical trainees and recent staff-appointees who completed the MBI were compared against a control group, matched in age, sex and grade. Attention and IB were tested using two operative videos. In each, participants were first instructed to focus on a specific part of the procedure and assessed (attention), then questioned on a separate but easily visible aspect within the operative field (inattention). If a participant were ‘inattentionally blind’ they would miss significant events occurring outside of their main focus. Median absolute error (MAE) scores were calculated for both attention and inattention. A generalised linear model was fitted for each, to determine the independent effect of mindfulness intervention on MAE. RESULTS: Thirteen neurosurgeons completed the mindfulness training (age, 30 years [range 27–35]; female:male, 5:8), compared to 15 neurosurgeons in the control group (age, 30 years [27–42]; female:male, 6:9). There were no significant demographic differences between groups. MBI participants demonstrated no significant differences on attention tasks as compared to controls (t = −1.50, p = 0.14). For inattention tasks, neurosurgeons who completed the MBI had significantly less errors (t = −2.47, p = 0.02), after adjusting for participant level and video differences versus controls. We found that both groups significantly improved their inattention error rate between videos (t = −11.37, p < 0.0001). In spite of this, MBI participants still significantly outperformed controls in inattention MAE in the second video following post-hoc analysis (MWU = 137.5, p = 0.05). DISCUSSION: Neurosurgeons who underwent an eight-week MBI had significantly reduced inattention blindness errors as compared to controls, suggesting mindfulness as a potential tool to increase vigilance and prevent operative mistakes. Our findings cautiously support further mindfulness evaluation and the implementation of these techniques within the neurosurgical training curriculum

Improving risk communication: a proof-of-concept randomised control trial assessing the impact of visual aids for neurosurgical consent

IntroductionInformed consent is a fundamental component in the work-up for surgical procedures. Statistical risk information pertaining to a procedure is by nature probabilistic and challenging to communicate, especially to those with poor numerical literacy. Visual aids and audio/video tools have previously been shown to improve patients' understanding of statistical information. In this study, we aimed to explore the impact of different methods of risk communication in healthy participants randomized to either undergo the consent process with visual aids or the standard consent process for lumbar puncture.Material and methodsHealthy individuals above 18 years old were eligible. The exclusion criteria were prior experience of the procedure or relevant medical knowledge, lack of capacity to consent, underlying cognitive impairment and hospitalised individuals. After randomisation, both groups received identical medical information about the procedure of a lumbar puncture in a hypothetical clinical scenario via different means of consent. The control group underwent the standard consent process in current clinical practice (Consent Form 1 without any illustrative examples), whereas the intervention group received additional anatomy diagrams, the Paling Palette and the Paling perspective scale. Anonymised questionnaires were received to evaluate their perception of the procedure and its associated risks.ResultsFifty-two individuals were eligible without statistically significant differences in age, sex, professional status and the familiarity of the procedure. Visual aids were noted to improve the confidence of participants to describe the risks by themselves (p = 0.009) and participants in the intervention group felt significantly less overwhelmed with medical information (p = 0.028). The enhanced consent process was found to be significantly more acceptable by participants (p = 0.03). There was a trend towards greater appropriateness (p = 0.06) and it appeared to have “good” usability (median SUS = 76.4), although this also did not reach statistical significance (p = 0.06)ConclusionVisual aids could be an appropriate alternative method for medical consent without being inferior regarding the understanding of the procedure, its risks and its benefits. Future studies could possibly compare or incorporate multiple interventions to determine the most effective tools in a larger scale of population including patients as well as healthy individuals

DCMS: A data analytics and management system for molecular simulation

Molecular Simulation (MS) is a powerful tool for studying physical/chemical features of large systems and has seen applications in many scientific and engineering domains. During the simulation process, the experiments generate a very large number of atoms and intend to observe their spatial and temporal relationships for scientific analysis. The sheer data volumes and their intensive interactions impose significant challenges for data accessing, managing, and analysis. To date, existing MS software systems fall short on storage and handling of MS data, mainly because of the missing of a platform to support applications that involve intensive data access and analytical process. In this paper, we present the database-centric molecular simulation (DCMS) system our team developed in the past few years. The main idea behind DCMS is to store MS data in a relational database management system (DBMS) to take advantage of the declarative query interface (i.e., SQL), data access methods, query processing, and optimization mechanisms of modern DBMSs. A unique challenge is to handle the analytical queries that are often compute-intensive. For that, we developed novel indexing and query processing strategies (including algorithms running on modern co-processors) as integrated components of the DBMS. As a result, researchers can upload and analyze their data using efficient functions implemented inside the DBMS. Index structures are generated to store analysis results that may be interesting to other users, so that the results are readily available without duplicating the analysis. We have developed a prototype of DCMS based on the PostgreSQL system and experiments using real MS data and workload show that DCMS significantly outperforms existing MS software systems. We also used it as a platform to test other data management issues such as security and compression